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Re-ran batch validation on all models across all sets

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Ross Wightman 4 years ago
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@ -4,47 +4,56 @@ This folder contains validation results for the models in this collection having
## Datasets
There are currently results for the ImageNet validation set and 5 additional test/label sets.
There are currently results for the ImageNet validation set and 5 additional test / label sets.
The test set results include rank and top-1/top-5 differences from clean validation. For the "Real Labels", ImageNetV2, and Sketch test sets, the differences were calculated against the full 1000 class ImageNet-1k validation set. For both the Adversarial and Rendition sets, the differences were calculated against 'clean' runs on the ImageNet-1k validation set with the same 200 classes used in each test set respectively.
### ImageNet Validation - [`results-imagenet.csv`](results-imagenet.csv)
The standard 50,000 image ImageNet-1k validation set. Model selection during training utilizes this validation set, so it is not a true test set. Question: Does anyone have the official ImageNet-1k test set classification labels now that challenges are done?
* Source: http://image-net.org/challenges/LSVRC/2012/index
* Paper: "ImageNet Large Scale Visual Recognition Challenge" - https://arxiv.org/abs/1409.0575
The standard 50,000 image ImageNet-1k validation set. Model selection during training utilizes this validation set, so it is not a true test set. Question: Does anyone have the official ImageNet-1k test set classification labels now that challenges are done?
### ImageNet-"Real Labels" - [`results-imagenet-real.csv`](results-imagenet-real.csv)
The usual ImageNet-1k validation set with a fresh new set of labels intended to improve on mistakes in the original annotation process.
* Source: https://github.com/google-research/reassessed-imagenet
* Paper: "Are we done with ImageNet?" - https://arxiv.org/abs/2006.07159
### ImageNetV2 Matched Frequency - [`results-imagenetv2-matched-frequency.csv`](results-imagenetv2-matched-frequency.csv)
An ImageNet test set of 10,000 images sampled from new images roughly 10 years after the original. Care was taken to replicate the original ImageNet curation/sampling process.
* Source: https://github.com/modestyachts/ImageNetV2
* Paper: "Do ImageNet Classifiers Generalize to ImageNet?" - https://arxiv.org/abs/1902.10811
An ImageNet test set of 10,000 images sampled from new images roughly 10 years after the original. Care was taken to replicate the original ImageNet curation/sampling process.
### ImageNet-Sketch - [`results-sketch.csv`](results-sketch.csv)
50,000 non photographic (or photos of such) images (sketches, doodles, mostly monochromatic) covering all 1000 ImageNet classes.
* Source: https://github.com/HaohanWang/ImageNet-Sketch
* Paper: "Learning Robust Global Representations by Penalizing Local Predictive Power" - https://arxiv.org/abs/1905.13549
50,000 non photographic (or photos of such) images (sketches, doodles, mostly monochromatic) covering all 1000 ImageNet classes.
### ImageNet-Adversarial - [`results-imagenet-a.csv`](results-imagenet-a.csv)
A collection of 7500 images covering 200 of the 1000 ImageNet classes. Images are naturally occuring adversarial examples that confuse typical ImageNet classifiers. This is a challenging dataset, your typical ResNet-50 will score 0% top-1.
For clean validation with same 200 classes, see [`results-imagenet-a-clean.csv`](results-imagenet-a-clean.csv)
* Source: https://github.com/hendrycks/natural-adv-examples
* Paper: "Natural Adversarial Examples" - https://arxiv.org/abs/1907.07174
A collection of 7500 images covering 200 of the 1000 ImageNet classes. Images are naturally occuring adversarial examples that confuse typical ImageNet classifiers. This is a challenging dataset, your typical ResNet-50 will score 0% top-1.
### ImageNet-Rendition - [`results-imagenet-r.csv`](results-imagenet-r.csv)
* Source: https://github.com/hendrycks/imagenet-r
* Paper: "The Many Faces of Robustness" - https://arxiv.org/abs/2006.16241
Renditions of 200 ImageNet classes resulting in 30,000 images for testing robustness.
### ImageNet-"Real Labels" - [`results-imagenet-real.csv`](results-imagenet-real.csv)
For clean validation with same 200 classes, see [`results-imagenet-r-clean.csv`](results-imagenet-r-clean.csv)
* Source: https://github.com/google-research/reassessed-imagenet
* Paper: "Are we done with ImageNet?" - https://arxiv.org/abs/2006.07159
* Source: https://github.com/hendrycks/imagenet-r
* Paper: "The Many Faces of Robustness" - https://arxiv.org/abs/2006.16241
## TODO
* Explore adding a reduced version of ImageNet-C (Corruptions) and ImageNet-P (Perturbations) from https://github.com/hendrycks/robustness. The originals are huge and image size specific.

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model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation
tf_efficientnet_l2_ns,98.550,1.450,99.820,0.180,480.31,800,0.960,bicubic
tf_efficientnet_l2_ns_475,98.500,1.500,99.830,0.170,480.31,475,0.936,bicubic
tf_efficientnet_b7_ns,97.910,2.090,99.720,0.280,66.35,600,0.949,bicubic
tf_efficientnet_b6_ns,97.630,2.370,99.580,0.420,43.04,528,0.942,bicubic
ig_resnext101_32x48d,97.620,2.380,99.700,0.300,828.41,224,0.875,bilinear
tf_efficientnet_b5_ns,97.500,2.500,99.630,0.370,30.39,456,0.934,bicubic
ig_resnext101_32x32d,97.360,2.640,99.680,0.320,468.53,224,0.875,bilinear
swsl_resnext101_32x8d,97.200,2.800,99.570,0.430,88.79,224,0.875,bilinear
tf_efficientnet_b7_ap,97.200,2.800,99.540,0.460,66.35,600,0.949,bicubic
tf_efficientnet_b8,97.200,2.800,99.500,0.500,87.41,672,0.954,bicubic
tf_efficientnet_b8_ap,97.110,2.890,99.660,0.340,87.41,672,0.954,bicubic
tf_efficientnet_b6_ap,97.080,2.920,99.620,0.380,43.04,528,0.942,bicubic
tf_efficientnet_b7,97.010,2.990,99.520,0.480,66.35,600,0.949,bicubic
tf_efficientnet_b4_ns,96.950,3.050,99.580,0.420,19.34,380,0.922,bicubic
ig_resnext101_32x16d,96.820,3.180,99.590,0.410,194.03,224,0.875,bilinear
tf_efficientnet_b5_ap,96.680,3.320,99.460,0.540,30.39,456,0.934,bicubic
tf_efficientnet_b6,96.670,3.330,99.370,0.630,43.04,528,0.942,bicubic
resnest200e,96.610,3.390,99.350,0.650,70.20,320,0.909,bicubic
swsl_resnext101_32x16d,96.600,3.400,99.520,0.480,194.03,224,0.875,bilinear
resnest269e,96.520,3.480,99.350,0.650,110.93,416,0.928,bicubic
swsl_resnext101_32x4d,96.420,3.580,99.470,0.530,44.18,224,0.875,bilinear
tf_efficientnet_b3_ns,96.390,3.610,99.350,0.650,12.23,300,0.904,bicubic
tf_efficientnet_b5,96.350,3.650,99.310,0.690,30.39,456,0.934,bicubic
ig_resnext101_32x8d,96.320,3.680,99.430,0.570,88.79,224,0.875,bilinear
tf_efficientnet_b4_ap,96.160,3.840,99.280,0.720,19.34,380,0.922,bicubic
tresnet_xl_448,95.970,4.030,99.130,0.870,78.44,448,0.875,bilinear
tf_efficientnet_b4,95.900,4.100,99.170,0.830,19.34,380,0.922,bicubic
swsl_resnext50_32x4d,95.870,4.130,99.250,0.750,25.03,224,0.875,bilinear
resnest101e,95.860,4.140,99.210,0.790,48.28,256,0.875,bilinear
tresnet_l_448,95.860,4.140,99.120,0.880,55.99,448,0.875,bilinear
ssl_resnext101_32x16d,95.800,4.200,99.180,0.820,194.03,224,0.875,bilinear
tf_efficientnet_b2_ns,95.770,4.230,99.120,0.880,9.11,260,0.890,bicubic
pnasnet5large,95.710,4.290,98.920,1.080,86.06,331,0.911,bicubic
nasnetalarge,95.680,4.320,98.930,1.070,88.75,331,0.911,bicubic
ecaresnet101d,95.530,4.470,99.130,0.870,44.57,224,0.875,bicubic
ssl_resnext101_32x8d,95.470,4.530,99.110,0.890,88.79,224,0.875,bilinear
ssl_resnext101_32x4d,95.440,4.560,99.130,0.870,44.18,224,0.875,bilinear
tresnet_xl,95.440,4.560,99.050,0.950,78.44,224,0.875,bilinear
swsl_resnet50,95.410,4.590,99.290,0.710,25.56,224,0.875,bilinear
tf_efficientnet_b3_ap,95.320,4.680,98.900,1.100,12.23,300,0.904,bicubic
tresnet_l,95.290,4.710,99.010,0.990,55.99,224,0.875,bilinear
efficientnet_b3a,95.260,4.740,98.930,1.070,12.23,320,1.000,bicubic
tf_efficientnet_b1_ns,95.170,4.830,99.110,0.890,7.79,240,0.882,bicubic
ecaresnet101d_pruned,95.080,4.920,98.980,1.020,24.88,224,0.875,bicubic
efficientnet_b3,95.080,4.920,98.980,1.020,12.23,300,0.904,bicubic
gluon_resnet152_v1s,95.040,4.960,98.930,1.070,60.32,224,0.875,bicubic
tf_efficientnet_b3,95.010,4.990,98.910,1.090,12.23,300,0.904,bicubic
tresnet_m_448,94.990,5.010,98.980,1.020,31.39,448,0.875,bilinear
resnest50d_4s2x40d,94.960,5.040,99.070,0.930,30.42,224,0.875,bicubic
rexnet_200,94.940,5.060,99.010,0.990,16.37,224,0.875,bicubic
gluon_seresnext101_64x4d,94.930,5.070,98.830,1.170,88.23,224,0.875,bicubic
gluon_senet154,94.920,5.080,98.760,1.240,115.09,224,0.875,bicubic
gluon_seresnext101_32x4d,94.920,5.080,98.810,1.190,48.96,224,0.875,bicubic
tf_efficientnet_lite4,94.890,5.110,99.020,0.980,13.01,380,0.920,bilinear
ssl_resnext50_32x4d,94.870,5.130,98.880,1.120,25.03,224,0.875,bilinear
resnest50d,94.830,5.170,98.880,1.120,27.48,224,0.875,bilinear
ecaresnetlight,94.770,5.230,98.800,1.200,30.16,224,0.875,bicubic
resnest50d_1s4x24d,94.750,5.250,98.980,1.020,25.68,224,0.875,bicubic
gluon_resnet152_v1d,94.740,5.260,98.740,1.260,60.21,224,0.875,bicubic
gluon_resnet101_v1s,94.720,5.280,98.820,1.180,44.67,224,0.875,bicubic
efficientnet_b2,94.700,5.300,98.670,1.330,9.11,260,0.875,bicubic
gluon_resnext101_64x4d,94.670,5.330,98.650,1.350,83.46,224,0.875,bicubic
cspdarknet53,94.660,5.340,98.800,1.200,27.64,256,0.887,bilinear
ecaresnet50d,94.630,5.370,98.890,1.110,25.58,224,0.875,bicubic
efficientnet_b3_pruned,94.630,5.370,98.760,1.240,9.86,300,0.904,bicubic
tresnet_m,94.620,5.380,98.550,1.450,31.39,224,0.875,bilinear
efficientnet_b2a,94.610,5.390,98.710,1.290,9.11,288,1.000,bicubic
tf_efficientnet_el,94.590,5.410,98.750,1.250,10.59,300,0.904,bicubic
seresnet50,94.550,5.450,98.750,1.250,28.09,224,0.875,bicubic
inception_resnet_v2,94.540,5.460,98.790,1.210,55.84,299,0.897,bicubic
regnety_320,94.540,5.460,98.850,1.150,145.05,224,0.875,bicubic
gluon_resnext101_32x4d,94.530,5.470,98.630,1.370,44.18,224,0.875,bicubic
tf_efficientnet_b2_ap,94.490,5.510,98.620,1.380,9.11,260,0.890,bicubic
regnety_120,94.480,5.520,98.810,1.190,51.82,224,0.875,bicubic
rexnet_150,94.480,5.520,98.790,1.210,9.73,224,0.875,bicubic
cspresnext50,94.480,5.520,98.680,1.320,20.57,224,0.875,bilinear
regnetx_320,94.460,5.540,98.740,1.260,107.81,224,0.875,bicubic
ssl_resnet50,94.450,5.550,98.920,1.080,25.56,224,0.875,bilinear
inception_v4,94.380,5.620,98.580,1.420,42.68,299,0.875,bicubic
tf_efficientnet_b2,94.360,5.640,98.610,1.390,9.11,260,0.890,bicubic
gluon_seresnext50_32x4d,94.340,5.660,98.610,1.390,27.56,224,0.875,bicubic
regnety_160,94.340,5.660,98.850,1.150,83.59,224,0.875,bicubic
dpn107,94.310,5.690,98.480,1.520,86.92,224,0.875,bicubic
xception71,94.280,5.720,98.640,1.360,42.34,299,0.903,bicubic
gluon_xception65,94.260,5.740,98.570,1.430,39.92,299,0.903,bicubic
skresnext50_32x4d,94.260,5.740,98.460,1.540,27.48,224,0.875,bicubic
regnetx_120,94.240,5.760,98.650,1.350,46.11,224,0.875,bicubic
dpn92,94.230,5.770,98.730,1.270,37.67,224,0.875,bicubic
ecaresnet50d_pruned,94.220,5.780,98.730,1.270,19.94,224,0.875,bicubic
gluon_resnet101_v1d,94.220,5.780,98.550,1.450,44.57,224,0.875,bicubic
tf_efficientnet_lite3,94.200,5.800,98.640,1.360,8.20,300,0.904,bilinear
mixnet_xl,94.190,5.810,98.340,1.660,11.90,224,0.875,bicubic
resnext50d_32x4d,94.180,5.820,98.570,1.430,25.05,224,0.875,bicubic
regnety_080,94.170,5.830,98.680,1.320,39.18,224,0.875,bicubic
ens_adv_inception_resnet_v2,94.160,5.840,98.600,1.400,55.84,299,0.897,bicubic
gluon_resnet152_v1c,94.160,5.840,98.640,1.360,60.21,224,0.875,bicubic
regnety_064,94.150,5.850,98.730,1.270,30.58,224,0.875,bicubic
efficientnet_b2_pruned,94.140,5.860,98.530,1.470,8.31,260,0.890,bicubic
dpn98,94.130,5.870,98.570,1.430,61.57,224,0.875,bicubic
regnetx_160,94.120,5.880,98.750,1.250,54.28,224,0.875,bicubic
resnext50_32x4d,94.100,5.900,98.350,1.650,25.03,224,0.875,bicubic
ese_vovnet39b,94.090,5.910,98.660,1.340,24.57,224,0.875,bicubic
gluon_resnet152_v1b,94.080,5.920,98.450,1.550,60.19,224,0.875,bicubic
dpn131,94.010,5.990,98.720,1.280,79.25,224,0.875,bicubic
hrnet_w64,94.010,5.990,98.610,1.390,128.06,224,0.875,bilinear
resnetblur50,93.960,6.040,98.590,1.410,25.56,224,0.875,bicubic
dla102x2,93.950,6.050,98.490,1.510,41.28,224,0.875,bilinear
hrnet_w48,93.920,6.080,98.610,1.390,77.47,224,0.875,bilinear
rexnet_130,93.900,6.100,98.400,1.600,7.56,224,0.875,bicubic
tf_efficientnet_cc_b1_8e,93.900,6.100,98.260,1.740,39.72,240,0.882,bicubic
regnetx_064,93.890,6.110,98.630,1.370,26.21,224,0.875,bicubic
regnetx_080,93.870,6.130,98.520,1.480,39.57,224,0.875,bicubic
regnety_040,93.860,6.140,98.650,1.350,20.65,224,0.875,bicubic
resnext101_32x8d,93.830,6.170,98.580,1.420,88.79,224,0.875,bilinear
gluon_resnext50_32x4d,93.810,6.190,98.410,1.590,25.03,224,0.875,bicubic
resnet50,93.810,6.190,98.390,1.610,25.56,224,0.875,bicubic
gluon_resnet50_v1d,93.770,6.230,98.390,1.610,25.58,224,0.875,bicubic
xception65,93.760,6.240,98.370,1.630,39.92,299,0.903,bicubic
gluon_resnet101_v1b,93.750,6.250,98.380,1.620,44.55,224,0.875,bicubic
res2net101_26w_4s,93.750,6.250,98.310,1.690,45.21,224,0.875,bilinear
wide_resnet101_2,93.720,6.280,98.540,1.460,126.89,224,0.875,bilinear
dpn68b,93.690,6.310,98.510,1.490,12.61,224,0.875,bicubic
tf_efficientnet_b1_ap,93.690,6.310,98.360,1.640,7.79,240,0.882,bicubic
gluon_resnet101_v1c,93.670,6.330,98.420,1.580,44.57,224,0.875,bicubic
tf_efficientnet_b0_ns,93.630,6.370,98.640,1.360,5.29,224,0.875,bicubic
gluon_resnet50_v1s,93.620,6.380,98.460,1.540,25.68,224,0.875,bicubic
regnetx_040,93.560,6.440,98.540,1.460,22.12,224,0.875,bicubic
hrnet_w44,93.550,6.450,98.700,1.300,67.06,224,0.875,bilinear
res2net50_26w_8s,93.540,6.460,98.260,1.740,48.40,224,0.875,bilinear
hrnet_w32,93.530,6.470,98.450,1.550,41.23,224,0.875,bilinear
dla102x,93.520,6.480,98.510,1.490,26.31,224,0.875,bilinear
tf_efficientnet_b1,93.500,6.500,98.360,1.640,7.79,240,0.882,bicubic
hrnet_w40,93.490,6.510,98.580,1.420,57.56,224,0.875,bilinear
tf_efficientnet_em,93.480,6.520,98.440,1.560,6.90,240,0.882,bicubic
gluon_inception_v3,93.460,6.540,98.570,1.430,23.83,299,0.875,bicubic
xception,93.460,6.540,98.530,1.470,22.86,299,0.897,bicubic
mixnet_l,93.450,6.550,98.220,1.780,7.33,224,0.875,bicubic
xception41,93.430,6.570,98.430,1.570,26.97,299,0.903,bicubic
res2net50_26w_6s,93.410,6.590,98.280,1.720,37.05,224,0.875,bilinear
regnety_032,93.390,6.610,98.640,1.360,19.44,224,0.875,bicubic
dla169,93.340,6.660,98.600,1.400,53.39,224,0.875,bilinear
resnest26d,93.330,6.670,98.630,1.370,17.07,224,0.875,bilinear
tf_inception_v3,93.320,6.680,98.030,1.970,23.83,299,0.875,bicubic
tf_mixnet_l,93.310,6.690,98.030,1.970,7.33,224,0.875,bicubic
resnet152,93.300,6.700,98.390,1.610,60.19,224,0.875,bilinear
selecsls60b,93.300,6.700,98.280,1.720,32.77,224,0.875,bicubic
efficientnet_b1,93.260,6.740,98.170,1.830,7.79,240,0.875,bicubic
hrnet_w30,93.200,6.800,98.410,1.590,37.71,224,0.875,bilinear
dla60_res2net,93.180,6.820,98.420,1.580,20.85,224,0.875,bilinear
dla60_res2next,93.180,6.820,98.410,1.590,17.03,224,0.875,bilinear
wide_resnet50_2,93.170,6.830,98.350,1.650,68.88,224,0.875,bilinear
efficientnet_es,93.140,6.860,98.420,1.580,5.44,224,0.875,bicubic
dla60x,93.120,6.880,98.510,1.490,17.35,224,0.875,bilinear
regnetx_032,93.120,6.880,98.390,1.610,15.30,224,0.875,bicubic
seresnext26t_32x4d,93.070,6.930,98.110,1.890,16.82,224,0.875,bicubic
dla102,93.060,6.940,98.540,1.460,33.27,224,0.875,bilinear
gluon_resnet50_v1c,93.030,6.970,98.390,1.610,25.58,224,0.875,bicubic
regnety_016,93.030,6.970,98.360,1.640,11.20,224,0.875,bicubic
rexnet_100,93.030,6.970,98.190,1.810,4.80,224,0.875,bicubic
selecsls60,93.030,6.970,98.300,1.700,30.67,224,0.875,bicubic
adv_inception_v3,92.880,7.120,98.140,1.860,23.83,299,0.875,bicubic
res2next50,92.840,7.160,98.180,1.820,24.67,224,0.875,bilinear
tf_efficientnet_cc_b0_8e,92.830,7.170,98.180,1.820,24.01,224,0.875,bicubic
seresnext26tn_32x4d,92.820,7.180,98.370,1.630,16.81,224,0.875,bicubic
resnet101,92.810,7.190,98.250,1.750,44.55,224,0.875,bilinear
efficientnet_b1_pruned,92.770,7.230,98.040,1.960,6.33,240,0.882,bicubic
densenet201,92.750,7.250,98.230,1.770,20.01,224,0.875,bicubic
res2net50_14w_8s,92.740,7.260,98.180,1.820,25.06,224,0.875,bilinear
tv_resnext50_32x4d,92.740,7.260,98.270,1.730,25.03,224,0.875,bilinear
inception_v3,92.720,7.280,97.970,2.030,23.83,299,0.875,bicubic
seresnext26d_32x4d,92.700,7.300,98.150,1.850,16.81,224,0.875,bicubic
efficientnet_b0,92.690,7.310,98.070,1.930,5.29,224,0.875,bicubic
tf_efficientnet_lite2,92.650,7.350,98.230,1.770,6.09,260,0.890,bicubic
tf_efficientnet_lite1,92.620,7.380,98.080,1.920,5.42,240,0.882,bicubic
tf_efficientnet_cc_b0_4e,92.590,7.410,98.080,1.920,13.31,224,0.875,bicubic
res2net50_48w_2s,92.550,7.450,98.080,1.920,25.29,224,0.875,bilinear
tf_efficientnet_es,92.550,7.450,98.280,1.720,5.44,224,0.875,bicubic
gluon_resnet50_v1b,92.540,7.460,98.170,1.830,25.56,224,0.875,bicubic
densenet161,92.500,7.500,98.290,1.710,28.68,224,0.875,bicubic
res2net50_26w_4s,92.500,7.500,98.060,1.940,25.70,224,0.875,bilinear
mixnet_m,92.430,7.570,97.870,2.130,5.01,224,0.875,bicubic
mobilenetv2_120d,92.400,7.600,98.050,1.950,5.83,224,0.875,bicubic
skresnet34,92.390,7.610,98.150,1.850,22.28,224,0.875,bicubic
tf_mixnet_m,92.330,7.670,97.890,2.110,5.01,224,0.875,bicubic
hrnet_w18,92.320,7.680,98.240,1.760,21.30,224,0.875,bilinear
ese_vovnet19b_dw,92.290,7.710,98.090,1.910,6.54,224,0.875,bicubic
selecsls42b,92.280,7.720,98.150,1.850,32.46,224,0.875,bicubic
tf_efficientnet_b0,92.250,7.750,98.000,2.000,5.29,224,0.875,bicubic
dla60,92.230,7.770,98.110,1.890,22.04,224,0.875,bilinear
tf_efficientnet_b0_ap,92.200,7.800,98.020,1.980,5.29,224,0.875,bicubic
regnetx_016,92.170,7.830,98.210,1.790,9.19,224,0.875,bicubic
resnet26d,92.070,7.930,97.960,2.040,16.01,224,0.875,bicubic
dpn68,92.010,7.990,98.050,1.950,12.61,224,0.875,bicubic
densenet169,91.930,8.070,98.100,1.900,14.15,224,0.875,bicubic
densenetblur121d,91.910,8.090,98.070,1.930,8.00,224,0.875,bicubic
tv_resnet50,91.880,8.120,98.040,1.960,25.56,224,0.875,bilinear
mobilenetv2_140,91.830,8.170,97.860,2.140,6.11,224,0.875,bicubic
mixnet_s,91.830,8.170,97.690,2.310,4.13,224,0.875,bicubic
regnety_008,91.750,8.250,98.180,1.820,6.26,224,0.875,bicubic
resnest14d,91.720,8.280,97.870,2.130,10.61,224,0.875,bilinear
densenet121,91.570,8.430,98.030,1.970,7.98,224,0.875,bicubic
tf_mixnet_s,91.510,8.490,97.620,2.380,4.13,224,0.875,bicubic
regnety_006,91.370,8.630,97.710,2.290,6.06,224,0.875,bicubic
mobilenetv3_large_100,91.320,8.680,97.710,2.290,5.48,224,0.875,bicubic
semnasnet_100,91.280,8.720,97.560,2.440,3.89,224,0.875,bicubic
tf_mobilenetv3_large_100,91.240,8.760,97.660,2.340,5.48,224,0.875,bilinear
mobilenetv3_rw,91.210,8.790,97.660,2.340,5.48,224,0.875,bicubic
hrnet_w18_small_v2,91.190,8.810,97.900,2.100,15.60,224,0.875,bilinear
efficientnet_lite0,91.140,8.860,97.630,2.370,4.65,224,0.875,bicubic
resnet34,91.130,8.870,97.620,2.380,21.80,224,0.875,bilinear
resnet26,91.110,8.890,97.740,2.260,16.00,224,0.875,bicubic
regnetx_008,91.050,8.950,97.710,2.290,7.26,224,0.875,bicubic
tf_efficientnet_lite0,91.040,8.960,97.590,2.410,4.65,224,0.875,bicubic
gluon_resnet34_v1b,90.960,9.040,97.630,2.370,21.80,224,0.875,bicubic
mobilenetv2_110d,90.950,9.050,97.550,2.450,4.52,224,0.875,bicubic
tv_densenet121,90.890,9.110,97.710,2.290,7.98,224,0.875,bicubic
dla34,90.760,9.240,97.660,2.340,15.74,224,0.875,bilinear
fbnetc_100,90.700,9.300,97.210,2.790,5.57,224,0.875,bilinear
swsl_resnet18,90.690,9.310,97.700,2.300,11.69,224,0.875,bilinear
mnasnet_100,90.510,9.490,97.470,2.530,4.38,224,0.875,bicubic
regnety_004,90.500,9.500,97.540,2.460,4.34,224,0.875,bicubic
regnetx_006,90.350,9.650,97.430,2.570,6.20,224,0.875,bicubic
spnasnet_100,90.350,9.650,97.190,2.810,4.42,224,0.875,bilinear
ssl_resnet18,90.220,9.780,97.550,2.450,11.69,224,0.875,bilinear
tv_resnet34,89.940,10.060,97.340,2.660,21.80,224,0.875,bilinear
tf_mobilenetv3_large_075,89.680,10.320,97.210,2.790,3.99,224,0.875,bilinear
skresnet18,89.660,10.340,97.230,2.770,11.96,224,0.875,bicubic
mobilenetv2_100,89.600,10.400,97.140,2.860,3.50,224,0.875,bicubic
hrnet_w18_small,89.050,10.950,97.110,2.890,13.19,224,0.875,bilinear
tf_mobilenetv3_large_minimal_100,88.970,11.030,96.860,3.140,3.92,224,0.875,bilinear
regnetx_004,88.900,11.100,97.120,2.880,5.16,224,0.875,bicubic
gluon_resnet18_v1b,88.400,11.600,96.680,3.320,11.69,224,0.875,bicubic
resnet18,87.390,12.610,96.290,3.710,11.69,224,0.875,bilinear
regnety_002,87.380,12.620,96.590,3.410,3.16,224,0.875,bicubic
dla60x_c,86.290,13.710,96.160,3.840,1.32,224,0.875,bilinear
regnetx_002,86.190,13.810,95.980,4.020,2.68,224,0.875,bicubic
tf_mobilenetv3_small_100,85.190,14.810,95.770,4.230,2.54,224,0.875,bilinear
dla46x_c,84.250,15.750,95.270,4.730,1.07,224,0.875,bilinear
dla46_c,83.650,16.350,94.920,5.080,1.30,224,0.875,bilinear
tf_mobilenetv3_small_075,83.520,16.480,94.790,5.210,2.04,224,0.875,bilinear
tf_mobilenetv3_small_minimal_100,81.380,18.620,93.670,6.330,2.04,224,0.875,bilinear
1 model top1 top1_err top5 top5_err param_count img_size cropt_pct interpolation
2 tf_efficientnet_l2_ns 98.550 1.450 99.820 0.180 480.31 800 0.960 bicubic
3 tf_efficientnet_l2_ns_475 98.500 1.500 99.830 0.170 480.31 475 0.936 bicubic
4 tf_efficientnet_b7_ns 97.910 2.090 99.720 0.280 66.35 600 0.949 bicubic
5 tf_efficientnet_b6_ns 97.630 2.370 99.580 0.420 43.04 528 0.942 bicubic
6 ig_resnext101_32x48d 97.620 2.380 99.700 0.300 828.41 224 0.875 bilinear
7 tf_efficientnet_b5_ns 97.500 2.500 99.630 0.370 30.39 456 0.934 bicubic
8 ig_resnext101_32x32d 97.360 2.640 99.680 0.320 468.53 224 0.875 bilinear
9 swsl_resnext101_32x8d 97.200 2.800 99.570 0.430 88.79 224 0.875 bilinear
10 tf_efficientnet_b7_ap 97.200 2.800 99.540 0.460 66.35 600 0.949 bicubic
11 tf_efficientnet_b8 97.200 2.800 99.500 0.500 87.41 672 0.954 bicubic
12 tf_efficientnet_b8_ap 97.110 2.890 99.660 0.340 87.41 672 0.954 bicubic
13 tf_efficientnet_b6_ap 97.080 2.920 99.620 0.380 43.04 528 0.942 bicubic
14 tf_efficientnet_b7 97.010 2.990 99.520 0.480 66.35 600 0.949 bicubic
15 tf_efficientnet_b4_ns 96.950 3.050 99.580 0.420 19.34 380 0.922 bicubic
16 ig_resnext101_32x16d 96.820 3.180 99.590 0.410 194.03 224 0.875 bilinear
17 tf_efficientnet_b5_ap 96.680 3.320 99.460 0.540 30.39 456 0.934 bicubic
18 tf_efficientnet_b6 96.670 3.330 99.370 0.630 43.04 528 0.942 bicubic
19 resnest200e 96.610 3.390 99.350 0.650 70.20 320 0.909 bicubic
20 swsl_resnext101_32x16d 96.600 3.400 99.520 0.480 194.03 224 0.875 bilinear
21 resnest269e 96.520 3.480 99.350 0.650 110.93 416 0.928 bicubic
22 swsl_resnext101_32x4d 96.420 3.580 99.470 0.530 44.18 224 0.875 bilinear
23 tf_efficientnet_b3_ns 96.390 3.610 99.350 0.650 12.23 300 0.904 bicubic
24 tf_efficientnet_b5 96.350 3.650 99.310 0.690 30.39 456 0.934 bicubic
25 ig_resnext101_32x8d 96.320 3.680 99.430 0.570 88.79 224 0.875 bilinear
26 tf_efficientnet_b4_ap 96.160 3.840 99.280 0.720 19.34 380 0.922 bicubic
27 tresnet_xl_448 95.970 4.030 99.130 0.870 78.44 448 0.875 bilinear
28 tf_efficientnet_b4 95.900 4.100 99.170 0.830 19.34 380 0.922 bicubic
29 swsl_resnext50_32x4d 95.870 4.130 99.250 0.750 25.03 224 0.875 bilinear
30 resnest101e 95.860 4.140 99.210 0.790 48.28 256 0.875 bilinear
31 tresnet_l_448 95.860 4.140 99.120 0.880 55.99 448 0.875 bilinear
32 ssl_resnext101_32x16d 95.800 4.200 99.180 0.820 194.03 224 0.875 bilinear
33 tf_efficientnet_b2_ns 95.770 4.230 99.120 0.880 9.11 260 0.890 bicubic
34 pnasnet5large 95.710 4.290 98.920 1.080 86.06 331 0.911 bicubic
35 nasnetalarge 95.680 4.320 98.930 1.070 88.75 331 0.911 bicubic
36 ecaresnet101d 95.530 4.470 99.130 0.870 44.57 224 0.875 bicubic
37 ssl_resnext101_32x8d 95.470 4.530 99.110 0.890 88.79 224 0.875 bilinear
38 ssl_resnext101_32x4d 95.440 4.560 99.130 0.870 44.18 224 0.875 bilinear
39 tresnet_xl 95.440 4.560 99.050 0.950 78.44 224 0.875 bilinear
40 swsl_resnet50 95.410 4.590 99.290 0.710 25.56 224 0.875 bilinear
41 tf_efficientnet_b3_ap 95.320 4.680 98.900 1.100 12.23 300 0.904 bicubic
42 tresnet_l 95.290 4.710 99.010 0.990 55.99 224 0.875 bilinear
43 efficientnet_b3a 95.260 4.740 98.930 1.070 12.23 320 1.000 bicubic
44 tf_efficientnet_b1_ns 95.170 4.830 99.110 0.890 7.79 240 0.882 bicubic
45 ecaresnet101d_pruned 95.080 4.920 98.980 1.020 24.88 224 0.875 bicubic
46 efficientnet_b3 95.080 4.920 98.980 1.020 12.23 300 0.904 bicubic
47 gluon_resnet152_v1s 95.040 4.960 98.930 1.070 60.32 224 0.875 bicubic
48 tf_efficientnet_b3 95.010 4.990 98.910 1.090 12.23 300 0.904 bicubic
49 tresnet_m_448 94.990 5.010 98.980 1.020 31.39 448 0.875 bilinear
50 resnest50d_4s2x40d 94.960 5.040 99.070 0.930 30.42 224 0.875 bicubic
51 rexnet_200 94.940 5.060 99.010 0.990 16.37 224 0.875 bicubic
52 gluon_seresnext101_64x4d 94.930 5.070 98.830 1.170 88.23 224 0.875 bicubic
53 gluon_senet154 94.920 5.080 98.760 1.240 115.09 224 0.875 bicubic
54 gluon_seresnext101_32x4d 94.920 5.080 98.810 1.190 48.96 224 0.875 bicubic
55 tf_efficientnet_lite4 94.890 5.110 99.020 0.980 13.01 380 0.920 bilinear
56 ssl_resnext50_32x4d 94.870 5.130 98.880 1.120 25.03 224 0.875 bilinear
57 resnest50d 94.830 5.170 98.880 1.120 27.48 224 0.875 bilinear
58 ecaresnetlight 94.770 5.230 98.800 1.200 30.16 224 0.875 bicubic
59 resnest50d_1s4x24d 94.750 5.250 98.980 1.020 25.68 224 0.875 bicubic
60 gluon_resnet152_v1d 94.740 5.260 98.740 1.260 60.21 224 0.875 bicubic
61 gluon_resnet101_v1s 94.720 5.280 98.820 1.180 44.67 224 0.875 bicubic
62 efficientnet_b2 94.700 5.300 98.670 1.330 9.11 260 0.875 bicubic
63 gluon_resnext101_64x4d 94.670 5.330 98.650 1.350 83.46 224 0.875 bicubic
64 cspdarknet53 94.660 5.340 98.800 1.200 27.64 256 0.887 bilinear
65 ecaresnet50d 94.630 5.370 98.890 1.110 25.58 224 0.875 bicubic
66 efficientnet_b3_pruned 94.630 5.370 98.760 1.240 9.86 300 0.904 bicubic
67 tresnet_m 94.620 5.380 98.550 1.450 31.39 224 0.875 bilinear
68 efficientnet_b2a 94.610 5.390 98.710 1.290 9.11 288 1.000 bicubic
69 tf_efficientnet_el 94.590 5.410 98.750 1.250 10.59 300 0.904 bicubic
70 seresnet50 94.550 5.450 98.750 1.250 28.09 224 0.875 bicubic
71 inception_resnet_v2 94.540 5.460 98.790 1.210 55.84 299 0.897 bicubic
72 regnety_320 94.540 5.460 98.850 1.150 145.05 224 0.875 bicubic
73 gluon_resnext101_32x4d 94.530 5.470 98.630 1.370 44.18 224 0.875 bicubic
74 tf_efficientnet_b2_ap 94.490 5.510 98.620 1.380 9.11 260 0.890 bicubic
75 regnety_120 94.480 5.520 98.810 1.190 51.82 224 0.875 bicubic
76 rexnet_150 94.480 5.520 98.790 1.210 9.73 224 0.875 bicubic
77 cspresnext50 94.480 5.520 98.680 1.320 20.57 224 0.875 bilinear
78 regnetx_320 94.460 5.540 98.740 1.260 107.81 224 0.875 bicubic
79 ssl_resnet50 94.450 5.550 98.920 1.080 25.56 224 0.875 bilinear
80 inception_v4 94.380 5.620 98.580 1.420 42.68 299 0.875 bicubic
81 tf_efficientnet_b2 94.360 5.640 98.610 1.390 9.11 260 0.890 bicubic
82 gluon_seresnext50_32x4d 94.340 5.660 98.610 1.390 27.56 224 0.875 bicubic
83 regnety_160 94.340 5.660 98.850 1.150 83.59 224 0.875 bicubic
84 dpn107 94.310 5.690 98.480 1.520 86.92 224 0.875 bicubic
85 xception71 94.280 5.720 98.640 1.360 42.34 299 0.903 bicubic
86 gluon_xception65 94.260 5.740 98.570 1.430 39.92 299 0.903 bicubic
87 skresnext50_32x4d 94.260 5.740 98.460 1.540 27.48 224 0.875 bicubic
88 regnetx_120 94.240 5.760 98.650 1.350 46.11 224 0.875 bicubic
89 dpn92 94.230 5.770 98.730 1.270 37.67 224 0.875 bicubic
90 ecaresnet50d_pruned 94.220 5.780 98.730 1.270 19.94 224 0.875 bicubic
91 gluon_resnet101_v1d 94.220 5.780 98.550 1.450 44.57 224 0.875 bicubic
92 tf_efficientnet_lite3 94.200 5.800 98.640 1.360 8.20 300 0.904 bilinear
93 mixnet_xl 94.190 5.810 98.340 1.660 11.90 224 0.875 bicubic
94 resnext50d_32x4d 94.180 5.820 98.570 1.430 25.05 224 0.875 bicubic
95 regnety_080 94.170 5.830 98.680 1.320 39.18 224 0.875 bicubic
96 ens_adv_inception_resnet_v2 94.160 5.840 98.600 1.400 55.84 299 0.897 bicubic
97 gluon_resnet152_v1c 94.160 5.840 98.640 1.360 60.21 224 0.875 bicubic
98 regnety_064 94.150 5.850 98.730 1.270 30.58 224 0.875 bicubic
99 efficientnet_b2_pruned 94.140 5.860 98.530 1.470 8.31 260 0.890 bicubic
100 dpn98 94.130 5.870 98.570 1.430 61.57 224 0.875 bicubic
101 regnetx_160 94.120 5.880 98.750 1.250 54.28 224 0.875 bicubic
102 resnext50_32x4d 94.100 5.900 98.350 1.650 25.03 224 0.875 bicubic
103 ese_vovnet39b 94.090 5.910 98.660 1.340 24.57 224 0.875 bicubic
104 gluon_resnet152_v1b 94.080 5.920 98.450 1.550 60.19 224 0.875 bicubic
105 dpn131 94.010 5.990 98.720 1.280 79.25 224 0.875 bicubic
106 hrnet_w64 94.010 5.990 98.610 1.390 128.06 224 0.875 bilinear
107 resnetblur50 93.960 6.040 98.590 1.410 25.56 224 0.875 bicubic
108 dla102x2 93.950 6.050 98.490 1.510 41.28 224 0.875 bilinear
109 hrnet_w48 93.920 6.080 98.610 1.390 77.47 224 0.875 bilinear
110 rexnet_130 93.900 6.100 98.400 1.600 7.56 224 0.875 bicubic
111 tf_efficientnet_cc_b1_8e 93.900 6.100 98.260 1.740 39.72 240 0.882 bicubic
112 regnetx_064 93.890 6.110 98.630 1.370 26.21 224 0.875 bicubic
113 regnetx_080 93.870 6.130 98.520 1.480 39.57 224 0.875 bicubic
114 regnety_040 93.860 6.140 98.650 1.350 20.65 224 0.875 bicubic
115 resnext101_32x8d 93.830 6.170 98.580 1.420 88.79 224 0.875 bilinear
116 gluon_resnext50_32x4d 93.810 6.190 98.410 1.590 25.03 224 0.875 bicubic
117 resnet50 93.810 6.190 98.390 1.610 25.56 224 0.875 bicubic
118 gluon_resnet50_v1d 93.770 6.230 98.390 1.610 25.58 224 0.875 bicubic
119 xception65 93.760 6.240 98.370 1.630 39.92 299 0.903 bicubic
120 gluon_resnet101_v1b 93.750 6.250 98.380 1.620 44.55 224 0.875 bicubic
121 res2net101_26w_4s 93.750 6.250 98.310 1.690 45.21 224 0.875 bilinear
122 wide_resnet101_2 93.720 6.280 98.540 1.460 126.89 224 0.875 bilinear
123 dpn68b 93.690 6.310 98.510 1.490 12.61 224 0.875 bicubic
124 tf_efficientnet_b1_ap 93.690 6.310 98.360 1.640 7.79 240 0.882 bicubic
125 gluon_resnet101_v1c 93.670 6.330 98.420 1.580 44.57 224 0.875 bicubic
126 tf_efficientnet_b0_ns 93.630 6.370 98.640 1.360 5.29 224 0.875 bicubic
127 gluon_resnet50_v1s 93.620 6.380 98.460 1.540 25.68 224 0.875 bicubic
128 regnetx_040 93.560 6.440 98.540 1.460 22.12 224 0.875 bicubic
129 hrnet_w44 93.550 6.450 98.700 1.300 67.06 224 0.875 bilinear
130 res2net50_26w_8s 93.540 6.460 98.260 1.740 48.40 224 0.875 bilinear
131 hrnet_w32 93.530 6.470 98.450 1.550 41.23 224 0.875 bilinear
132 dla102x 93.520 6.480 98.510 1.490 26.31 224 0.875 bilinear
133 tf_efficientnet_b1 93.500 6.500 98.360 1.640 7.79 240 0.882 bicubic
134 hrnet_w40 93.490 6.510 98.580 1.420 57.56 224 0.875 bilinear
135 tf_efficientnet_em 93.480 6.520 98.440 1.560 6.90 240 0.882 bicubic
136 gluon_inception_v3 93.460 6.540 98.570 1.430 23.83 299 0.875 bicubic
137 xception 93.460 6.540 98.530 1.470 22.86 299 0.897 bicubic
138 mixnet_l 93.450 6.550 98.220 1.780 7.33 224 0.875 bicubic
139 xception41 93.430 6.570 98.430 1.570 26.97 299 0.903 bicubic
140 res2net50_26w_6s 93.410 6.590 98.280 1.720 37.05 224 0.875 bilinear
141 regnety_032 93.390 6.610 98.640 1.360 19.44 224 0.875 bicubic
142 dla169 93.340 6.660 98.600 1.400 53.39 224 0.875 bilinear
143 resnest26d 93.330 6.670 98.630 1.370 17.07 224 0.875 bilinear
144 tf_inception_v3 93.320 6.680 98.030 1.970 23.83 299 0.875 bicubic
145 tf_mixnet_l 93.310 6.690 98.030 1.970 7.33 224 0.875 bicubic
146 resnet152 93.300 6.700 98.390 1.610 60.19 224 0.875 bilinear
147 selecsls60b 93.300 6.700 98.280 1.720 32.77 224 0.875 bicubic
148 efficientnet_b1 93.260 6.740 98.170 1.830 7.79 240 0.875 bicubic
149 hrnet_w30 93.200 6.800 98.410 1.590 37.71 224 0.875 bilinear
150 dla60_res2net 93.180 6.820 98.420 1.580 20.85 224 0.875 bilinear
151 dla60_res2next 93.180 6.820 98.410 1.590 17.03 224 0.875 bilinear
152 wide_resnet50_2 93.170 6.830 98.350 1.650 68.88 224 0.875 bilinear
153 efficientnet_es 93.140 6.860 98.420 1.580 5.44 224 0.875 bicubic
154 dla60x 93.120 6.880 98.510 1.490 17.35 224 0.875 bilinear
155 regnetx_032 93.120 6.880 98.390 1.610 15.30 224 0.875 bicubic
156 seresnext26t_32x4d 93.070 6.930 98.110 1.890 16.82 224 0.875 bicubic
157 dla102 93.060 6.940 98.540 1.460 33.27 224 0.875 bilinear
158 gluon_resnet50_v1c 93.030 6.970 98.390 1.610 25.58 224 0.875 bicubic
159 regnety_016 93.030 6.970 98.360 1.640 11.20 224 0.875 bicubic
160 rexnet_100 93.030 6.970 98.190 1.810 4.80 224 0.875 bicubic
161 selecsls60 93.030 6.970 98.300 1.700 30.67 224 0.875 bicubic
162 adv_inception_v3 92.880 7.120 98.140 1.860 23.83 299 0.875 bicubic
163 res2next50 92.840 7.160 98.180 1.820 24.67 224 0.875 bilinear
164 tf_efficientnet_cc_b0_8e 92.830 7.170 98.180 1.820 24.01 224 0.875 bicubic
165 seresnext26tn_32x4d 92.820 7.180 98.370 1.630 16.81 224 0.875 bicubic
166 resnet101 92.810 7.190 98.250 1.750 44.55 224 0.875 bilinear
167 efficientnet_b1_pruned 92.770 7.230 98.040 1.960 6.33 240 0.882 bicubic
168 densenet201 92.750 7.250 98.230 1.770 20.01 224 0.875 bicubic
169 res2net50_14w_8s 92.740 7.260 98.180 1.820 25.06 224 0.875 bilinear
170 tv_resnext50_32x4d 92.740 7.260 98.270 1.730 25.03 224 0.875 bilinear
171 inception_v3 92.720 7.280 97.970 2.030 23.83 299 0.875 bicubic
172 seresnext26d_32x4d 92.700 7.300 98.150 1.850 16.81 224 0.875 bicubic
173 efficientnet_b0 92.690 7.310 98.070 1.930 5.29 224 0.875 bicubic
174 tf_efficientnet_lite2 92.650 7.350 98.230 1.770 6.09 260 0.890 bicubic
175 tf_efficientnet_lite1 92.620 7.380 98.080 1.920 5.42 240 0.882 bicubic
176 tf_efficientnet_cc_b0_4e 92.590 7.410 98.080 1.920 13.31 224 0.875 bicubic
177 res2net50_48w_2s 92.550 7.450 98.080 1.920 25.29 224 0.875 bilinear
178 tf_efficientnet_es 92.550 7.450 98.280 1.720 5.44 224 0.875 bicubic
179 gluon_resnet50_v1b 92.540 7.460 98.170 1.830 25.56 224 0.875 bicubic
180 densenet161 92.500 7.500 98.290 1.710 28.68 224 0.875 bicubic
181 res2net50_26w_4s 92.500 7.500 98.060 1.940 25.70 224 0.875 bilinear
182 mixnet_m 92.430 7.570 97.870 2.130 5.01 224 0.875 bicubic
183 mobilenetv2_120d 92.400 7.600 98.050 1.950 5.83 224 0.875 bicubic
184 skresnet34 92.390 7.610 98.150 1.850 22.28 224 0.875 bicubic
185 tf_mixnet_m 92.330 7.670 97.890 2.110 5.01 224 0.875 bicubic
186 hrnet_w18 92.320 7.680 98.240 1.760 21.30 224 0.875 bilinear
187 ese_vovnet19b_dw 92.290 7.710 98.090 1.910 6.54 224 0.875 bicubic
188 selecsls42b 92.280 7.720 98.150 1.850 32.46 224 0.875 bicubic
189 tf_efficientnet_b0 92.250 7.750 98.000 2.000 5.29 224 0.875 bicubic
190 dla60 92.230 7.770 98.110 1.890 22.04 224 0.875 bilinear
191 tf_efficientnet_b0_ap 92.200 7.800 98.020 1.980 5.29 224 0.875 bicubic
192 regnetx_016 92.170 7.830 98.210 1.790 9.19 224 0.875 bicubic
193 resnet26d 92.070 7.930 97.960 2.040 16.01 224 0.875 bicubic
194 dpn68 92.010 7.990 98.050 1.950 12.61 224 0.875 bicubic
195 densenet169 91.930 8.070 98.100 1.900 14.15 224 0.875 bicubic
196 densenetblur121d 91.910 8.090 98.070 1.930 8.00 224 0.875 bicubic
197 tv_resnet50 91.880 8.120 98.040 1.960 25.56 224 0.875 bilinear
198 mobilenetv2_140 91.830 8.170 97.860 2.140 6.11 224 0.875 bicubic
199 mixnet_s 91.830 8.170 97.690 2.310 4.13 224 0.875 bicubic
200 regnety_008 91.750 8.250 98.180 1.820 6.26 224 0.875 bicubic
201 resnest14d 91.720 8.280 97.870 2.130 10.61 224 0.875 bilinear
202 densenet121 91.570 8.430 98.030 1.970 7.98 224 0.875 bicubic
203 tf_mixnet_s 91.510 8.490 97.620 2.380 4.13 224 0.875 bicubic
204 regnety_006 91.370 8.630 97.710 2.290 6.06 224 0.875 bicubic
205 mobilenetv3_large_100 91.320 8.680 97.710 2.290 5.48 224 0.875 bicubic
206 semnasnet_100 91.280 8.720 97.560 2.440 3.89 224 0.875 bicubic
207 tf_mobilenetv3_large_100 91.240 8.760 97.660 2.340 5.48 224 0.875 bilinear
208 mobilenetv3_rw 91.210 8.790 97.660 2.340 5.48 224 0.875 bicubic
209 hrnet_w18_small_v2 91.190 8.810 97.900 2.100 15.60 224 0.875 bilinear
210 efficientnet_lite0 91.140 8.860 97.630 2.370 4.65 224 0.875 bicubic
211 resnet34 91.130 8.870 97.620 2.380 21.80 224 0.875 bilinear
212 resnet26 91.110 8.890 97.740 2.260 16.00 224 0.875 bicubic
213 regnetx_008 91.050 8.950 97.710 2.290 7.26 224 0.875 bicubic
214 tf_efficientnet_lite0 91.040 8.960 97.590 2.410 4.65 224 0.875 bicubic
215 gluon_resnet34_v1b 90.960 9.040 97.630 2.370 21.80 224 0.875 bicubic
216 mobilenetv2_110d 90.950 9.050 97.550 2.450 4.52 224 0.875 bicubic
217 tv_densenet121 90.890 9.110 97.710 2.290 7.98 224 0.875 bicubic
218 dla34 90.760 9.240 97.660 2.340 15.74 224 0.875 bilinear
219 fbnetc_100 90.700 9.300 97.210 2.790 5.57 224 0.875 bilinear
220 swsl_resnet18 90.690 9.310 97.700 2.300 11.69 224 0.875 bilinear
221 mnasnet_100 90.510 9.490 97.470 2.530 4.38 224 0.875 bicubic
222 regnety_004 90.500 9.500 97.540 2.460 4.34 224 0.875 bicubic
223 regnetx_006 90.350 9.650 97.430 2.570 6.20 224 0.875 bicubic
224 spnasnet_100 90.350 9.650 97.190 2.810 4.42 224 0.875 bilinear
225 ssl_resnet18 90.220 9.780 97.550 2.450 11.69 224 0.875 bilinear
226 tv_resnet34 89.940 10.060 97.340 2.660 21.80 224 0.875 bilinear
227 tf_mobilenetv3_large_075 89.680 10.320 97.210 2.790 3.99 224 0.875 bilinear
228 skresnet18 89.660 10.340 97.230 2.770 11.96 224 0.875 bicubic
229 mobilenetv2_100 89.600 10.400 97.140 2.860 3.50 224 0.875 bicubic
230 hrnet_w18_small 89.050 10.950 97.110 2.890 13.19 224 0.875 bilinear
231 tf_mobilenetv3_large_minimal_100 88.970 11.030 96.860 3.140 3.92 224 0.875 bilinear
232 regnetx_004 88.900 11.100 97.120 2.880 5.16 224 0.875 bicubic
233 gluon_resnet18_v1b 88.400 11.600 96.680 3.320 11.69 224 0.875 bicubic
234 resnet18 87.390 12.610 96.290 3.710 11.69 224 0.875 bilinear
235 regnety_002 87.380 12.620 96.590 3.410 3.16 224 0.875 bicubic
236 dla60x_c 86.290 13.710 96.160 3.840 1.32 224 0.875 bilinear
237 regnetx_002 86.190 13.810 95.980 4.020 2.68 224 0.875 bicubic
238 tf_mobilenetv3_small_100 85.190 14.810 95.770 4.230 2.54 224 0.875 bilinear
239 dla46x_c 84.250 15.750 95.270 4.730 1.07 224 0.875 bilinear
240 dla46_c 83.650 16.350 94.920 5.080 1.30 224 0.875 bilinear
241 tf_mobilenetv3_small_075 83.520 16.480 94.790 5.210 2.04 224 0.875 bilinear
242 tf_mobilenetv3_small_minimal_100 81.380 18.620 93.670 6.330 2.04 224 0.875 bilinear

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model,rank_diff,top1,top1_diff,top1_err,top5,top5_diff,top5_err,param_count,img_size,cropt_pct,interpolation
tf_efficientnet_l2_ns_475,+1,62.387,-25.847,37.613,87.107,-11.439,12.893,480.31,475,0.936,bicubic
tf_efficientnet_l2_ns,-1,62.027,-26.325,37.973,87.960,-10.688,12.040,480.31,800,0.960,bicubic
tf_efficientnet_b7_ns,=,45.720,-41.118,54.280,74.200,-23.894,25.800,66.35,600,0.949,bicubic
ig_resnext101_32x48d,+2,41.573,-43.869,58.427,66.613,-30.959,33.387,828.41,224,0.875,bilinear
tf_efficientnet_b6_ns,-1,40.427,-46.035,59.573,68.840,-29.044,31.160,43.04,528,0.942,bicubic
ig_resnext101_32x32d,+5,39.413,-45.679,60.587,63.760,-33.676,36.240,468.53,224,0.875,bilinear
tf_efficientnet_b5_ns,-2,39.013,-47.067,60.987,68.040,-29.714,31.960,30.39,456,0.934,bicubic
ig_resnext101_32x16d,+9,36.053,-48.123,63.947,59.040,-38.156,40.960,194.03,224,0.875,bilinear
swsl_resnext101_32x8d,+5,32.067,-52.227,67.933,59.400,-37.774,40.600,88.79,224,0.875,bilinear
tf_efficientnet_b4_ns,-1,30.800,-54.358,69.200,59.440,-38.028,40.560,19.34,380,0.922,bicubic
tf_efficientnet_b8_ap,-3,29.600,-55.768,70.400,56.933,-40.361,43.067,87.41,672,0.954,bicubic
tf_efficientnet_b8,-5,29.373,-55.997,70.627,57.067,-40.325,42.933,87.41,672,0.954,bicubic
ig_resnext101_32x8d,+16,28.707,-53.981,71.293,52.320,-44.312,47.680,88.79,224,0.875,bilinear
swsl_resnext101_32x16d,+8,27.947,-55.391,72.053,52.320,-44.532,47.680,194.03,224,0.875,bilinear
tf_efficientnet_b7_ap,-5,27.813,-57.305,72.187,54.773,-42.479,45.227,66.35,600,0.949,bicubic
resnest269e,=,27.613,-56.573,72.387,53.107,-43.815,46.893,110.93,416,0.875,bilinear
tresnet_xl_448,+8,26.880,-56.168,73.120,51.093,-45.081,48.907,78.44,448,0.875,bilinear
resnest200e,+2,26.427,-57.407,73.573,51.933,-44.905,48.067,70.20,320,0.875,bilinear
swsl_resnext101_32x4d,+5,25.347,-57.887,74.653,49.627,-47.129,50.373,44.18,224,0.875,bilinear
tf_efficientnet_b7,-8,25.253,-59.679,74.747,51.667,-45.541,48.333,66.35,600,0.949,bicubic
tresnet_l_448,+11,24.573,-57.695,75.427,48.600,-47.378,51.400,55.99,448,0.875,bilinear
tf_efficientnet_b6_ap,-9,24.347,-60.439,75.653,50.427,-46.711,49.573,43.04,528,0.942,bicubic
tf_efficientnet_b6,-5,20.373,-63.739,79.627,45.493,-51.391,54.507,43.04,528,0.942,bicubic
tresnet_m_448,+15,19.680,-62.032,80.320,42.760,-52.810,57.240,31.39,448,0.875,bilinear
tf_efficientnet_b5_ap,-10,19.467,-64.787,80.533,44.720,-52.256,55.280,30.39,456,0.934,bicubic
tf_efficientnet_b3_ns,-7,19.413,-64.641,80.587,44.627,-52.285,55.373,12.23,300,0.904,bicubic
swsl_resnext50_32x4d,+6,18.067,-64.113,81.933,41.867,-54.361,58.133,25.03,224,0.875,bilinear
ssl_resnext101_32x16d,+9,17.213,-64.623,82.787,39.947,-56.147,60.053,194.03,224,0.875,bilinear
tf_efficientnet_b5,-8,17.067,-66.749,82.933,41.907,-54.843,58.093,30.39,456,0.934,bicubic
resnest101e,-3,16.493,-66.397,83.507,40.747,-55.577,59.253,48.28,256,0.875,bilinear
swsl_resnet50,+17,15.987,-65.193,84.013,38.853,-57.133,61.147,25.56,224,0.875,bilinear
ssl_resnext101_32x8d,+9,15.120,-66.506,84.880,37.720,-58.318,62.280,88.79,224,0.875,bilinear
tf_efficientnet_b4_ap,-10,13.680,-69.568,86.320,35.920,-60.468,64.080,19.34,380,0.922,bicubic
ecaresnet101d,=,13.307,-68.859,86.693,35.533,-60.519,64.467,44.57,224,0.875,bicubic
tf_efficientnet_b4,-9,13.307,-69.709,86.693,35.520,-60.778,64.480,19.34,380,0.922,bicubic
pnasnet5large,-8,13.080,-69.660,86.920,32.213,-63.827,67.787,86.06,331,0.875,bicubic
nasnetalarge,-7,12.573,-69.985,87.427,33.413,-62.623,66.587,88.75,331,0.875,bicubic
ssl_resnext101_32x4d,+15,12.120,-68.808,87.880,31.893,-63.835,68.107,44.18,224,0.875,bilinear
tf_efficientnet_b2_ns,-8,11.787,-70.593,88.213,32.960,-63.292,67.040,9.11,260,0.890,bicubic
gluon_senet154,+7,9.907,-71.317,90.093,26.453,-68.903,73.547,115.09,224,0.875,bicubic
resnest50d_4s2x40d,+8,9.787,-71.327,90.213,29.147,-66.421,70.853,30.42,224,0.875,bicubic
ssl_resnext50_32x4d,+30,9.667,-70.661,90.333,28.427,-66.977,71.573,25.03,224,0.875,bilinear
senet154,+3,9.453,-71.851,90.547,26.440,-69.058,73.560,115.09,224,0.875,bilinear
tresnet_xl,-9,9.307,-72.763,90.693,28.413,-67.515,71.587,78.44,224,0.875,bilinear
efficientnet_b3a,-9,9.267,-72.607,90.733,28.427,-67.413,71.573,12.23,320,1.000,bicubic
efficientnet_b3,-3,8.947,-72.551,91.053,28.213,-67.505,71.787,12.23,300,0.904,bicubic
inception_v4,+32,8.920,-71.236,91.080,24.707,-70.267,75.293,42.68,299,0.875,bicubic
gluon_seresnext101_64x4d,+7,8.867,-72.023,91.133,27.320,-67.984,72.680,88.23,224,0.875,bicubic
tf_efficientnet_b1_ns,-4,8.613,-72.773,91.387,27.280,-68.458,72.720,7.79,240,0.882,bicubic
resnest50d_1s4x24d,+1,8.520,-72.470,91.480,26.787,-68.535,73.213,25.68,224,0.875,bicubic
ecaresnet50d,+10,8.507,-72.097,91.493,26.267,-69.055,73.733,25.58,224,0.875,bicubic
gluon_xception65,+45,8.467,-71.137,91.533,25.133,-69.615,74.867,39.92,299,0.875,bicubic
gluon_resnet152_v1d,+11,8.413,-72.057,91.587,23.453,-71.753,76.547,60.21,224,0.875,bicubic
inception_resnet_v2,+11,8.160,-72.300,91.840,23.533,-71.777,76.467,55.84,299,0.897,bicubic
tf_efficientnet_b3_ap,-17,8.133,-73.695,91.867,26.280,-69.344,73.720,12.23,300,0.904,bicubic
gluon_seresnext101_32x4d,-2,8.040,-72.862,91.960,24.733,-70.561,75.267,48.96,224,0.875,bicubic
tf_efficientnet_b3,-17,8.013,-73.627,91.987,25.467,-70.255,74.533,12.23,300,0.904,bicubic
ens_adv_inception_resnet_v2,+25,7.987,-71.989,92.013,23.827,-71.119,76.173,55.84,299,0.897,bicubic
tf_efficientnet_lite4,-17,7.933,-73.595,92.067,25.560,-70.108,74.440,13.01,380,0.920,bilinear
tresnet_l,-16,7.880,-73.608,92.120,25.187,-70.441,74.813,55.99,224,0.875,bilinear
gluon_resnet152_v1s,-11,7.867,-73.145,92.133,23.173,-72.243,76.827,60.32,224,0.875,bicubic
resnest50d,-10,7.747,-73.211,92.253,25.293,-70.089,74.707,27.48,224,0.875,bilinear
gluon_resnext101_64x4d,-1,7.707,-72.895,92.293,23.240,-71.754,76.760,83.46,224,0.875,bicubic
skresnext50_32x4d,+16,7.080,-73.070,92.920,23.027,-71.617,76.973,27.48,224,0.875,bicubic
ssl_resnet50,+45,7.000,-72.228,93.000,23.920,-70.912,76.080,25.56,224,0.875,bilinear
regnety_320,-9,6.920,-73.894,93.080,23.040,-72.200,76.960,145.05,224,0.875,bicubic
ecaresnet101d_pruned,-9,6.800,-74.008,93.200,24.200,-71.428,75.800,24.88,224,0.875,bicubic
ecaresnetlight,-2,6.760,-73.694,93.240,22.560,-72.696,77.440,30.16,224,0.875,bicubic
efficientnet_b2a,-9,6.760,-73.848,93.240,23.493,-71.817,76.507,9.11,288,1.000,bicubic
seresnext101_32x4d,+7,6.413,-73.823,93.587,21.520,-73.508,78.480,48.96,224,0.875,bilinear
efficientnet_b2,-2,6.093,-74.309,93.907,21.933,-73.143,78.067,9.11,260,0.875,bicubic
gluon_resnext101_32x4d,-1,6.040,-74.294,93.960,21.133,-73.793,78.867,44.18,224,0.875,bicubic
regnetx_320,+3,5.987,-74.259,94.013,19.880,-75.142,80.120,107.81,224,0.875,bicubic
ese_vovnet39b,+29,5.973,-73.347,94.027,21.293,-73.417,78.707,24.57,224,0.875,bicubic
gluon_resnet101_v1d,-7,5.920,-74.504,94.080,19.947,-75.073,80.053,44.57,224,0.875,bicubic
gluon_seresnext50_32x4d,+10,5.787,-74.125,94.213,21.427,-73.391,78.573,27.56,224,0.875,bicubic
efficientnet_b3_pruned,-21,5.733,-75.123,94.267,21.360,-73.880,78.640,9.86,300,0.904,bicubic
regnety_160,-3,5.640,-74.660,94.360,19.347,-75.615,80.653,83.59,224,0.875,bicubic
gluon_inception_v3,+47,5.507,-73.297,94.493,19.947,-74.433,80.053,23.83,299,0.875,bicubic
mixnet_xl,-17,5.480,-74.998,94.520,21.093,-73.839,78.907,11.90,224,0.875,bicubic
tresnet_m,-22,5.440,-75.356,94.560,19.960,-74.896,80.040,31.39,224,0.875,bilinear
regnety_120,-12,5.413,-74.969,94.587,19.853,-75.275,80.147,51.82,224,0.875,bicubic
gluon_resnet101_v1s,-9,5.280,-75.020,94.720,19.547,-75.603,80.453,44.67,224,0.875,bicubic
hrnet_w64,+16,5.133,-74.339,94.867,19.453,-75.197,80.547,128.06,224,0.875,bilinear
regnety_080,+2,5.000,-74.868,95.000,18.600,-76.232,81.400,39.18,224,0.875,bicubic
efficientnet_b2_pruned,-2,4.947,-74.971,95.053,19.347,-75.501,80.653,8.31,260,0.890,bicubic
dpn107,-9,4.880,-75.284,95.120,17.613,-77.299,82.387,86.92,224,0.875,bicubic
gluon_resnet152_v1c,-3,4.867,-75.049,95.133,17.773,-77.069,82.227,60.21,224,0.875,bicubic
adv_inception_v3,+76,4.747,-72.833,95.253,17.547,-76.177,82.453,23.83,299,0.875,bicubic
dla102x2,+11,4.747,-74.705,95.253,18.960,-75.684,81.040,41.75,224,0.875,bilinear
tf_inception_v3,+68,4.747,-73.109,95.253,17.747,-75.897,82.253,23.83,299,0.875,bicubic
hrnet_w48,+13,4.720,-74.590,95.280,18.440,-76.078,81.560,77.47,224,0.875,bilinear
dpn131,-4,4.640,-75.188,95.360,16.867,-77.837,83.133,79.25,224,0.875,bicubic
gluon_resnet152_v1b,=,4.587,-75.105,95.413,16.533,-78.205,83.467,60.19,224,0.875,bicubic
ecaresnet50d_pruned,-3,4.547,-75.171,95.453,18.547,-76.343,81.453,19.94,224,0.875,bicubic
dpn92,-14,4.493,-75.523,95.507,18.200,-76.638,81.800,37.67,224,0.875,bicubic
hrnet_w44,+25,4.493,-74.401,95.507,17.347,-77.023,82.653,67.06,224,0.875,bilinear
regnetx_160,-10,4.373,-75.493,95.627,17.093,-77.735,82.907,54.28,224,0.875,bicubic
resnext50d_32x4d,-4,4.347,-75.327,95.653,17.773,-77.095,82.227,25.05,224,0.875,bicubic
xception,+18,4.347,-74.701,95.653,16.760,-77.632,83.240,22.86,299,0.897,bicubic
seresnext50_32x4d,+14,4.280,-74.796,95.720,17.813,-76.621,82.187,27.56,224,0.875,bilinear
resnext50_32x4d,-11,4.253,-75.509,95.747,18.387,-76.213,81.613,25.03,224,0.875,bicubic
tf_efficientnet_cc_b1_8e,+4,4.240,-75.058,95.760,15.947,-78.417,84.053,39.72,240,0.882,bicubic
regnety_064,-11,4.227,-75.485,95.773,17.187,-77.587,82.813,30.58,224,0.875,bicubic
tf_efficientnet_el,-38,4.227,-76.221,95.773,18.173,-76.987,81.827,10.59,300,0.904,bicubic
inception_v3,+64,4.187,-73.249,95.813,16.293,-77.183,83.707,23.83,299,0.875,bicubic
tf_efficientnet_b2_ap,-34,4.173,-76.133,95.827,18.320,-76.708,81.680,9.11,260,0.890,bicubic
seresnet152,+24,4.147,-74.511,95.853,15.893,-78.481,84.107,66.82,224,0.875,bilinear
resnext101_32x8d,-5,4.133,-75.179,95.867,16.987,-77.539,83.013,88.79,224,0.875,bilinear
tf_efficientnet_b0_ns,+23,4.133,-74.519,95.867,17.680,-76.688,82.320,5.29,224,0.875,bicubic
dpn98,-15,4.080,-75.556,95.920,15.947,-78.647,84.053,61.57,224,0.875,bicubic
res2net101_26w_4s,+2,4.000,-75.196,96.000,14.827,-79.613,85.173,45.21,224,0.875,bilinear
efficientnet_b1,+17,3.973,-74.725,96.027,15.760,-78.392,84.240,7.79,240,0.875,bicubic
tf_efficientnet_lite3,-24,3.933,-75.879,96.067,16.520,-78.394,83.480,8.20,300,0.904,bilinear
tf_efficientnet_b2,-34,3.773,-76.317,96.227,16.613,-78.293,83.387,9.11,260,0.890,bicubic
regnety_040,-5,3.747,-75.475,96.253,16.400,-78.256,83.600,20.65,224,0.875,bicubic
hrnet_w30,+31,3.680,-74.516,96.320,15.573,-78.647,84.427,37.71,224,0.875,bilinear
hrnet_w32,+23,3.653,-74.795,96.347,14.787,-79.401,85.213,41.23,224,0.875,bilinear
hrnet_w40,+2,3.653,-75.281,96.347,15.440,-79.026,84.560,57.56,224,0.875,bilinear
regnetx_120,-22,3.627,-75.963,96.373,15.973,-78.767,84.027,46.11,224,0.875,bicubic
seresnext26t_32x4d,+34,3.613,-74.375,96.387,15.893,-77.813,84.107,16.82,224,0.875,bicubic
tf_efficientnet_b1_ap,-13,3.547,-75.731,96.453,15.067,-79.241,84.933,7.79,240,0.882,bicubic
seresnext26tn_32x4d,+31,3.507,-74.483,96.493,15.760,-77.988,84.240,16.81,224,0.875,bicubic
resnest26d,+13,3.493,-74.989,96.507,15.667,-78.623,84.333,17.07,224,0.875,bilinear
dla169,+4,3.467,-75.243,96.533,15.333,-79.005,84.667,53.99,224,0.875,bilinear
gluon_resnext50_32x4d,-24,3.453,-75.903,96.547,16.120,-78.304,83.880,25.03,224,0.875,bicubic
mixnet_l,-7,3.440,-75.536,96.560,15.307,-78.877,84.693,7.33,224,0.875,bicubic
seresnext26d_32x4d,+36,3.400,-74.204,96.600,16.160,-77.452,83.840,16.81,224,0.875,bicubic
res2net50_26w_8s,-17,3.333,-75.877,96.667,14.040,-80.322,85.960,48.40,224,0.875,bilinear
resnetblur50,-22,3.333,-75.957,96.667,15.587,-79.045,84.413,25.56,224,0.875,bicubic
dla102x,+4,3.307,-75.201,96.693,15.120,-79.114,84.880,26.77,224,0.875,bilinear
gluon_resnet101_v1c,-33,3.307,-76.237,96.693,14.120,-80.466,85.880,44.57,224,0.875,bicubic
seresnet101,+10,3.253,-75.143,96.747,15.453,-78.805,84.547,49.33,224,0.875,bilinear
densenetblur121d,+55,3.067,-73.509,96.933,14.280,-78.910,85.720,8.00,224,0.875,bicubic
dla60_res2next,+5,3.040,-75.408,96.960,14.453,-79.691,85.547,17.33,224,0.875,bilinear
regnety_032,-13,3.027,-75.843,96.973,14.240,-80.162,85.760,19.44,224,0.875,bicubic
gluon_resnet50_v1d,-21,3.013,-76.061,96.987,14.627,-79.849,85.373,25.58,224,0.875,bicubic
wide_resnet101_2,-14,2.960,-75.886,97.040,13.947,-80.337,86.053,126.89,224,0.875,bilinear
efficientnet_b1_pruned,+7,2.933,-75.309,97.067,14.413,-79.419,85.587,6.33,240,0.882,bicubic
gluon_resnet50_v1s,-12,2.920,-75.792,97.080,13.120,-81.122,86.880,25.68,224,0.875,bicubic
tf_efficientnet_b1,-16,2.867,-75.965,97.133,13.507,-80.689,86.493,7.79,240,0.882,bicubic
res2net50_26w_6s,-8,2.840,-75.734,97.160,12.600,-81.526,87.400,37.05,224,0.875,bilinear
efficientnet_b0,+18,2.813,-74.879,97.187,13.907,-79.625,86.093,5.29,224,0.875,bicubic
tf_mixnet_l,-17,2.813,-75.957,97.187,13.040,-80.964,86.960,7.33,224,0.875,bicubic
regnetx_064,-28,2.787,-76.279,97.213,13.880,-80.576,86.120,26.21,224,0.875,bicubic
dpn68b,+21,2.707,-74.807,97.293,12.640,-81.182,87.360,12.61,224,0.875,bicubic
selecsls60b,-5,2.693,-75.725,97.307,13.173,-80.993,86.827,32.77,224,0.875,bicubic
tf_efficientnet_cc_b0_8e,+10,2.680,-75.228,97.320,12.773,-80.883,87.227,24.01,224,0.875,bicubic
dla60_res2net,-11,2.640,-75.832,97.360,14.200,-80.004,85.800,21.15,224,0.875,bilinear
gluon_resnet101_v1b,-44,2.627,-76.677,97.373,13.573,-80.951,86.427,44.55,224,0.875,bicubic
dla60x,-6,2.613,-75.629,97.387,13.333,-80.689,86.667,17.65,224,0.875,bilinear
mixnet_m,+25,2.547,-74.709,97.453,12.427,-80.991,87.573,5.01,224,0.875,bicubic
skresnet34,+31,2.520,-74.390,97.480,12.773,-80.543,87.227,22.28,224,0.875,bicubic
efficientnet_es,-3,2.373,-75.681,97.627,13.880,-80.050,86.120,5.44,224,0.875,bicubic
resnet152,-11,2.360,-75.952,97.640,12.200,-81.846,87.800,60.19,224,0.875,bilinear
regnetx_080,-43,2.347,-76.851,97.653,12.693,-81.865,87.307,39.57,224,0.875,bicubic
swsl_resnet18,+64,2.333,-70.953,97.667,11.213,-80.519,88.787,11.69,224,0.875,bilinear
wide_resnet50_2,-19,2.320,-76.148,97.680,11.800,-82.286,88.200,68.88,224,0.875,bilinear
seresnext26_32x4d,+20,2.293,-74.807,97.707,12.440,-80.870,87.560,16.79,224,0.875,bicubic
hrnet_w18,+26,2.267,-74.489,97.733,11.853,-81.589,88.147,21.30,224,0.875,bilinear
dla102,-9,2.253,-75.773,97.747,12.120,-81.830,87.880,33.73,224,0.875,bilinear
resnet50,-43,2.227,-76.805,97.773,11.333,-83.051,88.667,25.56,224,0.875,bicubic
regnety_016,-3,2.173,-75.679,97.827,11.440,-82.276,88.560,11.20,224,0.875,bicubic
regnetx_040,-28,2.160,-76.326,97.840,11.800,-82.442,88.200,22.12,224,0.875,bicubic
resnest14d,+36,2.147,-73.357,97.853,10.400,-82.114,89.600,10.61,224,0.875,bilinear
selecsls60,-10,2.080,-75.902,97.920,12.840,-80.992,87.160,30.67,224,0.875,bicubic
tf_efficientnet_cc_b0_4e,+6,2.080,-75.224,97.920,10.973,-82.359,89.027,13.31,224,0.875,bicubic
res2next50,-21,2.067,-76.175,97.933,11.453,-82.439,88.547,24.67,224,0.875,bilinear
seresnet50,-7,2.067,-75.569,97.933,12.267,-81.485,87.733,28.09,224,0.875,bilinear
densenet161,+2,1.973,-75.375,98.027,10.587,-83.061,89.413,28.68,224,0.875,bicubic
tf_efficientnet_b0_ap,+9,1.960,-75.124,98.040,10.800,-82.454,89.200,5.29,224,0.875,bicubic
regnetx_032,-23,1.920,-76.246,98.080,10.947,-83.133,89.053,15.30,224,0.875,bicubic
tf_efficientnet_em,-42,1.813,-76.885,98.187,11.627,-82.693,88.373,6.90,240,0.882,bicubic
tf_mixnet_m,+8,1.813,-75.137,98.187,10.547,-82.609,89.453,5.01,224,0.875,bicubic
tf_efficientnet_lite2,-6,1.800,-75.660,98.200,11.147,-82.599,88.853,6.09,260,0.890,bicubic
res2net50_14w_8s,-26,1.787,-76.365,98.213,10.347,-83.495,89.653,25.06,224,0.875,bilinear
res2net50_26w_4s,-20,1.773,-76.173,98.227,10.440,-83.412,89.560,25.70,224,0.875,bilinear
mobilenetv3_large_100,+18,1.760,-74.008,98.240,10.293,-82.247,89.707,5.48,224,0.875,bicubic
densenet121,+20,1.733,-73.841,98.267,10.853,-81.803,89.147,7.98,224,0.875,bicubic
tf_efficientnet_b0,+5,1.693,-75.147,98.307,9.733,-83.493,90.267,5.29,224,0.875,bicubic
tv_resnext50_32x4d,-18,1.680,-75.938,98.320,10.600,-83.098,89.400,25.03,224,0.875,bilinear
mobilenetv3_rw,+16,1.667,-73.961,98.333,10.733,-81.977,89.267,5.48,224,0.875,bicubic
resnet101,-12,1.667,-75.707,98.333,9.813,-83.733,90.187,44.55,224,0.875,bilinear
mobilenetv2_120d,-10,1.640,-75.654,98.360,10.453,-83.049,89.547,5.83,224,0.875,bicubic
mixnet_s,+9,1.587,-74.401,98.413,10.253,-82.541,89.747,4.13,224,0.875,bicubic
densenet201,-11,1.547,-75.743,98.453,9.627,-83.851,90.373,20.01,224,0.875,bicubic
gluon_resnet50_v1c,-34,1.547,-76.463,98.453,10.613,-83.375,89.387,25.58,224,0.875,bicubic
semnasnet_100,+14,1.547,-73.909,98.453,9.320,-83.272,90.680,3.89,224,0.875,bicubic
selecsls42b,-11,1.467,-75.709,98.533,10.440,-82.952,89.560,32.46,224,0.875,bicubic
tf_efficientnet_lite1,-2,1.453,-75.185,98.547,9.707,-83.525,90.293,5.42,240,0.882,bicubic
regnety_008,=,1.427,-74.887,98.573,8.947,-84.115,91.053,6.26,224,0.875,bicubic
ssl_resnet18,+32,1.387,-71.213,98.613,8.160,-83.256,91.840,11.69,224,0.875,bilinear
dla60,-12,1.347,-75.677,98.653,9.467,-83.841,90.533,22.33,224,0.875,bilinear
dpn68,-2,1.347,-74.959,98.653,8.813,-84.157,91.187,12.61,224,0.875,bicubic
res2net50_48w_2s,-27,1.307,-76.207,98.693,8.920,-84.628,91.080,25.29,224,0.875,bilinear
tf_mixnet_s,+1,1.280,-74.368,98.720,8.747,-83.889,91.253,4.13,224,0.875,bicubic
mobilenetv2_140,-7,1.253,-75.271,98.747,9.107,-83.883,90.893,6.11,224,0.875,bicubic
fbnetc_100,+8,1.227,-73.893,98.773,8.747,-83.639,91.253,5.57,224,0.875,bilinear
resnet26d,-12,1.227,-75.453,98.773,9.280,-83.886,90.720,16.01,224,0.875,bicubic
densenet169,-5,1.187,-74.725,98.813,8.320,-84.704,91.680,14.15,224,0.875,bicubic
tf_mobilenetv3_large_100,-1,1.187,-74.329,98.813,7.947,-84.653,92.053,5.48,224,0.875,bilinear
gluon_resnet50_v1b,-36,1.160,-76.418,98.840,9.027,-84.691,90.973,25.56,224,0.875,bicubic
seresnet34,+8,1.120,-73.688,98.880,7.400,-84.726,92.600,21.96,224,0.875,bilinear
tf_efficientnet_es,-28,1.120,-76.144,98.880,8.600,-85.000,91.400,5.44,224,0.875,bicubic
spnasnet_100,+11,1.107,-72.973,98.893,8.253,-83.579,91.747,4.42,224,0.875,bilinear
tf_efficientnet_lite0,+4,1.107,-73.735,98.893,7.493,-84.677,92.507,4.65,224,0.875,bicubic
regnetx_016,-24,1.093,-75.837,98.907,8.627,-84.791,91.373,9.19,224,0.875,bicubic
dla34,+6,1.080,-73.556,98.920,7.693,-84.371,92.307,15.78,224,0.875,bilinear
regnety_006,-5,1.053,-74.207,98.947,8.400,-84.128,91.600,6.06,224,0.875,bicubic
regnety_004,+7,1.013,-73.013,98.987,7.333,-84.415,92.667,4.34,224,0.875,bicubic
resnet34,-4,0.987,-74.125,99.013,7.533,-84.755,92.467,21.80,224,0.875,bilinear
mobilenetv2_110d,-4,0.933,-74.119,99.067,8.107,-84.073,91.893,4.52,224,0.875,bicubic
gluon_resnet34_v1b,+2,0.893,-73.687,99.107,6.600,-85.388,93.400,21.80,224,0.875,bicubic
hrnet_w18_small_v2,-9,0.893,-74.233,99.107,7.387,-85.029,92.613,15.60,224,0.875,bilinear
regnetx_008,-6,0.893,-74.129,99.107,6.907,-85.437,93.093,7.26,224,0.875,bicubic
skresnet18,+6,0.880,-72.164,99.120,7.387,-83.791,92.613,11.96,224,0.875,bicubic
mnasnet_100,-4,0.867,-73.789,99.133,7.867,-84.259,92.133,4.38,224,0.875,bicubic
tf_mobilenetv3_large_075,+1,0.867,-72.575,99.133,6.720,-84.632,93.280,3.99,224,0.875,bilinear
regnetx_006,-1,0.760,-73.102,99.240,6.493,-85.187,93.507,6.20,224,0.875,bicubic
tf_mobilenetv3_small_100,+13,0.747,-67.171,99.253,4.667,-82.995,95.333,2.54,224,0.875,bilinear
seresnet18,+7,0.720,-71.038,99.280,6.027,-84.307,93.973,11.78,224,0.875,bicubic
regnetx_004,+3,0.693,-71.713,99.307,5.507,-85.323,94.493,5.16,224,0.875,bicubic
tv_densenet121,-11,0.680,-74.072,99.320,6.907,-85.245,93.093,7.98,224,0.875,bicubic
regnety_002,+6,0.667,-69.615,99.333,5.533,-84.007,94.467,3.16,224,0.875,bicubic
tf_mobilenetv3_small_075,+11,0.627,-65.091,99.373,4.173,-81.963,95.827,2.04,224,0.875,bilinear
resnet26,-23,0.600,-74.692,99.400,6.880,-85.690,93.120,16.00,224,0.875,bicubic
tv_resnet34,-7,0.600,-72.714,99.400,5.520,-85.900,94.480,21.80,224,0.875,bilinear
mobilenetv2_100,-5,0.533,-72.445,99.467,6.187,-84.829,93.813,3.50,224,0.875,bicubic
dla46_c,+8,0.520,-64.358,99.480,4.187,-82.099,95.813,1.31,224,0.875,bilinear
tf_mobilenetv3_large_minimal_100,-3,0.480,-71.764,99.520,4.880,-85.756,95.120,3.92,224,0.875,bilinear
dla60x_c,+3,0.467,-67.441,99.533,5.213,-83.221,94.787,1.34,224,0.875,bilinear
hrnet_w18_small,-6,0.453,-71.889,99.547,4.840,-85.832,95.160,13.19,224,0.875,bilinear
dla46x_c,+2,0.413,-65.567,99.587,4.440,-82.540,95.560,1.08,224,0.875,bilinear
gluon_resnet18_v1b,-5,0.387,-70.443,99.613,4.787,-84.969,95.213,11.69,224,0.875,bicubic
tf_mobilenetv3_small_minimal_100,+3,0.360,-62.538,99.640,2.867,-81.363,97.133,2.04,224,0.875,bilinear
resnet18,-5,0.293,-69.465,99.707,4.040,-85.038,95.960,11.69,224,0.875,bilinear
regnetx_002,-5,0.227,-68.527,99.773,3.987,-84.561,96.013,2.68,224,0.875,bicubic
tv_resnet50,-45,0.000,-76.130,100.000,2.893,-89.969,97.107,25.56,224,0.875,bilinear
model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff
tf_efficientnet_l2_ns,84.760,15.240,96.147,3.853,480.31,800,0.960,bicubic,-13.790,-3.673,0
tf_efficientnet_l2_ns_475,83.373,16.627,95.453,4.547,480.31,475,0.936,bicubic,-15.127,-4.377,0
tf_efficientnet_b7_ns,67.040,32.960,88.667,11.333,66.35,600,0.949,bicubic,-30.870,-11.053,0
tf_efficientnet_b6_ns,62.267,37.733,85.173,14.827,43.04,528,0.942,bicubic,-35.363,-14.407,0
ig_resnext101_32x48d,61.013,38.987,83.347,16.653,828.41,224,0.875,bilinear,-36.607,-16.353,0
tf_efficientnet_b5_ns,60.320,39.680,84.493,15.507,30.39,456,0.934,bicubic,-37.180,-15.137,0
ig_resnext101_32x32d,58.093,41.907,80.653,19.347,468.53,224,0.875,bilinear,-39.267,-19.027,0
ig_resnext101_32x16d,53.067,46.933,76.907,23.093,194.03,224,0.875,bilinear,-43.753,-22.683,+7
tf_efficientnet_b4_ns,51.213,48.787,79.187,20.813,19.34,380,0.922,bicubic,-45.737,-20.393,+5
swsl_resnext101_32x8d,51.187,48.813,78.240,21.760,88.79,224,0.875,bilinear,-46.013,-21.330,-2
tf_efficientnet_b8,48.947,51.053,77.240,22.760,87.41,672,0.954,bicubic,-48.253,-22.260,-1
resnest269e,48.187,51.813,74.333,25.667,110.93,416,0.928,bicubic,-48.333,-25.017,+8
tf_efficientnet_b8_ap,46.893,53.107,76.507,23.493,87.41,672,0.954,bicubic,-50.217,-23.153,-2
swsl_resnext101_32x16d,46.200,53.800,72.200,27.800,194.03,224,0.875,bilinear,-50.400,-27.320,+5
tf_efficientnet_b7_ap,45.373,54.627,74.213,25.787,66.35,600,0.949,bicubic,-51.827,-25.327,-6
ig_resnext101_32x8d,45.320,54.680,70.867,29.133,88.79,224,0.875,bilinear,-51.000,-28.563,+8
resnest200e,44.147,55.853,73.467,26.533,70.20,320,0.909,bicubic,-52.463,-25.883,+1
tresnet_xl_448,43.480,56.520,72.453,27.547,78.44,448,0.875,bilinear,-52.490,-26.677,+8
tf_efficientnet_b7,42.960,57.040,73.133,26.867,66.35,600,0.949,bicubic,-54.050,-26.387,-6
swsl_resnext101_32x4d,41.560,58.440,71.760,28.240,44.18,224,0.875,bilinear,-54.860,-27.710,+1
tf_efficientnet_b6_ap,40.800,59.200,71.627,28.373,43.04,528,0.942,bicubic,-56.280,-27.993,-9
tresnet_l_448,40.200,59.800,69.893,30.107,55.99,448,0.875,bilinear,-55.660,-29.227,+8
tf_efficientnet_b3_ns,35.520,64.480,67.773,32.227,12.23,300,0.904,bicubic,-60.870,-31.577,-1
tf_efficientnet_b6,35.213,64.787,67.720,32.280,43.04,528,0.942,bicubic,-61.457,-31.650,-7
tf_efficientnet_b5_ap,34.787,65.213,67.493,32.507,30.39,456,0.934,bicubic,-61.893,-31.967,-9
tresnet_m_448,34.107,65.893,64.493,35.507,31.39,448,0.875,bilinear,-60.883,-34.487,+22
swsl_resnext50_32x4d,33.013,66.987,65.067,34.933,25.03,224,0.875,bilinear,-62.857,-34.183,+1
ssl_resnext101_32x16d,32.600,67.400,64.000,36.000,194.03,224,0.875,bilinear,-63.200,-35.180,+3
tf_efficientnet_b5,31.840,68.160,65.293,34.707,30.39,456,0.934,bicubic,-64.510,-34.017,-6
resnest101e,31.413,68.587,64.360,35.640,48.28,256,0.875,bilinear,-64.447,-34.850,-1
swsl_resnet50,29.867,70.133,63.853,36.147,25.56,224,0.875,bilinear,-65.543,-35.437,+8
ssl_resnext101_32x8d,29.040,70.960,60.973,39.027,88.79,224,0.875,bilinear,-66.430,-38.137,+4
tf_efficientnet_b4,26.293,73.707,60.107,39.893,19.34,380,0.922,bicubic,-69.607,-39.063,-6
tf_efficientnet_b4_ap,26.240,73.760,60.227,39.773,19.34,380,0.922,bicubic,-69.920,-39.053,-9
ecaresnet101d,26.027,73.973,58.987,41.013,44.57,224,0.875,bicubic,-69.503,-40.143,0
ssl_resnext101_32x4d,24.173,75.827,57.413,42.587,44.18,224,0.875,bilinear,-71.267,-41.717,+1
tf_efficientnet_b2_ns,24.013,75.987,57.293,42.707,9.11,260,0.890,bicubic,-71.757,-41.827,-5
nasnetalarge,23.493,76.507,55.027,44.973,88.75,331,0.911,bicubic,-72.187,-43.903,-4
pnasnet5large,23.333,76.667,53.640,46.360,86.06,331,0.911,bicubic,-72.377,-45.280,-6
resnest50d_4s2x40d,20.387,79.613,52.800,47.200,30.42,224,0.875,bicubic,-74.573,-46.270,+9
ssl_resnext50_32x4d,20.000,80.000,53.613,46.387,25.03,224,0.875,bilinear,-74.870,-45.267,+14
tresnet_xl,19.640,80.360,53.133,46.867,78.44,224,0.875,bilinear,-75.800,-45.917,-4
gluon_senet154,19.307,80.693,47.533,52.467,115.09,224,0.875,bicubic,-75.613,-51.227,+9
rexnet_200,19.227,80.773,52.720,47.280,16.37,224,0.875,bicubic,-75.713,-46.290,+6
gluon_seresnext101_64x4d,18.907,81.093,49.187,50.813,88.23,224,0.875,bicubic,-76.023,-49.643,+6
tf_efficientnet_b1_ns,18.693,81.307,51.667,48.333,7.79,240,0.882,bicubic,-76.477,-47.443,-4
efficientnet_b3,18.693,81.307,52.347,47.653,12.23,300,0.904,bicubic,-76.387,-46.633,-1
efficientnet_b3a,18.600,81.400,51.640,48.360,12.23,320,1.000,bicubic,-76.660,-47.290,-6
ecaresnet50d,18.227,81.773,51.893,48.107,25.58,224,0.875,bicubic,-76.403,-46.997,+15
tf_efficientnet_lite4,18.133,81.867,50.707,49.293,13.01,380,0.920,bilinear,-76.757,-48.313,+4
resnest50d_1s4x24d,17.693,82.307,49.800,50.200,25.68,224,0.875,bicubic,-77.057,-49.180,+7
gluon_seresnext101_32x4d,17.373,82.627,46.373,53.627,48.96,224,0.875,bicubic,-77.547,-52.437,+1
resnest50d,17.373,82.627,50.707,49.293,27.48,224,0.875,bilinear,-77.457,-48.173,+3
inception_v4,17.267,82.733,45.920,54.080,42.68,299,0.875,bicubic,-77.113,-52.660,+25
tf_efficientnet_b3_ap,17.187,82.813,49.680,50.320,12.23,300,0.904,bicubic,-78.133,-49.220,-15
tf_efficientnet_b3,17.000,83.000,49.267,50.733,12.23,300,0.904,bicubic,-78.010,-49.643,-9
xception71,17.000,83.000,45.520,54.480,42.34,299,0.903,bicubic,-77.280,-53.120,+27
gluon_resnext101_64x4d,16.853,83.147,44.213,55.787,83.46,224,0.875,bicubic,-77.817,-54.437,+4
tresnet_l,16.600,83.400,49.920,50.080,55.99,224,0.875,bilinear,-78.690,-49.090,-18
inception_resnet_v2,16.573,83.427,44.960,55.040,55.84,299,0.897,bicubic,-77.967,-53.830,+8
gluon_resnet152_v1s,16.573,83.427,44.533,55.467,60.32,224,0.875,bicubic,-78.467,-54.397,-15
gluon_resnet152_v1d,16.573,83.427,44.280,55.720,60.21,224,0.875,bicubic,-78.167,-54.460,-1
gluon_xception65,16.440,83.560,46.027,53.973,39.92,299,0.903,bicubic,-77.820,-52.543,+22
ens_adv_inception_resnet_v2,16.240,83.760,43.640,56.360,55.84,299,0.897,bicubic,-77.920,-54.960,+31
xception65,16.027,83.973,43.773,56.227,39.92,299,0.903,bicubic,-77.733,-54.597,+53
ssl_resnet50,15.960,84.040,49.467,50.533,25.56,224,0.875,bilinear,-78.490,-49.453,+12
regnety_320,15.627,84.373,44.827,55.173,145.05,224,0.875,bicubic,-78.913,-54.023,+4
ecaresnet101d_pruned,15.600,84.400,48.027,51.973,24.88,224,0.875,bicubic,-79.480,-50.953,-24
skresnext50_32x4d,15.373,84.627,44.493,55.507,27.48,224,0.875,bicubic,-78.887,-53.967,+17
ecaresnetlight,15.160,84.840,45.827,54.173,30.16,224,0.875,bicubic,-79.610,-52.973,-13
rexnet_150,14.720,85.280,46.907,53.093,9.73,224,0.875,bicubic,-79.760,-51.903,+4
efficientnet_b2a,14.440,85.560,46.080,53.920,9.11,288,1.000,bicubic,-80.170,-52.630,-5
seresnet50,14.147,85.853,45.467,54.533,28.09,224,0.875,bicubic,-80.403,-53.283,-4
gluon_resnext101_32x4d,13.867,86.133,41.653,58.347,44.18,224,0.875,bicubic,-80.663,-56.977,-2
gluon_seresnext50_32x4d,13.600,86.400,43.760,56.240,27.56,224,0.875,bicubic,-80.740,-54.850,+6
ese_vovnet39b,13.320,86.680,43.813,56.187,24.57,224,0.875,bicubic,-80.770,-54.847,+26
efficientnet_b2,13.307,86.693,44.440,55.560,9.11,260,0.875,bicubic,-81.393,-54.230,-16
regnetx_320,13.307,86.693,40.720,59.280,107.81,224,0.875,bicubic,-81.153,-58.020,-1
efficientnet_b3_pruned,13.173,86.827,45.213,54.787,9.86,300,0.904,bicubic,-81.457,-53.547,-14
gluon_resnet101_v1d,13.160,86.840,41.493,58.507,44.57,224,0.875,bicubic,-81.060,-57.057,+10
mixnet_xl,13.120,86.880,43.253,56.747,11.90,224,0.875,bicubic,-81.070,-55.087,+11
gluon_inception_v3,12.640,87.360,40.493,59.507,23.83,299,0.875,bicubic,-80.820,-58.077,+53
tresnet_m,12.600,87.400,41.893,58.107,31.39,224,0.875,bilinear,-82.020,-56.657,-17
regnety_120,12.427,87.573,42.200,57.800,51.82,224,0.875,bicubic,-82.053,-56.480,-10
regnety_160,12.200,87.800,41.320,58.680,83.59,224,0.875,bicubic,-82.140,-57.530,-3
hrnet_w64,12.027,87.973,40.787,59.213,128.06,224,0.875,bilinear,-81.983,-57.823,+19
cspdarknet53,12.013,87.987,43.253,56.747,27.64,256,0.887,bilinear,-82.647,-55.547,-24
gluon_resnet101_v1s,11.880,88.120,40.973,59.027,44.67,224,0.875,bicubic,-82.840,-57.847,-28
dpn92,11.627,88.373,40.267,59.733,37.67,224,0.875,bicubic,-82.603,-58.463,-1
xception41,11.600,88.400,39.133,60.867,26.97,299,0.903,bicubic,-81.830,-59.297,+48
dla102x2,11.573,88.427,41.293,58.707,41.28,224,0.875,bilinear,-82.377,-57.197,+16
regnety_080,11.413,88.587,40.613,59.387,39.18,224,0.875,bicubic,-82.757,-58.067,+2
efficientnet_b2_pruned,11.360,88.640,42.027,57.973,8.31,260,0.890,bicubic,-82.780,-56.503,+5
gluon_resnet152_v1c,11.093,88.907,37.120,62.880,60.21,224,0.875,bicubic,-83.067,-61.520,+2
dpn107,11.080,88.920,38.693,61.307,86.92,224,0.875,bicubic,-83.230,-59.787,-12
hrnet_w48,11.080,88.920,40.320,59.680,77.47,224,0.875,bilinear,-82.840,-58.290,+12
ecaresnet50d_pruned,11.027,88.973,41.947,58.053,19.94,224,0.875,bicubic,-83.193,-56.783,-8
adv_inception_v3,11.013,88.987,36.720,63.280,23.83,299,0.875,bicubic,-81.867,-61.420,+63
tf_efficientnet_el,10.960,89.040,41.773,58.227,10.59,300,0.904,bicubic,-83.630,-56.977,-31
tf_efficientnet_b0_ns,10.933,89.067,40.067,59.933,5.29,224,0.875,bicubic,-82.697,-58.573,+25
tf_inception_v3,10.840,89.160,36.853,63.147,23.83,299,0.875,bicubic,-82.480,-61.177,+42
resnext50_32x4d,10.800,89.200,40.307,59.693,25.03,224,0.875,bicubic,-83.300,-58.043,-1
dpn131,10.787,89.213,37.200,62.800,79.25,224,0.875,bicubic,-83.223,-61.520,+1
tf_efficientnet_b2_ap,10.533,89.467,40.107,59.893,9.11,260,0.890,bicubic,-83.957,-58.513,-31
resnext50d_32x4d,10.413,89.587,39.733,60.267,25.05,224,0.875,bicubic,-83.767,-58.837,-12
rexnet_130,10.400,89.600,41.547,58.453,7.56,224,0.875,bicubic,-83.500,-56.853,+3
hrnet_w44,10.320,89.680,39.507,60.493,67.06,224,0.875,bilinear,-83.230,-59.193,+21
resnext101_32x8d,10.187,89.813,37.827,62.173,88.79,224,0.875,bilinear,-83.643,-60.753,+6
regnetx_160,10.147,89.853,38.000,62.000,54.28,224,0.875,bicubic,-83.973,-60.750,-9
dpn98,10.133,89.867,36.587,63.413,61.57,224,0.875,bicubic,-83.997,-61.983,-11
cspresnext50,10.120,89.880,40.373,59.627,20.57,224,0.875,bilinear,-84.360,-58.417,-35
inception_v3,10.027,89.973,35.213,64.787,23.83,299,0.875,bicubic,-82.693,-62.757,+58
xception,9.987,90.013,38.027,61.973,22.86,299,0.897,bicubic,-83.473,-60.503,+23
regnety_064,9.947,90.053,39.067,60.933,30.58,224,0.875,bicubic,-84.203,-59.663,-17
dpn68b,9.787,90.213,38.053,61.947,12.61,224,0.875,bicubic,-83.903,-60.457,+7
gluon_resnet152_v1b,9.747,90.253,36.067,63.933,60.19,224,0.875,bicubic,-84.333,-62.383,-13
tf_efficientnet_lite3,9.667,90.333,39.000,61.000,8.20,300,0.904,bilinear,-84.533,-59.640,-26
tf_efficientnet_b2,9.653,90.347,38.880,61.120,9.11,260,0.890,bicubic,-84.707,-59.730,-38
tf_efficientnet_cc_b1_8e,9.573,90.427,36.773,63.227,39.72,240,0.882,bicubic,-84.327,-61.487,-9
res2net101_26w_4s,9.520,90.480,35.027,64.973,45.21,224,0.875,bilinear,-84.230,-63.283,0
seresnext26t_32x4d,9.347,90.653,37.520,62.480,16.82,224,0.875,bicubic,-83.723,-60.590,+34
hrnet_w40,9.227,90.773,36.893,63.107,57.56,224,0.875,bilinear,-84.263,-61.687,+11
regnetx_120,9.187,90.813,37.200,62.800,46.11,224,0.875,bicubic,-85.053,-61.450,-36
seresnext26d_32x4d,9.147,90.853,36.840,63.160,16.81,224,0.875,bicubic,-83.553,-61.310,+47
efficientnet_b1,9.120,90.880,37.360,62.640,7.79,240,0.875,bicubic,-84.140,-60.810,+22
resnest26d,9.080,90.920,37.853,62.147,17.07,224,0.875,bilinear,-84.250,-60.777,+16
regnety_040,9.000,91.000,37.053,62.947,20.65,224,0.875,bicubic,-84.860,-61.597,-14
gluon_resnext50_32x4d,8.947,91.053,36.333,63.667,25.03,224,0.875,bicubic,-84.863,-62.077,-13
rexnet_100,8.893,91.107,36.373,63.627,4.80,224,0.875,bicubic,-84.137,-61.817,+30
seresnext26tn_32x4d,8.893,91.107,36.907,63.093,16.81,224,0.875,bicubic,-83.927,-61.463,+34
mixnet_l,8.853,91.147,36.187,63.813,7.33,224,0.875,bicubic,-84.597,-62.033,+6
dla169,8.640,91.360,36.040,63.960,53.39,224,0.875,bilinear,-84.700,-62.560,+9
hrnet_w30,8.613,91.387,37.040,62.960,37.71,224,0.875,bilinear,-84.587,-61.370,+15
tf_efficientnet_b1_ap,8.453,91.547,35.253,64.747,7.79,240,0.882,bicubic,-85.237,-63.107,-11
resnetblur50,8.240,91.760,37.400,62.600,25.56,224,0.875,bicubic,-85.720,-61.190,-29
dla102x,8.200,91.800,37.013,62.987,26.31,224,0.875,bilinear,-85.320,-61.497,-5
hrnet_w32,8.040,91.960,37.507,62.493,41.23,224,0.875,bilinear,-85.490,-60.943,-7
res2net50_26w_8s,8.000,92.000,33.853,66.147,48.40,224,0.875,bilinear,-85.540,-64.407,-9
gluon_resnet101_v1c,7.987,92.013,33.360,66.640,44.57,224,0.875,bicubic,-85.683,-65.060,-15
gluon_resnet50_v1d,7.920,92.080,35.000,65.000,25.58,224,0.875,bicubic,-85.850,-63.390,-23
dla60_res2next,7.787,92.213,34.987,65.013,17.03,224,0.875,bilinear,-85.393,-63.423,+9
densenetblur121d,7.720,92.280,34.733,65.267,8.00,224,0.875,bicubic,-84.190,-63.337,+53
regnety_032,7.680,92.320,34.227,65.773,19.44,224,0.875,bicubic,-85.710,-64.413,-3
dla60_res2net,7.560,92.440,34.627,65.373,20.85,224,0.875,bilinear,-85.620,-63.793,+5
efficientnet_b1_pruned,7.440,92.560,34.533,65.467,6.33,240,0.882,bicubic,-85.330,-63.507,+21
wide_resnet101_2,7.360,92.640,34.147,65.853,126.89,224,0.875,bilinear,-86.360,-64.393,-25
regnetx_064,7.333,92.667,34.373,65.627,26.21,224,0.875,bicubic,-86.557,-64.257,-36
gluon_resnet101_v1b,7.227,92.773,32.773,67.227,44.55,224,0.875,bicubic,-86.523,-65.607,-29
efficientnet_b0,7.213,92.787,34.013,65.987,5.29,224,0.875,bicubic,-85.477,-64.057,+23
gluon_resnet50_v1s,7.213,92.787,33.507,66.493,25.68,224,0.875,bicubic,-86.407,-64.953,-24
tf_mixnet_l,7.147,92.853,31.613,68.387,7.33,224,0.875,bicubic,-86.163,-66.417,-7
tf_efficientnet_b1,7.133,92.867,33.040,66.960,7.79,240,0.882,bicubic,-86.367,-65.320,-20
tf_efficientnet_cc_b0_8e,7.120,92.880,31.787,68.213,24.01,224,0.875,bicubic,-85.710,-66.393,+10
ese_vovnet19b_dw,6.733,93.267,33.413,66.587,6.54,224,0.875,bicubic,-85.557,-64.677,+32
selecsls60b,6.733,93.267,33.267,66.733,32.77,224,0.875,bicubic,-86.567,-65.013,-9
efficientnet_es,6.707,93.293,33.840,66.160,5.44,224,0.875,bicubic,-86.433,-64.580,-4
res2net50_26w_6s,6.693,93.307,31.653,68.347,37.05,224,0.875,bilinear,-86.717,-66.627,-18
mixnet_m,6.627,93.373,32.053,67.947,5.01,224,0.875,bicubic,-85.803,-65.817,+23
skresnet34,6.480,93.520,31.547,68.453,22.28,224,0.875,bicubic,-85.910,-66.603,+24
dla60x,6.427,93.573,34.080,65.920,17.35,224,0.875,bilinear,-86.693,-64.430,-7
regnetx_080,6.307,93.693,32.320,67.680,39.57,224,0.875,bicubic,-87.563,-66.200,-49
swsl_resnet18,6.240,93.760,31.600,68.400,11.69,224,0.875,bilinear,-84.450,-66.100,+57
resnet152,6.040,93.960,32.053,67.947,60.19,224,0.875,bilinear,-87.260,-66.337,-18
wide_resnet50_2,6.000,94.000,32.147,67.853,68.88,224,0.875,bilinear,-87.170,-66.203,-13
regnetx_040,5.973,94.027,31.547,68.453,22.12,224,0.875,bicubic,-87.587,-66.993,-38
tf_efficientnet_cc_b0_4e,5.973,94.027,29.600,70.400,13.31,224,0.875,bicubic,-86.617,-68.480,+9
resnet50,5.933,94.067,29.093,70.907,25.56,224,0.875,bicubic,-87.877,-69.297,-51
dla102,5.880,94.120,32.707,67.293,33.27,224,0.875,bilinear,-87.180,-65.833,-12
regnety_016,5.680,94.320,30.413,69.587,11.20,224,0.875,bicubic,-87.350,-67.947,-11
selecsls60,5.653,94.347,32.507,67.493,30.67,224,0.875,bicubic,-87.377,-65.793,-10
res2next50,5.627,94.373,30.867,69.133,24.67,224,0.875,bilinear,-87.213,-67.313,-9
tf_efficientnet_em,5.520,94.480,32.173,67.827,6.90,240,0.882,bicubic,-87.960,-66.267,-38
hrnet_w18,5.493,94.507,30.960,69.040,21.30,224,0.875,bilinear,-86.827,-67.280,+12
resnest14d,5.480,94.520,28.547,71.453,10.61,224,0.875,bilinear,-86.240,-69.323,+26
tf_efficientnet_lite2,5.360,94.640,30.907,69.093,6.09,260,0.890,bicubic,-87.290,-67.323,-2
tf_efficientnet_b0_ap,5.307,94.693,28.813,71.187,5.29,224,0.875,bicubic,-86.893,-69.207,+14
densenet121,5.293,94.707,29.907,70.093,7.98,224,0.875,bicubic,-86.277,-68.123,+24
res2net50_26w_4s,5.160,94.840,29.360,70.640,25.70,224,0.875,bilinear,-87.340,-68.700,+2
tf_mixnet_m,5.080,94.920,28.147,71.853,5.01,224,0.875,bicubic,-87.250,-69.743,+5
mobilenetv3_large_100,5.067,94.933,28.187,71.813,5.48,224,0.875,bicubic,-86.253,-69.523,+24
tf_efficientnet_b0,5.067,94.933,28.800,71.200,5.29,224,0.875,bicubic,-87.183,-69.200,+7
res2net50_14w_8s,5.040,94.960,28.773,71.227,25.06,224,0.875,bilinear,-87.700,-69.407,-14
mixnet_s,4.907,95.093,28.573,71.427,4.13,224,0.875,bicubic,-86.923,-69.287,+15
mobilenetv3_rw,4.907,95.093,29.853,70.147,5.48,224,0.875,bicubic,-86.303,-67.807,+23
gluon_resnet50_v1c,4.893,95.107,28.147,71.853,25.58,224,0.875,bicubic,-88.137,-70.243,-28
regnetx_032,4.853,95.147,30.280,69.720,15.30,224,0.875,bicubic,-88.267,-68.110,-32
tv_resnext50_32x4d,4.840,95.160,30.307,69.693,25.03,224,0.875,bilinear,-87.900,-67.963,-18
resnet101,4.707,95.293,29.333,70.667,44.55,224,0.875,bilinear,-88.103,-68.917,-23
densenet161,4.693,95.307,29.547,70.453,28.68,224,0.875,bicubic,-87.807,-68.743,-10
selecsls42b,4.667,95.333,28.587,71.413,32.46,224,0.875,bicubic,-87.613,-69.563,-3
tf_efficientnet_lite1,4.613,95.387,28.387,71.613,5.42,240,0.882,bicubic,-88.007,-69.693,-17
mobilenetv2_120d,4.533,95.467,29.280,70.720,5.83,224,0.875,bicubic,-87.867,-68.770,-10
fbnetc_100,4.133,95.867,25.933,74.067,5.57,224,0.875,bilinear,-86.567,-71.277,+25
densenet201,4.120,95.880,27.547,72.453,20.01,224,0.875,bicubic,-88.630,-70.683,-27
gluon_resnet50_v1b,4.120,95.880,26.933,73.067,25.56,224,0.875,bicubic,-88.420,-71.237,-17
resnet26d,4.040,95.960,28.520,71.480,16.01,224,0.875,bicubic,-88.030,-69.440,-4
semnasnet_100,3.960,96.040,26.947,73.053,3.89,224,0.875,bicubic,-87.320,-70.613,+8
tf_mixnet_s,3.880,96.120,25.253,74.747,4.13,224,0.875,bicubic,-87.630,-72.367,+4
dpn68,3.867,96.133,26.080,73.920,12.61,224,0.875,bicubic,-88.143,-71.970,-6
regnety_008,3.813,96.187,27.133,72.867,6.26,224,0.875,bicubic,-87.937,-71.047,-1
dla60,3.773,96.227,27.933,72.067,22.04,224,0.875,bilinear,-88.457,-70.177,-12
ssl_resnet18,3.747,96.253,25.427,74.573,11.69,224,0.875,bilinear,-86.473,-72.123,+22
mobilenetv2_140,3.720,96.280,26.747,73.253,6.11,224,0.875,bicubic,-88.110,-70.943,-6
densenet169,3.707,96.293,25.613,74.387,14.15,224,0.875,bicubic,-88.223,-72.487,-10
regnetx_016,3.627,96.373,26.293,73.707,9.19,224,0.875,bicubic,-88.543,-71.917,-14
res2net50_48w_2s,3.587,96.413,26.613,73.387,25.29,224,0.875,bilinear,-88.963,-71.467,-30
spnasnet_100,3.547,96.453,24.293,75.707,4.42,224,0.875,bilinear,-86.803,-72.897,+16
tf_mobilenetv3_large_100,3.547,96.453,25.053,74.947,5.48,224,0.875,bilinear,-87.693,-72.607,-2
regnety_006,3.467,96.533,24.893,75.107,6.06,224,0.875,bicubic,-87.903,-72.817,-6
tf_efficientnet_es,3.427,96.573,27.493,72.507,5.44,224,0.875,bicubic,-89.123,-70.787,-33
efficientnet_lite0,3.253,96.747,25.867,74.133,4.65,224,0.875,bicubic,-87.887,-71.763,-2
dla34,3.227,96.773,23.573,76.427,15.74,224,0.875,bilinear,-87.533,-74.087,+5
regnety_004,3.200,96.800,22.653,77.347,4.34,224,0.875,bicubic,-87.300,-74.887,+8
mobilenetv2_110d,3.173,96.827,24.587,75.413,4.52,224,0.875,bicubic,-87.777,-72.963,+1
mnasnet_100,3.120,96.880,24.227,75.773,4.38,224,0.875,bicubic,-87.390,-73.243,+5
tf_efficientnet_lite0,3.080,96.920,22.907,77.093,4.65,224,0.875,bicubic,-87.960,-74.683,-3
skresnet18,3.013,96.987,22.800,77.200,11.96,224,0.875,bicubic,-86.647,-74.430,+10
resnet34,2.920,97.080,23.680,76.320,21.80,224,0.875,bilinear,-88.210,-73.940,-8
tf_mobilenetv3_large_075,2.867,97.133,21.573,78.427,3.99,224,0.875,bilinear,-86.813,-75.637,+7
hrnet_w18_small_v2,2.720,97.280,23.693,76.307,15.60,224,0.875,bilinear,-88.470,-74.207,-12
gluon_resnet34_v1b,2.667,97.333,21.680,78.320,21.80,224,0.875,bicubic,-88.293,-75.950,-7
regnetx_008,2.653,97.347,22.453,77.547,7.26,224,0.875,bicubic,-88.397,-75.257,-10
tv_densenet121,2.560,97.440,22.667,77.333,7.98,224,0.875,bicubic,-88.330,-75.043,-7
regnetx_006,2.507,97.493,20.653,79.347,6.20,224,0.875,bicubic,-87.843,-76.777,-2
resnet26,2.480,97.520,22.987,77.013,16.00,224,0.875,bicubic,-88.630,-74.753,-14
regnety_002,2.147,97.853,18.880,81.120,3.16,224,0.875,bicubic,-85.233,-77.710,+7
mobilenetv2_100,2.147,97.853,19.907,80.093,3.50,224,0.875,bicubic,-87.453,-77.233,+2
tf_mobilenetv3_small_100,2.013,97.987,15.867,84.133,2.54,224,0.875,bilinear,-83.177,-79.903,+9
tf_mobilenetv3_small_075,2.000,98.000,14.813,85.187,2.04,224,0.875,bilinear,-81.520,-79.977,+11
regnetx_004,1.960,98.040,19.173,80.827,5.16,224,0.875,bicubic,-86.940,-77.947,+1
tv_resnet34,1.867,98.133,20.000,80.000,21.80,224,0.875,bilinear,-88.073,-77.340,-6
dla46x_c,1.760,98.240,16.480,83.520,1.07,224,0.875,bilinear,-82.490,-78.790,+6
tf_mobilenetv3_large_minimal_100,1.627,98.373,17.120,82.880,3.92,224,0.875,bilinear,-87.343,-79.740,-3
dla60x_c,1.613,98.387,18.040,81.960,1.32,224,0.875,bilinear,-84.677,-78.120,+1
gluon_resnet18_v1b,1.547,98.453,16.613,83.387,11.69,224,0.875,bicubic,-86.853,-80.067,-3
hrnet_w18_small,1.533,98.467,18.120,81.880,13.19,224,0.875,bilinear,-87.517,-78.990,-7
dla46_c,1.520,98.480,15.267,84.733,1.30,224,0.875,bilinear,-82.130,-79.653,+2
regnetx_002,1.373,98.627,15.027,84.973,2.68,224,0.875,bicubic,-84.817,-80.953,-2
resnet18,1.160,98.840,16.213,83.787,11.69,224,0.875,bilinear,-86.230,-80.077,-6
tf_mobilenetv3_small_minimal_100,1.013,98.987,11.493,88.507,2.04,224,0.875,bilinear,-80.367,-82.177,+1
tv_resnet50,0.000,100.000,14.453,85.547,25.56,224,0.875,bilinear,-91.880,-83.587,-45

1 model top1 top1_err top5 top5_err param_count img_size cropt_pct interpolation top1_diff top5_diff rank_diff
2 tf_efficientnet_l2_ns_475 tf_efficientnet_l2_ns 62.387 84.760 37.613 15.240 87.107 96.147 12.893 3.853 480.31 475 800 0.936 0.960 bicubic -25.847 -13.790 -11.439 -3.673 +1 0
3 tf_efficientnet_l2_ns tf_efficientnet_l2_ns_475 62.027 83.373 37.973 16.627 87.960 95.453 12.040 4.547 480.31 800 475 0.960 0.936 bicubic -26.325 -15.127 -10.688 -4.377 -1 0
4 tf_efficientnet_b7_ns 45.720 67.040 54.280 32.960 74.200 88.667 25.800 11.333 66.35 600 0.949 bicubic -41.118 -30.870 -23.894 -11.053 = 0
5 ig_resnext101_32x48d tf_efficientnet_b6_ns 41.573 62.267 58.427 37.733 66.613 85.173 33.387 14.827 828.41 43.04 224 528 0.875 0.942 bilinear bicubic -43.869 -35.363 -30.959 -14.407 +2 0
6 tf_efficientnet_b6_ns ig_resnext101_32x48d 40.427 61.013 59.573 38.987 68.840 83.347 31.160 16.653 43.04 828.41 528 224 0.942 0.875 bicubic bilinear -46.035 -36.607 -29.044 -16.353 -1 0
7 ig_resnext101_32x32d tf_efficientnet_b5_ns 39.413 60.320 60.587 39.680 63.760 84.493 36.240 15.507 468.53 30.39 224 456 0.875 0.934 bilinear bicubic -45.679 -37.180 -33.676 -15.137 +5 0
8 tf_efficientnet_b5_ns ig_resnext101_32x32d 39.013 58.093 60.987 41.907 68.040 80.653 31.960 19.347 30.39 468.53 456 224 0.934 0.875 bicubic bilinear -47.067 -39.267 -29.714 -19.027 -2 0
9 ig_resnext101_32x16d 36.053 53.067 63.947 46.933 59.040 76.907 40.960 23.093 194.03 224 0.875 bilinear -48.123 -43.753 -38.156 -22.683 +9 +7
10 swsl_resnext101_32x8d tf_efficientnet_b4_ns 32.067 51.213 67.933 48.787 59.400 79.187 40.600 20.813 88.79 19.34 224 380 0.875 0.922 bilinear bicubic -52.227 -45.737 -37.774 -20.393 +5
11 tf_efficientnet_b4_ns swsl_resnext101_32x8d 30.800 51.187 69.200 48.813 59.440 78.240 40.560 21.760 19.34 88.79 380 224 0.922 0.875 bicubic bilinear -54.358 -46.013 -38.028 -21.330 -1 -2
12 tf_efficientnet_b8_ap tf_efficientnet_b8 29.600 48.947 70.400 51.053 56.933 77.240 43.067 22.760 87.41 672 0.954 bicubic -55.768 -48.253 -40.361 -22.260 -3 -1
13 tf_efficientnet_b8 resnest269e 29.373 48.187 70.627 51.813 57.067 74.333 42.933 25.667 87.41 110.93 672 416 0.954 0.928 bicubic -55.997 -48.333 -40.325 -25.017 -5 +8
14 ig_resnext101_32x8d tf_efficientnet_b8_ap 28.707 46.893 71.293 53.107 52.320 76.507 47.680 23.493 88.79 87.41 224 672 0.875 0.954 bilinear bicubic -53.981 -50.217 -44.312 -23.153 +16 -2
15 swsl_resnext101_32x16d 27.947 46.200 72.053 53.800 52.320 72.200 47.680 27.800 194.03 224 0.875 bilinear -55.391 -50.400 -44.532 -27.320 +8 +5
16 tf_efficientnet_b7_ap 27.813 45.373 72.187 54.627 54.773 74.213 45.227 25.787 66.35 600 0.949 bicubic -57.305 -51.827 -42.479 -25.327 -5 -6
17 resnest269e ig_resnext101_32x8d 27.613 45.320 72.387 54.680 53.107 70.867 46.893 29.133 110.93 88.79 416 224 0.875 bilinear -56.573 -51.000 -43.815 -28.563 = +8
18 tresnet_xl_448 resnest200e 26.880 44.147 73.120 55.853 51.093 73.467 48.907 26.533 78.44 70.20 448 320 0.875 0.909 bilinear bicubic -56.168 -52.463 -45.081 -25.883 +8 +1
19 resnest200e tresnet_xl_448 26.427 43.480 73.573 56.520 51.933 72.453 48.067 27.547 70.20 78.44 320 448 0.875 bilinear -57.407 -52.490 -44.905 -26.677 +2 +8
20 swsl_resnext101_32x4d tf_efficientnet_b7 25.347 42.960 74.653 57.040 49.627 73.133 50.373 26.867 44.18 66.35 224 600 0.875 0.949 bilinear bicubic -57.887 -54.050 -47.129 -26.387 +5 -6
21 tf_efficientnet_b7 swsl_resnext101_32x4d 25.253 41.560 74.747 58.440 51.667 71.760 48.333 28.240 66.35 44.18 600 224 0.949 0.875 bicubic bilinear -59.679 -54.860 -45.541 -27.710 -8 +1
22 tresnet_l_448 tf_efficientnet_b6_ap 24.573 40.800 75.427 59.200 48.600 71.627 51.400 28.373 55.99 43.04 448 528 0.875 0.942 bilinear bicubic -57.695 -56.280 -47.378 -27.993 +11 -9
23 tf_efficientnet_b6_ap tresnet_l_448 24.347 40.200 75.653 59.800 50.427 69.893 49.573 30.107 43.04 55.99 528 448 0.942 0.875 bicubic bilinear -60.439 -55.660 -46.711 -29.227 -9 +8
24 tf_efficientnet_b6 tf_efficientnet_b3_ns 20.373 35.520 79.627 64.480 45.493 67.773 54.507 32.227 43.04 12.23 528 300 0.942 0.904 bicubic -63.739 -60.870 -51.391 -31.577 -5 -1
25 tresnet_m_448 tf_efficientnet_b6 19.680 35.213 80.320 64.787 42.760 67.720 57.240 32.280 31.39 43.04 448 528 0.875 0.942 bilinear bicubic -62.032 -61.457 -52.810 -31.650 +15 -7
26 tf_efficientnet_b5_ap 19.467 34.787 80.533 65.213 44.720 67.493 55.280 32.507 30.39 456 0.934 bicubic -64.787 -61.893 -52.256 -31.967 -10 -9
27 tf_efficientnet_b3_ns tresnet_m_448 19.413 34.107 80.587 65.893 44.627 64.493 55.373 35.507 12.23 31.39 300 448 0.904 0.875 bicubic bilinear -64.641 -60.883 -52.285 -34.487 -7 +22
28 swsl_resnext50_32x4d 18.067 33.013 81.933 66.987 41.867 65.067 58.133 34.933 25.03 224 0.875 bilinear -64.113 -62.857 -54.361 -34.183 +6 +1
29 ssl_resnext101_32x16d 17.213 32.600 82.787 67.400 39.947 64.000 60.053 36.000 194.03 224 0.875 bilinear -64.623 -63.200 -56.147 -35.180 +9 +3
30 tf_efficientnet_b5 17.067 31.840 82.933 68.160 41.907 65.293 58.093 34.707 30.39 456 0.934 bicubic -66.749 -64.510 -54.843 -34.017 -8 -6
31 resnest101e 16.493 31.413 83.507 68.587 40.747 64.360 59.253 35.640 48.28 256 0.875 bilinear -66.397 -64.447 -55.577 -34.850 -3 -1
32 swsl_resnet50 15.987 29.867 84.013 70.133 38.853 63.853 61.147 36.147 25.56 224 0.875 bilinear -65.193 -65.543 -57.133 -35.437 +17 +8
33 ssl_resnext101_32x8d 15.120 29.040 84.880 70.960 37.720 60.973 62.280 39.027 88.79 224 0.875 bilinear -66.506 -66.430 -58.318 -38.137 +9 +4
34 tf_efficientnet_b4_ap tf_efficientnet_b4 13.680 26.293 86.320 73.707 35.920 60.107 64.080 39.893 19.34 380 0.922 bicubic -69.568 -69.607 -60.468 -39.063 -10 -6
35 ecaresnet101d tf_efficientnet_b4_ap 13.307 26.240 86.693 73.760 35.533 60.227 64.467 39.773 44.57 19.34 224 380 0.875 0.922 bicubic -68.859 -69.920 -60.519 -39.053 = -9
36 tf_efficientnet_b4 ecaresnet101d 13.307 26.027 86.693 73.973 35.520 58.987 64.480 41.013 19.34 44.57 380 224 0.922 0.875 bicubic -69.709 -69.503 -60.778 -40.143 -9 0
37 pnasnet5large ssl_resnext101_32x4d 13.080 24.173 86.920 75.827 32.213 57.413 67.787 42.587 86.06 44.18 331 224 0.875 bicubic bilinear -69.660 -71.267 -63.827 -41.717 -8 +1
38 nasnetalarge tf_efficientnet_b2_ns 12.573 24.013 87.427 75.987 33.413 57.293 66.587 42.707 88.75 9.11 331 260 0.875 0.890 bicubic -69.985 -71.757 -62.623 -41.827 -7 -5
39 ssl_resnext101_32x4d nasnetalarge 12.120 23.493 87.880 76.507 31.893 55.027 68.107 44.973 44.18 88.75 224 331 0.875 0.911 bilinear bicubic -68.808 -72.187 -63.835 -43.903 +15 -4
40 tf_efficientnet_b2_ns pnasnet5large 11.787 23.333 88.213 76.667 32.960 53.640 67.040 46.360 9.11 86.06 260 331 0.890 0.911 bicubic -70.593 -72.377 -63.292 -45.280 -8 -6
41 gluon_senet154 resnest50d_4s2x40d 9.907 20.387 90.093 79.613 26.453 52.800 73.547 47.200 115.09 30.42 224 0.875 bicubic -71.317 -74.573 -68.903 -46.270 +7 +9
42 resnest50d_4s2x40d ssl_resnext50_32x4d 9.787 20.000 90.213 80.000 29.147 53.613 70.853 46.387 30.42 25.03 224 0.875 bicubic bilinear -71.327 -74.870 -66.421 -45.267 +8 +14
43 ssl_resnext50_32x4d tresnet_xl 9.667 19.640 90.333 80.360 28.427 53.133 71.573 46.867 25.03 78.44 224 0.875 bilinear -70.661 -75.800 -66.977 -45.917 +30 -4
44 senet154 gluon_senet154 9.453 19.307 90.547 80.693 26.440 47.533 73.560 52.467 115.09 224 0.875 bilinear bicubic -71.851 -75.613 -69.058 -51.227 +3 +9
45 tresnet_xl rexnet_200 9.307 19.227 90.693 80.773 28.413 52.720 71.587 47.280 78.44 16.37 224 0.875 bilinear bicubic -72.763 -75.713 -67.515 -46.290 -9 +6
46 efficientnet_b3a gluon_seresnext101_64x4d 9.267 18.907 90.733 81.093 28.427 49.187 71.573 50.813 12.23 88.23 320 224 1.000 0.875 bicubic -72.607 -76.023 -67.413 -49.643 -9 +6
47 efficientnet_b3 tf_efficientnet_b1_ns 8.947 18.693 91.053 81.307 28.213 51.667 71.787 48.333 12.23 7.79 300 240 0.904 0.882 bicubic -72.551 -76.477 -67.505 -47.443 -3 -4
48 inception_v4 efficientnet_b3 8.920 18.693 91.080 81.307 24.707 52.347 75.293 47.653 42.68 12.23 299 300 0.875 0.904 bicubic -71.236 -76.387 -70.267 -46.633 +32 -1
49 gluon_seresnext101_64x4d efficientnet_b3a 8.867 18.600 91.133 81.400 27.320 51.640 72.680 48.360 88.23 12.23 224 320 0.875 1.000 bicubic -72.023 -76.660 -67.984 -47.290 +7 -6
50 tf_efficientnet_b1_ns ecaresnet50d 8.613 18.227 91.387 81.773 27.280 51.893 72.720 48.107 7.79 25.58 240 224 0.882 0.875 bicubic -72.773 -76.403 -68.458 -46.997 -4 +15
51 resnest50d_1s4x24d tf_efficientnet_lite4 8.520 18.133 91.480 81.867 26.787 50.707 73.213 49.293 25.68 13.01 224 380 0.875 0.920 bicubic bilinear -72.470 -76.757 -68.535 -48.313 +1 +4
52 ecaresnet50d resnest50d_1s4x24d 8.507 17.693 91.493 82.307 26.267 49.800 73.733 50.200 25.58 25.68 224 0.875 bicubic -72.097 -77.057 -69.055 -49.180 +10 +7
53 gluon_xception65 gluon_seresnext101_32x4d 8.467 17.373 91.533 82.627 25.133 46.373 74.867 53.627 39.92 48.96 299 224 0.875 bicubic -71.137 -77.547 -69.615 -52.437 +45 +1
54 gluon_resnet152_v1d resnest50d 8.413 17.373 91.587 82.627 23.453 50.707 76.547 49.293 60.21 27.48 224 0.875 bicubic bilinear -72.057 -77.457 -71.753 -48.173 +11 +3
55 inception_resnet_v2 inception_v4 8.160 17.267 91.840 82.733 23.533 45.920 76.467 54.080 55.84 42.68 299 0.897 0.875 bicubic -72.300 -77.113 -71.777 -52.660 +11 +25
56 tf_efficientnet_b3_ap 8.133 17.187 91.867 82.813 26.280 49.680 73.720 50.320 12.23 300 0.904 bicubic -73.695 -78.133 -69.344 -49.220 -17 -15
57 gluon_seresnext101_32x4d tf_efficientnet_b3 8.040 17.000 91.960 83.000 24.733 49.267 75.267 50.733 48.96 12.23 224 300 0.875 0.904 bicubic -72.862 -78.010 -70.561 -49.643 -2 -9
58 tf_efficientnet_b3 xception71 8.013 17.000 91.987 83.000 25.467 45.520 74.533 54.480 12.23 42.34 300 299 0.904 0.903 bicubic -73.627 -77.280 -70.255 -53.120 -17 +27
59 ens_adv_inception_resnet_v2 gluon_resnext101_64x4d 7.987 16.853 92.013 83.147 23.827 44.213 76.173 55.787 55.84 83.46 299 224 0.897 0.875 bicubic -71.989 -77.817 -71.119 -54.437 +25 +4
60 tf_efficientnet_lite4 tresnet_l 7.933 16.600 92.067 83.400 25.560 49.920 74.440 50.080 13.01 55.99 380 224 0.920 0.875 bilinear -73.595 -78.690 -70.108 -49.090 -17 -18
61 tresnet_l inception_resnet_v2 7.880 16.573 92.120 83.427 25.187 44.960 74.813 55.040 55.99 55.84 224 299 0.875 0.897 bilinear bicubic -73.608 -77.967 -70.441 -53.830 -16 +8
62 gluon_resnet152_v1s 7.867 16.573 92.133 83.427 23.173 44.533 76.827 55.467 60.32 224 0.875 bicubic -73.145 -78.467 -72.243 -54.397 -11 -15
63 resnest50d gluon_resnet152_v1d 7.747 16.573 92.253 83.427 25.293 44.280 74.707 55.720 27.48 60.21 224 0.875 bilinear bicubic -73.211 -78.167 -70.089 -54.460 -10 -1
64 gluon_resnext101_64x4d gluon_xception65 7.707 16.440 92.293 83.560 23.240 46.027 76.760 53.973 83.46 39.92 224 299 0.875 0.903 bicubic -72.895 -77.820 -71.754 -52.543 -1 +22
65 skresnext50_32x4d ens_adv_inception_resnet_v2 7.080 16.240 92.920 83.760 23.027 43.640 76.973 56.360 27.48 55.84 224 299 0.875 0.897 bicubic -73.070 -77.920 -71.617 -54.960 +16 +31
66 ssl_resnet50 xception65 7.000 16.027 93.000 83.973 23.920 43.773 76.080 56.227 25.56 39.92 224 299 0.875 0.903 bilinear bicubic -72.228 -77.733 -70.912 -54.597 +45 +53
67 regnety_320 ssl_resnet50 6.920 15.960 93.080 84.040 23.040 49.467 76.960 50.533 145.05 25.56 224 0.875 bicubic bilinear -73.894 -78.490 -72.200 -49.453 -9 +12
68 ecaresnet101d_pruned regnety_320 6.800 15.627 93.200 84.373 24.200 44.827 75.800 55.173 24.88 145.05 224 0.875 bicubic -74.008 -78.913 -71.428 -54.023 -9 +4
69 ecaresnetlight ecaresnet101d_pruned 6.760 15.600 93.240 84.400 22.560 48.027 77.440 51.973 30.16 24.88 224 0.875 bicubic -73.694 -79.480 -72.696 -50.953 -2 -24
70 efficientnet_b2a skresnext50_32x4d 6.760 15.373 93.240 84.627 23.493 44.493 76.507 55.507 9.11 27.48 288 224 1.000 0.875 bicubic -73.848 -78.887 -71.817 -53.967 -9 +17
71 seresnext101_32x4d ecaresnetlight 6.413 15.160 93.587 84.840 21.520 45.827 78.480 54.173 48.96 30.16 224 0.875 bilinear bicubic -73.823 -79.610 -73.508 -52.973 +7 -13
72 efficientnet_b2 rexnet_150 6.093 14.720 93.907 85.280 21.933 46.907 78.067 53.093 9.11 9.73 260 224 0.875 bicubic -74.309 -79.760 -73.143 -51.903 -2 +4
73 gluon_resnext101_32x4d efficientnet_b2a 6.040 14.440 93.960 85.560 21.133 46.080 78.867 53.920 44.18 9.11 224 288 0.875 1.000 bicubic -74.294 -80.170 -73.793 -52.630 -1 -5
74 regnetx_320 seresnet50 5.987 14.147 94.013 85.853 19.880 45.467 80.120 54.533 107.81 28.09 224 0.875 bicubic -74.259 -80.403 -75.142 -53.283 +3 -4
75 ese_vovnet39b gluon_resnext101_32x4d 5.973 13.867 94.027 86.133 21.293 41.653 78.707 58.347 24.57 44.18 224 0.875 bicubic -73.347 -80.663 -73.417 -56.977 +29 -2
76 gluon_resnet101_v1d gluon_seresnext50_32x4d 5.920 13.600 94.080 86.400 19.947 43.760 80.053 56.240 44.57 27.56 224 0.875 bicubic -74.504 -80.740 -75.073 -54.850 -7 +6
77 gluon_seresnext50_32x4d ese_vovnet39b 5.787 13.320 94.213 86.680 21.427 43.813 78.573 56.187 27.56 24.57 224 0.875 bicubic -74.125 -80.770 -73.391 -54.847 +10 +26
78 efficientnet_b3_pruned efficientnet_b2 5.733 13.307 94.267 86.693 21.360 44.440 78.640 55.560 9.86 9.11 300 260 0.904 0.875 bicubic -75.123 -81.393 -73.880 -54.230 -21 -16
79 regnety_160 regnetx_320 5.640 13.307 94.360 86.693 19.347 40.720 80.653 59.280 83.59 107.81 224 0.875 bicubic -74.660 -81.153 -75.615 -58.020 -3 -1
80 gluon_inception_v3 efficientnet_b3_pruned 5.507 13.173 94.493 86.827 19.947 45.213 80.053 54.787 23.83 9.86 299 300 0.875 0.904 bicubic -73.297 -81.457 -74.433 -53.547 +47 -14
81 mixnet_xl gluon_resnet101_v1d 5.480 13.160 94.520 86.840 21.093 41.493 78.907 58.507 11.90 44.57 224 0.875 bicubic -74.998 -81.060 -73.839 -57.057 -17 +10
82 tresnet_m mixnet_xl 5.440 13.120 94.560 86.880 19.960 43.253 80.040 56.747 31.39 11.90 224 0.875 bilinear bicubic -75.356 -81.070 -74.896 -55.087 -22 +11
83 regnety_120 gluon_inception_v3 5.413 12.640 94.587 87.360 19.853 40.493 80.147 59.507 51.82 23.83 224 299 0.875 bicubic -74.969 -80.820 -75.275 -58.077 -12 +53
84 gluon_resnet101_v1s tresnet_m 5.280 12.600 94.720 87.400 19.547 41.893 80.453 58.107 44.67 31.39 224 0.875 bicubic bilinear -75.020 -82.020 -75.603 -56.657 -9 -17
85 hrnet_w64 regnety_120 5.133 12.427 94.867 87.573 19.453 42.200 80.547 57.800 128.06 51.82 224 0.875 bilinear bicubic -74.339 -82.053 -75.197 -56.480 +16 -10
86 regnety_080 regnety_160 5.000 12.200 95.000 87.800 18.600 41.320 81.400 58.680 39.18 83.59 224 0.875 bicubic -74.868 -82.140 -76.232 -57.530 +2 -3
87 efficientnet_b2_pruned hrnet_w64 4.947 12.027 95.053 87.973 19.347 40.787 80.653 59.213 8.31 128.06 260 224 0.890 0.875 bicubic bilinear -74.971 -81.983 -75.501 -57.823 -2 +19
88 dpn107 cspdarknet53 4.880 12.013 95.120 87.987 17.613 43.253 82.387 56.747 86.92 27.64 224 256 0.875 0.887 bicubic bilinear -75.284 -82.647 -77.299 -55.547 -9 -24
89 gluon_resnet152_v1c gluon_resnet101_v1s 4.867 11.880 95.133 88.120 17.773 40.973 82.227 59.027 60.21 44.67 224 0.875 bicubic -75.049 -82.840 -77.069 -57.847 -3 -28
90 adv_inception_v3 dpn92 4.747 11.627 95.253 88.373 17.547 40.267 82.453 59.733 23.83 37.67 299 224 0.875 bicubic -72.833 -82.603 -76.177 -58.463 +76 -1
91 dla102x2 xception41 4.747 11.600 95.253 88.400 18.960 39.133 81.040 60.867 41.75 26.97 224 299 0.875 0.903 bilinear bicubic -74.705 -81.830 -75.684 -59.297 +11 +48
92 tf_inception_v3 dla102x2 4.747 11.573 95.253 88.427 17.747 41.293 82.253 58.707 23.83 41.28 299 224 0.875 bicubic bilinear -73.109 -82.377 -75.897 -57.197 +68 +16
93 hrnet_w48 regnety_080 4.720 11.413 95.280 88.587 18.440 40.613 81.560 59.387 77.47 39.18 224 0.875 bilinear bicubic -74.590 -82.757 -76.078 -58.067 +13 +2
94 dpn131 efficientnet_b2_pruned 4.640 11.360 95.360 88.640 16.867 42.027 83.133 57.973 79.25 8.31 224 260 0.875 0.890 bicubic -75.188 -82.780 -77.837 -56.503 -4 +5
95 gluon_resnet152_v1b gluon_resnet152_v1c 4.587 11.093 95.413 88.907 16.533 37.120 83.467 62.880 60.19 60.21 224 0.875 bicubic -75.105 -83.067 -78.205 -61.520 = +2
96 ecaresnet50d_pruned dpn107 4.547 11.080 95.453 88.920 18.547 38.693 81.453 61.307 19.94 86.92 224 0.875 bicubic -75.171 -83.230 -76.343 -59.787 -3 -12
97 dpn92 hrnet_w48 4.493 11.080 95.507 88.920 18.200 40.320 81.800 59.680 37.67 77.47 224 0.875 bicubic bilinear -75.523 -82.840 -76.638 -58.290 -14 +12
98 hrnet_w44 ecaresnet50d_pruned 4.493 11.027 95.507 88.973 17.347 41.947 82.653 58.053 67.06 19.94 224 0.875 bilinear bicubic -74.401 -83.193 -77.023 -56.783 +25 -8
99 regnetx_160 adv_inception_v3 4.373 11.013 95.627 88.987 17.093 36.720 82.907 63.280 54.28 23.83 224 299 0.875 bicubic -75.493 -81.867 -77.735 -61.420 -10 +63
100 resnext50d_32x4d tf_efficientnet_el 4.347 10.960 95.653 89.040 17.773 41.773 82.227 58.227 25.05 10.59 224 300 0.875 0.904 bicubic -75.327 -83.630 -77.095 -56.977 -4 -31
101 xception tf_efficientnet_b0_ns 4.347 10.933 95.653 89.067 16.760 40.067 83.240 59.933 22.86 5.29 299 224 0.897 0.875 bicubic -74.701 -82.697 -77.632 -58.573 +18 +25
102 seresnext50_32x4d tf_inception_v3 4.280 10.840 95.720 89.160 17.813 36.853 82.187 63.147 27.56 23.83 224 299 0.875 bilinear bicubic -74.796 -82.480 -76.621 -61.177 +14 +42
103 resnext50_32x4d 4.253 10.800 95.747 89.200 18.387 40.307 81.613 59.693 25.03 224 0.875 bicubic -75.509 -83.300 -76.213 -58.043 -11 -1
104 tf_efficientnet_cc_b1_8e dpn131 4.240 10.787 95.760 89.213 15.947 37.200 84.053 62.800 39.72 79.25 240 224 0.882 0.875 bicubic -75.058 -83.223 -78.417 -61.520 +4 +1
105 regnety_064 tf_efficientnet_b2_ap 4.227 10.533 95.773 89.467 17.187 40.107 82.813 59.893 30.58 9.11 224 260 0.875 0.890 bicubic -75.485 -83.957 -77.587 -58.513 -11 -31
106 tf_efficientnet_el resnext50d_32x4d 4.227 10.413 95.773 89.587 18.173 39.733 81.827 60.267 10.59 25.05 300 224 0.904 0.875 bicubic -76.221 -83.767 -76.987 -58.837 -38 -12
107 inception_v3 rexnet_130 4.187 10.400 95.813 89.600 16.293 41.547 83.707 58.453 23.83 7.56 299 224 0.875 bicubic -73.249 -83.500 -77.183 -56.853 +64 +3
108 tf_efficientnet_b2_ap hrnet_w44 4.173 10.320 95.827 89.680 18.320 39.507 81.680 60.493 9.11 67.06 260 224 0.890 0.875 bicubic bilinear -76.133 -83.230 -76.708 -59.193 -34 +21
109 seresnet152 resnext101_32x8d 4.147 10.187 95.853 89.813 15.893 37.827 84.107 62.173 66.82 88.79 224 0.875 bilinear -74.511 -83.643 -78.481 -60.753 +24 +6
110 resnext101_32x8d regnetx_160 4.133 10.147 95.867 89.853 16.987 38.000 83.013 62.000 88.79 54.28 224 0.875 bilinear bicubic -75.179 -83.973 -77.539 -60.750 -5 -9
111 tf_efficientnet_b0_ns dpn98 4.133 10.133 95.867 89.867 17.680 36.587 82.320 63.413 5.29 61.57 224 0.875 bicubic -74.519 -83.997 -76.688 -61.983 +23 -11
112 dpn98 cspresnext50 4.080 10.120 95.920 89.880 15.947 40.373 84.053 59.627 61.57 20.57 224 0.875 bicubic bilinear -75.556 -84.360 -78.647 -58.417 -15 -35
113 res2net101_26w_4s inception_v3 4.000 10.027 96.000 89.973 14.827 35.213 85.173 64.787 45.21 23.83 224 299 0.875 bilinear bicubic -75.196 -82.693 -79.613 -62.757 +2 +58
114 efficientnet_b1 xception 3.973 9.987 96.027 90.013 15.760 38.027 84.240 61.973 7.79 22.86 240 299 0.875 0.897 bicubic -74.725 -83.473 -78.392 -60.503 +17 +23
115 tf_efficientnet_lite3 regnety_064 3.933 9.947 96.067 90.053 16.520 39.067 83.480 60.933 8.20 30.58 300 224 0.904 0.875 bilinear bicubic -75.879 -84.203 -78.394 -59.663 -24 -17
116 tf_efficientnet_b2 dpn68b 3.773 9.787 96.227 90.213 16.613 38.053 83.387 61.947 9.11 12.61 260 224 0.890 0.875 bicubic -76.317 -83.903 -78.293 -60.457 -34 +7
117 regnety_040 gluon_resnet152_v1b 3.747 9.747 96.253 90.253 16.400 36.067 83.600 63.933 20.65 60.19 224 0.875 bicubic -75.475 -84.333 -78.256 -62.383 -5 -13
118 hrnet_w30 tf_efficientnet_lite3 3.680 9.667 96.320 90.333 15.573 39.000 84.427 61.000 37.71 8.20 224 300 0.875 0.904 bilinear -74.516 -84.533 -78.647 -59.640 +31 -26
119 hrnet_w32 tf_efficientnet_b2 3.653 9.653 96.347 90.347 14.787 38.880 85.213 61.120 41.23 9.11 224 260 0.875 0.890 bilinear bicubic -74.795 -84.707 -79.401 -59.730 +23 -38
120 hrnet_w40 tf_efficientnet_cc_b1_8e 3.653 9.573 96.347 90.427 15.440 36.773 84.560 63.227 57.56 39.72 224 240 0.875 0.882 bilinear bicubic -75.281 -84.327 -79.026 -61.487 +2 -9
121 regnetx_120 res2net101_26w_4s 3.627 9.520 96.373 90.480 15.973 35.027 84.027 64.973 46.11 45.21 224 0.875 bicubic bilinear -75.963 -84.230 -78.767 -63.283 -22 0
122 seresnext26t_32x4d 3.613 9.347 96.387 90.653 15.893 37.520 84.107 62.480 16.82 224 0.875 bicubic -74.375 -83.723 -77.813 -60.590 +34
123 tf_efficientnet_b1_ap hrnet_w40 3.547 9.227 96.453 90.773 15.067 36.893 84.933 63.107 7.79 57.56 240 224 0.882 0.875 bicubic bilinear -75.731 -84.263 -79.241 -61.687 -13 +11
124 seresnext26tn_32x4d regnetx_120 3.507 9.187 96.493 90.813 15.760 37.200 84.240 62.800 16.81 46.11 224 0.875 bicubic -74.483 -85.053 -77.988 -61.450 +31 -36
125 resnest26d seresnext26d_32x4d 3.493 9.147 96.507 90.853 15.667 36.840 84.333 63.160 17.07 16.81 224 0.875 bilinear bicubic -74.989 -83.553 -78.623 -61.310 +13 +47
126 dla169 efficientnet_b1 3.467 9.120 96.533 90.880 15.333 37.360 84.667 62.640 53.99 7.79 224 240 0.875 bilinear bicubic -75.243 -84.140 -79.005 -60.810 +4 +22
127 gluon_resnext50_32x4d resnest26d 3.453 9.080 96.547 90.920 16.120 37.853 83.880 62.147 25.03 17.07 224 0.875 bicubic bilinear -75.903 -84.250 -78.304 -60.777 -24 +16
128 mixnet_l regnety_040 3.440 9.000 96.560 91.000 15.307 37.053 84.693 62.947 7.33 20.65 224 0.875 bicubic -75.536 -84.860 -78.877 -61.597 -7 -14
129 seresnext26d_32x4d gluon_resnext50_32x4d 3.400 8.947 96.600 91.053 16.160 36.333 83.840 63.667 16.81 25.03 224 0.875 bicubic -74.204 -84.863 -77.452 -62.077 +36 -13
130 res2net50_26w_8s rexnet_100 3.333 8.893 96.667 91.107 14.040 36.373 85.960 63.627 48.40 4.80 224 0.875 bilinear bicubic -75.877 -84.137 -80.322 -61.817 -17 +30
131 resnetblur50 seresnext26tn_32x4d 3.333 8.893 96.667 91.107 15.587 36.907 84.413 63.093 25.56 16.81 224 0.875 bicubic -75.957 -83.927 -79.045 -61.463 -22 +34
132 dla102x mixnet_l 3.307 8.853 96.693 91.147 15.120 36.187 84.880 63.813 26.77 7.33 224 0.875 bilinear bicubic -75.201 -84.597 -79.114 -62.033 +4 +6
133 gluon_resnet101_v1c dla169 3.307 8.640 96.693 91.360 14.120 36.040 85.880 63.960 44.57 53.39 224 0.875 bicubic bilinear -76.237 -84.700 -80.466 -62.560 -33 +9
134 seresnet101 hrnet_w30 3.253 8.613 96.747 91.387 15.453 37.040 84.547 62.960 49.33 37.71 224 0.875 bilinear -75.143 -84.587 -78.805 -61.370 +10 +15
135 densenetblur121d tf_efficientnet_b1_ap 3.067 8.453 96.933 91.547 14.280 35.253 85.720 64.747 8.00 7.79 224 240 0.875 0.882 bicubic -73.509 -85.237 -78.910 -63.107 +55 -11
136 dla60_res2next resnetblur50 3.040 8.240 96.960 91.760 14.453 37.400 85.547 62.600 17.33 25.56 224 0.875 bilinear bicubic -75.408 -85.720 -79.691 -61.190 +5 -29
137 regnety_032 dla102x 3.027 8.200 96.973 91.800 14.240 37.013 85.760 62.987 19.44 26.31 224 0.875 bicubic bilinear -75.843 -85.320 -80.162 -61.497 -13 -5
138 gluon_resnet50_v1d hrnet_w32 3.013 8.040 96.987 91.960 14.627 37.507 85.373 62.493 25.58 41.23 224 0.875 bicubic bilinear -76.061 -85.490 -79.849 -60.943 -21 -7
139 wide_resnet101_2 res2net50_26w_8s 2.960 8.000 97.040 92.000 13.947 33.853 86.053 66.147 126.89 48.40 224 0.875 bilinear -75.886 -85.540 -80.337 -64.407 -14 -9
140 efficientnet_b1_pruned gluon_resnet101_v1c 2.933 7.987 97.067 92.013 14.413 33.360 85.587 66.640 6.33 44.57 240 224 0.882 0.875 bicubic -75.309 -85.683 -79.419 -65.060 +7 -15
141 gluon_resnet50_v1s gluon_resnet50_v1d 2.920 7.920 97.080 92.080 13.120 35.000 86.880 65.000 25.68 25.58 224 0.875 bicubic -75.792 -85.850 -81.122 -63.390 -12 -23
142 tf_efficientnet_b1 dla60_res2next 2.867 7.787 97.133 92.213 13.507 34.987 86.493 65.013 7.79 17.03 240 224 0.882 0.875 bicubic bilinear -75.965 -85.393 -80.689 -63.423 -16 +9
143 res2net50_26w_6s densenetblur121d 2.840 7.720 97.160 92.280 12.600 34.733 87.400 65.267 37.05 8.00 224 0.875 bilinear bicubic -75.734 -84.190 -81.526 -63.337 -8 +53
144 efficientnet_b0 regnety_032 2.813 7.680 97.187 92.320 13.907 34.227 86.093 65.773 5.29 19.44 224 0.875 bicubic -74.879 -85.710 -79.625 -64.413 +18 -3
145 tf_mixnet_l dla60_res2net 2.813 7.560 97.187 92.440 13.040 34.627 86.960 65.373 7.33 20.85 224 0.875 bicubic bilinear -75.957 -85.620 -80.964 -63.793 -17 +5
146 regnetx_064 efficientnet_b1_pruned 2.787 7.440 97.213 92.560 13.880 34.533 86.120 65.467 26.21 6.33 224 240 0.875 0.882 bicubic -76.279 -85.330 -80.576 -63.507 -28 +21
147 dpn68b wide_resnet101_2 2.707 7.360 97.293 92.640 12.640 34.147 87.360 65.853 12.61 126.89 224 0.875 bicubic bilinear -74.807 -86.360 -81.182 -64.393 +21 -25
148 selecsls60b regnetx_064 2.693 7.333 97.307 92.667 13.173 34.373 86.827 65.627 32.77 26.21 224 0.875 bicubic -75.725 -86.557 -80.993 -64.257 -5 -36
149 tf_efficientnet_cc_b0_8e gluon_resnet101_v1b 2.680 7.227 97.320 92.773 12.773 32.773 87.227 67.227 24.01 44.55 224 0.875 bicubic -75.228 -86.523 -80.883 -65.607 +10 -29
150 dla60_res2net efficientnet_b0 2.640 7.213 97.360 92.787 14.200 34.013 85.800 65.987 21.15 5.29 224 0.875 bilinear bicubic -75.832 -85.477 -80.004 -64.057 -11 +23
151 gluon_resnet101_v1b gluon_resnet50_v1s 2.627 7.213 97.373 92.787 13.573 33.507 86.427 66.493 44.55 25.68 224 0.875 bicubic -76.677 -86.407 -80.951 -64.953 -44 -24
152 dla60x tf_mixnet_l 2.613 7.147 97.387 92.853 13.333 31.613 86.667 68.387 17.65 7.33 224 0.875 bilinear bicubic -75.629 -86.163 -80.689 -66.417 -6 -7
153 mixnet_m tf_efficientnet_b1 2.547 7.133 97.453 92.867 12.427 33.040 87.573 66.960 5.01 7.79 224 240 0.875 0.882 bicubic -74.709 -86.367 -80.991 -65.320 +25 -20
154 skresnet34 tf_efficientnet_cc_b0_8e 2.520 7.120 97.480 92.880 12.773 31.787 87.227 68.213 22.28 24.01 224 0.875 bicubic -74.390 -85.710 -80.543 -66.393 +31 +10
155 efficientnet_es ese_vovnet19b_dw 2.373 6.733 97.627 93.267 13.880 33.413 86.120 66.587 5.44 6.54 224 0.875 bicubic -75.681 -85.557 -80.050 -64.677 -3 +32
156 resnet152 selecsls60b 2.360 6.733 97.640 93.267 12.200 33.267 87.800 66.733 60.19 32.77 224 0.875 bilinear bicubic -75.952 -86.567 -81.846 -65.013 -11 -9
157 regnetx_080 efficientnet_es 2.347 6.707 97.653 93.293 12.693 33.840 87.307 66.160 39.57 5.44 224 0.875 bicubic -76.851 -86.433 -81.865 -64.580 -43 -4
158 swsl_resnet18 res2net50_26w_6s 2.333 6.693 97.667 93.307 11.213 31.653 88.787 68.347 11.69 37.05 224 0.875 bilinear -70.953 -86.717 -80.519 -66.627 +64 -18
159 wide_resnet50_2 mixnet_m 2.320 6.627 97.680 93.373 11.800 32.053 88.200 67.947 68.88 5.01 224 0.875 bilinear bicubic -76.148 -85.803 -82.286 -65.817 -19 +23
160 seresnext26_32x4d skresnet34 2.293 6.480 97.707 93.520 12.440 31.547 87.560 68.453 16.79 22.28 224 0.875 bicubic -74.807 -85.910 -80.870 -66.603 +20 +24
161 hrnet_w18 dla60x 2.267 6.427 97.733 93.573 11.853 34.080 88.147 65.920 21.30 17.35 224 0.875 bilinear -74.489 -86.693 -81.589 -64.430 +26 -7
162 dla102 regnetx_080 2.253 6.307 97.747 93.693 12.120 32.320 87.880 67.680 33.73 39.57 224 0.875 bilinear bicubic -75.773 -87.563 -81.830 -66.200 -9 -49
163 resnet50 swsl_resnet18 2.227 6.240 97.773 93.760 11.333 31.600 88.667 68.400 25.56 11.69 224 0.875 bicubic bilinear -76.805 -84.450 -83.051 -66.100 -43 +57
164 regnety_016 resnet152 2.173 6.040 97.827 93.960 11.440 32.053 88.560 67.947 11.20 60.19 224 0.875 bicubic bilinear -75.679 -87.260 -82.276 -66.337 -3 -18
165 regnetx_040 wide_resnet50_2 2.160 6.000 97.840 94.000 11.800 32.147 88.200 67.853 22.12 68.88 224 0.875 bicubic bilinear -76.326 -87.170 -82.442 -66.203 -28 -13
166 resnest14d regnetx_040 2.147 5.973 97.853 94.027 10.400 31.547 89.600 68.453 10.61 22.12 224 0.875 bilinear bicubic -73.357 -87.587 -82.114 -66.993 +36 -38
167 selecsls60 tf_efficientnet_cc_b0_4e 2.080 5.973 97.920 94.027 12.840 29.600 87.160 70.400 30.67 13.31 224 0.875 bicubic -75.902 -86.617 -80.992 -68.480 -10 +9
168 tf_efficientnet_cc_b0_4e resnet50 2.080 5.933 97.920 94.067 10.973 29.093 89.027 70.907 13.31 25.56 224 0.875 bicubic -75.224 -87.877 -82.359 -69.297 +6 -51
169 res2next50 dla102 2.067 5.880 97.933 94.120 11.453 32.707 88.547 67.293 24.67 33.27 224 0.875 bilinear -76.175 -87.180 -82.439 -65.833 -21 -12
170 seresnet50 regnety_016 2.067 5.680 97.933 94.320 12.267 30.413 87.733 69.587 28.09 11.20 224 0.875 bilinear bicubic -75.569 -87.350 -81.485 -67.947 -7 -11
171 densenet161 selecsls60 1.973 5.653 98.027 94.347 10.587 32.507 89.413 67.493 28.68 30.67 224 0.875 bicubic -75.375 -87.377 -83.061 -65.793 +2 -10
172 tf_efficientnet_b0_ap res2next50 1.960 5.627 98.040 94.373 10.800 30.867 89.200 69.133 5.29 24.67 224 0.875 bicubic bilinear -75.124 -87.213 -82.454 -67.313 +9 -9
173 regnetx_032 tf_efficientnet_em 1.920 5.520 98.080 94.480 10.947 32.173 89.053 67.827 15.30 6.90 224 240 0.875 0.882 bicubic -76.246 -87.960 -83.133 -66.267 -23 -38
174 tf_efficientnet_em hrnet_w18 1.813 5.493 98.187 94.507 11.627 30.960 88.373 69.040 6.90 21.30 240 224 0.882 0.875 bicubic bilinear -76.885 -86.827 -82.693 -67.280 -42 +12
175 tf_mixnet_m resnest14d 1.813 5.480 98.187 94.520 10.547 28.547 89.453 71.453 5.01 10.61 224 0.875 bicubic bilinear -75.137 -86.240 -82.609 -69.323 +8 +26
176 tf_efficientnet_lite2 1.800 5.360 98.200 94.640 11.147 30.907 88.853 69.093 6.09 260 0.890 bicubic -75.660 -87.290 -82.599 -67.323 -6 -2
177 res2net50_14w_8s tf_efficientnet_b0_ap 1.787 5.307 98.213 94.693 10.347 28.813 89.653 71.187 25.06 5.29 224 0.875 bilinear bicubic -76.365 -86.893 -83.495 -69.207 -26 +14
178 res2net50_26w_4s densenet121 1.773 5.293 98.227 94.707 10.440 29.907 89.560 70.093 25.70 7.98 224 0.875 bilinear bicubic -76.173 -86.277 -83.412 -68.123 -20 +24
179 mobilenetv3_large_100 res2net50_26w_4s 1.760 5.160 98.240 94.840 10.293 29.360 89.707 70.640 5.48 25.70 224 0.875 bicubic bilinear -74.008 -87.340 -82.247 -68.700 +18 +2
180 densenet121 tf_mixnet_m 1.733 5.080 98.267 94.920 10.853 28.147 89.147 71.853 7.98 5.01 224 0.875 bicubic -73.841 -87.250 -81.803 -69.743 +20 +5
181 tf_efficientnet_b0 mobilenetv3_large_100 1.693 5.067 98.307 94.933 9.733 28.187 90.267 71.813 5.29 5.48 224 0.875 bicubic -75.147 -86.253 -83.493 -69.523 +5 +24
182 tv_resnext50_32x4d tf_efficientnet_b0 1.680 5.067 98.320 94.933 10.600 28.800 89.400 71.200 25.03 5.29 224 0.875 bilinear bicubic -75.938 -87.183 -83.098 -69.200 -18 +7
183 mobilenetv3_rw res2net50_14w_8s 1.667 5.040 98.333 94.960 10.733 28.773 89.267 71.227 5.48 25.06 224 0.875 bicubic bilinear -73.961 -87.700 -81.977 -69.407 +16 -14
184 resnet101 mixnet_s 1.667 4.907 98.333 95.093 9.813 28.573 90.187 71.427 44.55 4.13 224 0.875 bilinear bicubic -75.707 -86.923 -83.733 -69.287 -12 +15
185 mobilenetv2_120d mobilenetv3_rw 1.640 4.907 98.360 95.093 10.453 29.853 89.547 70.147 5.83 5.48 224 0.875 bicubic -75.654 -86.303 -83.049 -67.807 -10 +23
186 mixnet_s gluon_resnet50_v1c 1.587 4.893 98.413 95.107 10.253 28.147 89.747 71.853 4.13 25.58 224 0.875 bicubic -74.401 -88.137 -82.541 -70.243 +9 -28
187 densenet201 regnetx_032 1.547 4.853 98.453 95.147 9.627 30.280 90.373 69.720 20.01 15.30 224 0.875 bicubic -75.743 -88.267 -83.851 -68.110 -11 -32
188 gluon_resnet50_v1c tv_resnext50_32x4d 1.547 4.840 98.453 95.160 10.613 30.307 89.387 69.693 25.58 25.03 224 0.875 bicubic bilinear -76.463 -87.900 -83.375 -67.963 -34 -18
189 semnasnet_100 resnet101 1.547 4.707 98.453 95.293 9.320 29.333 90.680 70.667 3.89 44.55 224 0.875 bicubic bilinear -73.909 -88.103 -83.272 -68.917 +14 -23
190 selecsls42b densenet161 1.467 4.693 98.533 95.307 10.440 29.547 89.560 70.453 32.46 28.68 224 0.875 bicubic -75.709 -87.807 -82.952 -68.743 -11 -10
191 tf_efficientnet_lite1 selecsls42b 1.453 4.667 98.547 95.333 9.707 28.587 90.293 71.413 5.42 32.46 240 224 0.882 0.875 bicubic -75.185 -87.613 -83.525 -69.563 -2 -3
192 regnety_008 tf_efficientnet_lite1 1.427 4.613 98.573 95.387 8.947 28.387 91.053 71.613 6.26 5.42 224 240 0.875 0.882 bicubic -74.887 -88.007 -84.115 -69.693 = -17
193 ssl_resnet18 mobilenetv2_120d 1.387 4.533 98.613 95.467 8.160 29.280 91.840 70.720 11.69 5.83 224 0.875 bilinear bicubic -71.213 -87.867 -83.256 -68.770 +32 -10
194 dla60 fbnetc_100 1.347 4.133 98.653 95.867 9.467 25.933 90.533 74.067 22.33 5.57 224 0.875 bilinear -75.677 -86.567 -83.841 -71.277 -12 +25
195 dpn68 densenet201 1.347 4.120 98.653 95.880 8.813 27.547 91.187 72.453 12.61 20.01 224 0.875 bicubic -74.959 -88.630 -84.157 -70.683 -2 -27
196 res2net50_48w_2s gluon_resnet50_v1b 1.307 4.120 98.693 95.880 8.920 26.933 91.080 73.067 25.29 25.56 224 0.875 bilinear bicubic -76.207 -88.420 -84.628 -71.237 -27 -17
197 tf_mixnet_s resnet26d 1.280 4.040 98.720 95.960 8.747 28.520 91.253 71.480 4.13 16.01 224 0.875 bicubic -74.368 -88.030 -83.889 -69.440 +1 -4
198 mobilenetv2_140 semnasnet_100 1.253 3.960 98.747 96.040 9.107 26.947 90.893 73.053 6.11 3.89 224 0.875 bicubic -75.271 -87.320 -83.883 -70.613 -7 +8
199 fbnetc_100 tf_mixnet_s 1.227 3.880 98.773 96.120 8.747 25.253 91.253 74.747 5.57 4.13 224 0.875 bilinear bicubic -73.893 -87.630 -83.639 -72.367 +8 +4
200 resnet26d dpn68 1.227 3.867 98.773 96.133 9.280 26.080 90.720 73.920 16.01 12.61 224 0.875 bicubic -75.453 -88.143 -83.886 -71.970 -12 -6
201 densenet169 regnety_008 1.187 3.813 98.813 96.187 8.320 27.133 91.680 72.867 14.15 6.26 224 0.875 bicubic -74.725 -87.937 -84.704 -71.047 -5 -1
202 tf_mobilenetv3_large_100 dla60 1.187 3.773 98.813 96.227 7.947 27.933 92.053 72.067 5.48 22.04 224 0.875 bilinear -74.329 -88.457 -84.653 -70.177 -1 -12
203 gluon_resnet50_v1b ssl_resnet18 1.160 3.747 98.840 96.253 9.027 25.427 90.973 74.573 25.56 11.69 224 0.875 bicubic bilinear -76.418 -86.473 -84.691 -72.123 -36 +22
204 seresnet34 mobilenetv2_140 1.120 3.720 98.880 96.280 7.400 26.747 92.600 73.253 21.96 6.11 224 0.875 bilinear bicubic -73.688 -88.110 -84.726 -70.943 +8 -6
205 tf_efficientnet_es densenet169 1.120 3.707 98.880 96.293 8.600 25.613 91.400 74.387 5.44 14.15 224 0.875 bicubic -76.144 -88.223 -85.000 -72.487 -28 -10
206 spnasnet_100 regnetx_016 1.107 3.627 98.893 96.373 8.253 26.293 91.747 73.707 4.42 9.19 224 0.875 bilinear bicubic -72.973 -88.543 -83.579 -71.917 +11 -14
207 tf_efficientnet_lite0 res2net50_48w_2s 1.107 3.587 98.893 96.413 7.493 26.613 92.507 73.387 4.65 25.29 224 0.875 bicubic bilinear -73.735 -88.963 -84.677 -71.467 +4 -30
208 regnetx_016 spnasnet_100 1.093 3.547 98.907 96.453 8.627 24.293 91.373 75.707 9.19 4.42 224 0.875 bicubic bilinear -75.837 -86.803 -84.791 -72.897 -24 +16
209 dla34 tf_mobilenetv3_large_100 1.080 3.547 98.920 96.453 7.693 25.053 92.307 74.947 15.78 5.48 224 0.875 bilinear -73.556 -87.693 -84.371 -72.607 +6 -2
210 regnety_006 1.053 3.467 98.947 96.533 8.400 24.893 91.600 75.107 6.06 224 0.875 bicubic -74.207 -87.903 -84.128 -72.817 -5 -6
211 regnety_004 tf_efficientnet_es 1.013 3.427 98.987 96.573 7.333 27.493 92.667 72.507 4.34 5.44 224 0.875 bicubic -73.013 -89.123 -84.415 -70.787 +7 -33
212 resnet34 efficientnet_lite0 0.987 3.253 99.013 96.747 7.533 25.867 92.467 74.133 21.80 4.65 224 0.875 bilinear bicubic -74.125 -87.887 -84.755 -71.763 -4 -2
213 mobilenetv2_110d dla34 0.933 3.227 99.067 96.773 8.107 23.573 91.893 76.427 4.52 15.74 224 0.875 bicubic bilinear -74.119 -87.533 -84.073 -74.087 -4 +5
214 gluon_resnet34_v1b regnety_004 0.893 3.200 99.107 96.800 6.600 22.653 93.400 77.347 21.80 4.34 224 0.875 bicubic -73.687 -87.300 -85.388 -74.887 +2 +8
215 hrnet_w18_small_v2 mobilenetv2_110d 0.893 3.173 99.107 96.827 7.387 24.587 92.613 75.413 15.60 4.52 224 0.875 bilinear bicubic -74.233 -87.777 -85.029 -72.963 -9 +1
216 regnetx_008 mnasnet_100 0.893 3.120 99.107 96.880 6.907 24.227 93.093 75.773 7.26 4.38 224 0.875 bicubic -74.129 -87.390 -85.437 -73.243 -6 +5
217 skresnet18 tf_efficientnet_lite0 0.880 3.080 99.120 96.920 7.387 22.907 92.613 77.093 11.96 4.65 224 0.875 bicubic -72.164 -87.960 -83.791 -74.683 +6 -3
218 mnasnet_100 skresnet18 0.867 3.013 99.133 96.987 7.867 22.800 92.133 77.200 4.38 11.96 224 0.875 bicubic -73.789 -86.647 -84.259 -74.430 -4 +10
219 tf_mobilenetv3_large_075 resnet34 0.867 2.920 99.133 97.080 6.720 23.680 93.280 76.320 3.99 21.80 224 0.875 bilinear -72.575 -88.210 -84.632 -73.940 +1 -8
220 regnetx_006 tf_mobilenetv3_large_075 0.760 2.867 99.240 97.133 6.493 21.573 93.507 78.427 6.20 3.99 224 0.875 bicubic bilinear -73.102 -86.813 -85.187 -75.637 -1 +7
221 tf_mobilenetv3_small_100 hrnet_w18_small_v2 0.747 2.720 99.253 97.280 4.667 23.693 95.333 76.307 2.54 15.60 224 0.875 bilinear -67.171 -88.470 -82.995 -74.207 +13 -12
222 seresnet18 gluon_resnet34_v1b 0.720 2.667 99.280 97.333 6.027 21.680 93.973 78.320 11.78 21.80 224 0.875 bicubic -71.038 -88.293 -84.307 -75.950 +7 -7
223 regnetx_004 regnetx_008 0.693 2.653 99.307 97.347 5.507 22.453 94.493 77.547 5.16 7.26 224 0.875 bicubic -71.713 -88.397 -85.323 -75.257 +3 -10
224 tv_densenet121 0.680 2.560 99.320 97.440 6.907 22.667 93.093 77.333 7.98 224 0.875 bicubic -74.072 -88.330 -85.245 -75.043 -11 -7
225 regnety_002 regnetx_006 0.667 2.507 99.333 97.493 5.533 20.653 94.467 79.347 3.16 6.20 224 0.875 bicubic -69.615 -87.843 -84.007 -76.777 +6 -2
226 tf_mobilenetv3_small_075 resnet26 0.627 2.480 99.373 97.520 4.173 22.987 95.827 77.013 2.04 16.00 224 0.875 bilinear bicubic -65.091 -88.630 -81.963 -74.753 +11 -14
227 resnet26 regnety_002 0.600 2.147 99.400 97.853 6.880 18.880 93.120 81.120 16.00 3.16 224 0.875 bicubic -74.692 -85.233 -85.690 -77.710 -23 +7
228 tv_resnet34 mobilenetv2_100 0.600 2.147 99.400 97.853 5.520 19.907 94.480 80.093 21.80 3.50 224 0.875 bilinear bicubic -72.714 -87.453 -85.900 -77.233 -7 +2
229 mobilenetv2_100 tf_mobilenetv3_small_100 0.533 2.013 99.467 97.987 6.187 15.867 93.813 84.133 3.50 2.54 224 0.875 bicubic bilinear -72.445 -83.177 -84.829 -79.903 -5 +9
230 dla46_c tf_mobilenetv3_small_075 0.520 2.000 99.480 98.000 4.187 14.813 95.813 85.187 1.31 2.04 224 0.875 bilinear -64.358 -81.520 -82.099 -79.977 +8 +11
231 tf_mobilenetv3_large_minimal_100 regnetx_004 0.480 1.960 99.520 98.040 4.880 19.173 95.120 80.827 3.92 5.16 224 0.875 bilinear bicubic -71.764 -86.940 -85.756 -77.947 -3 +1
232 dla60x_c tv_resnet34 0.467 1.867 99.533 98.133 5.213 20.000 94.787 80.000 1.34 21.80 224 0.875 bilinear -67.441 -88.073 -83.221 -77.340 +3 -6
233 hrnet_w18_small dla46x_c 0.453 1.760 99.547 98.240 4.840 16.480 95.160 83.520 13.19 1.07 224 0.875 bilinear -71.889 -82.490 -85.832 -78.790 -6 +6
234 dla46x_c tf_mobilenetv3_large_minimal_100 0.413 1.627 99.587 98.373 4.440 17.120 95.560 82.880 1.08 3.92 224 0.875 bilinear -65.567 -87.343 -82.540 -79.740 +2 -3
235 gluon_resnet18_v1b dla60x_c 0.387 1.613 99.613 98.387 4.787 18.040 95.213 81.960 11.69 1.32 224 0.875 bicubic bilinear -70.443 -84.677 -84.969 -78.120 -5 +1
236 tf_mobilenetv3_small_minimal_100 gluon_resnet18_v1b 0.360 1.547 99.640 98.453 2.867 16.613 97.133 83.387 2.04 11.69 224 0.875 bilinear bicubic -62.538 -86.853 -81.363 -80.067 +3 -3
237 resnet18 hrnet_w18_small 0.293 1.533 99.707 98.467 4.040 18.120 95.960 81.880 11.69 13.19 224 0.875 bilinear -69.465 -87.517 -85.038 -78.990 -5 -7
238 regnetx_002 dla46_c 0.227 1.520 99.773 98.480 3.987 15.267 96.013 84.733 2.68 1.30 224 0.875 bicubic bilinear -68.527 -82.130 -84.561 -79.653 -5 +2
239 tv_resnet50 regnetx_002 0.000 1.373 100.000 98.627 2.893 15.027 97.107 84.973 25.56 2.68 224 0.875 bilinear bicubic -76.130 -84.817 -89.969 -80.953 -45 -2
240 resnet18 1.160 98.840 16.213 83.787 11.69 224 0.875 bilinear -86.230 -80.077 -6
241 tf_mobilenetv3_small_minimal_100 1.013 98.987 11.493 88.507 2.04 224 0.875 bilinear -80.367 -82.177 +1
242 tv_resnet50 0.000 100.000 14.453 85.547 25.56 224 0.875 bilinear -91.880 -83.587 -45

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model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation
tf_efficientnet_l2_ns,97.780,2.220,99.890,0.110,480.31,800,0.960,bicubic
tf_efficientnet_l2_ns_475,97.750,2.250,99.820,0.180,480.31,475,0.936,bicubic
tf_efficientnet_b7_ns,97.200,2.800,99.700,0.300,66.35,600,0.949,bicubic
tf_efficientnet_b6_ns,97.020,2.980,99.710,0.290,43.04,528,0.942,bicubic
ig_resnext101_32x48d,96.970,3.030,99.670,0.330,828.41,224,0.875,bilinear
tf_efficientnet_b5_ns,96.870,3.130,99.640,0.360,30.39,456,0.934,bicubic
ig_resnext101_32x32d,96.780,3.220,99.530,0.470,468.53,224,0.875,bilinear
tf_efficientnet_b4_ns,96.710,3.290,99.640,0.360,19.34,380,0.922,bicubic
tf_efficientnet_b8,96.700,3.300,99.530,0.470,87.41,672,0.954,bicubic
tf_efficientnet_b7,96.580,3.420,99.510,0.490,66.35,600,0.949,bicubic
tf_efficientnet_b8_ap,96.550,3.450,99.540,0.460,87.41,672,0.954,bicubic
ig_resnext101_32x16d,96.440,3.560,99.540,0.460,194.03,224,0.875,bilinear
tf_efficientnet_b6_ap,96.370,3.630,99.550,0.450,43.04,528,0.942,bicubic
tf_efficientnet_b7_ap,96.350,3.650,99.590,0.410,66.35,600,0.949,bicubic
tf_efficientnet_b6,96.290,3.710,99.520,0.480,43.04,528,0.942,bicubic
swsl_resnext101_32x16d,96.270,3.730,99.500,0.500,194.03,224,0.875,bilinear
swsl_resnext101_32x8d,96.240,3.760,99.590,0.410,88.79,224,0.875,bilinear
resnest269e,96.120,3.880,99.520,0.480,110.93,416,0.928,bicubic
tf_efficientnet_b3_ns,96.100,3.900,99.480,0.520,12.23,300,0.904,bicubic
tf_efficientnet_b5_ap,96.080,3.920,99.540,0.460,30.39,456,0.934,bicubic
resnest200e,96.070,3.930,99.480,0.520,70.20,320,0.909,bicubic
swsl_resnext101_32x4d,96.050,3.950,99.530,0.470,44.18,224,0.875,bilinear
tf_efficientnet_b5,95.980,4.020,99.450,0.550,30.39,456,0.934,bicubic
ig_resnext101_32x8d,95.930,4.070,99.380,0.620,88.79,224,0.875,bilinear
swsl_resnext50_32x4d,95.620,4.380,99.440,0.560,25.03,224,0.875,bilinear
tf_efficientnet_b4,95.590,4.410,99.330,0.670,19.34,380,0.922,bicubic
resnest101e,95.570,4.430,99.270,0.730,48.28,256,0.875,bilinear
tf_efficientnet_b2_ns,95.520,4.480,99.340,0.660,9.11,260,0.890,bicubic
tresnet_xl_448,95.510,4.490,99.340,0.660,78.44,448,0.875,bilinear
tf_efficientnet_b4_ap,95.490,4.510,99.390,0.610,19.34,380,0.922,bicubic
tresnet_l_448,95.410,4.590,99.300,0.700,55.99,448,0.875,bilinear
ssl_resnext101_32x16d,95.410,4.590,99.410,0.590,194.03,224,0.875,bilinear
pnasnet5large,95.360,4.640,99.130,0.870,86.06,331,0.911,bicubic
ssl_resnext101_32x8d,95.340,4.660,99.320,0.680,88.79,224,0.875,bilinear
swsl_resnet50,95.200,4.800,99.390,0.610,25.56,224,0.875,bilinear
ecaresnet101d,95.160,4.840,99.230,0.770,44.57,224,0.875,bicubic
ssl_resnext101_32x4d,95.160,4.840,99.300,0.700,44.18,224,0.875,bilinear
nasnetalarge,95.150,4.850,99.130,0.870,88.75,331,0.911,bicubic
efficientnet_b3a,95.120,4.880,99.120,0.880,12.23,320,1.000,bicubic
tresnet_xl,95.060,4.940,99.260,0.740,78.44,224,0.875,bilinear
tf_efficientnet_b3_ap,94.970,5.030,99.110,0.890,12.23,300,0.904,bicubic
efficientnet_b3,94.960,5.040,99.200,0.800,12.23,300,0.904,bicubic
tf_efficientnet_b3,94.910,5.090,99.110,0.890,12.23,300,0.904,bicubic
tresnet_l,94.900,5.100,99.030,0.970,55.99,224,0.875,bilinear
tf_efficientnet_lite4,94.870,5.130,99.090,0.910,13.01,380,0.920,bilinear
tf_efficientnet_b1_ns,94.860,5.140,99.250,0.750,7.79,240,0.882,bicubic
gluon_resnet152_v1s,94.720,5.280,99.060,0.940,60.32,224,0.875,bicubic
gluon_senet154,94.710,5.290,98.970,1.030,115.09,224,0.875,bicubic
resnest50d_4s2x40d,94.710,5.290,99.130,0.870,30.42,224,0.875,bicubic
ssl_resnext50_32x4d,94.700,5.300,99.240,0.760,25.03,224,0.875,bilinear
rexnet_200,94.660,5.340,99.090,0.910,16.37,224,0.875,bicubic
tresnet_m_448,94.660,5.340,99.150,0.850,31.39,448,0.875,bilinear
gluon_seresnext101_64x4d,94.650,5.350,98.980,1.020,88.23,224,0.875,bicubic
resnest50d,94.620,5.380,99.030,0.970,27.48,224,0.875,bilinear
efficientnet_b3_pruned,94.580,5.420,99.070,0.930,9.86,300,0.904,bicubic
regnety_320,94.520,5.480,99.170,0.830,145.05,224,0.875,bicubic
ecaresnet101d_pruned,94.450,5.550,99.100,0.900,24.88,224,0.875,bicubic
gluon_seresnext101_32x4d,94.450,5.550,99.090,0.910,48.96,224,0.875,bicubic
tf_efficientnet_el,94.450,5.550,99.080,0.920,10.59,300,0.904,bicubic
gluon_resnet152_v1d,94.440,5.560,99.010,0.990,60.21,224,0.875,bicubic
resnest50d_1s4x24d,94.390,5.610,99.070,0.930,25.68,224,0.875,bicubic
inception_v4,94.380,5.620,98.820,1.180,42.68,299,0.875,bicubic
efficientnet_b2a,94.370,5.630,99.050,0.950,9.11,288,1.000,bicubic
gluon_resnext101_64x4d,94.350,5.650,98.880,1.120,83.46,224,0.875,bicubic
efficientnet_b2,94.340,5.660,99.100,0.900,9.11,260,0.875,bicubic
inception_resnet_v2,94.340,5.660,98.800,1.200,55.84,299,0.897,bicubic
ssl_resnet50,94.310,5.690,99.150,0.850,25.56,224,0.875,bilinear
regnetx_120,94.270,5.730,99.190,0.810,46.11,224,0.875,bicubic
rexnet_150,94.270,5.730,99.080,0.920,9.73,224,0.875,bicubic
tf_efficientnet_b2_ap,94.270,5.730,98.950,1.050,9.11,260,0.890,bicubic
mixnet_xl,94.230,5.770,98.820,1.180,11.90,224,0.875,bicubic
regnetx_320,94.210,5.790,99.050,0.950,107.81,224,0.875,bicubic
tf_efficientnet_b2,94.210,5.790,99.030,0.970,9.11,260,0.890,bicubic
dpn92,94.190,5.810,98.930,1.070,37.67,224,0.875,bicubic
ecaresnet50d,94.190,5.810,99.020,0.980,25.58,224,0.875,bicubic
gluon_seresnext50_32x4d,94.170,5.830,98.910,1.090,27.56,224,0.875,bicubic
gluon_resnet101_v1d,94.170,5.830,98.940,1.060,44.57,224,0.875,bicubic
gluon_resnet101_v1s,94.170,5.830,99.010,0.990,44.67,224,0.875,bicubic
ecaresnetlight,94.140,5.860,98.950,1.050,30.16,224,0.875,bicubic
regnety_064,94.140,5.860,99.030,0.970,30.58,224,0.875,bicubic
ens_adv_inception_resnet_v2,94.130,5.870,98.790,1.210,55.84,299,0.897,bicubic
tf_efficientnet_lite3,94.130,5.870,98.960,1.040,8.20,300,0.904,bilinear
gluon_resnext101_32x4d,94.120,5.880,98.930,1.070,44.18,224,0.875,bicubic
regnety_160,94.120,5.880,99.020,0.980,83.59,224,0.875,bicubic
cspdarknet53,94.090,5.910,98.980,1.020,27.64,256,0.887,bilinear
seresnet50,94.080,5.920,98.970,1.030,28.09,224,0.875,bicubic
tresnet_m,94.070,5.930,98.830,1.170,31.39,224,0.875,bilinear
gluon_resnet152_v1b,94.030,5.970,98.740,1.260,60.19,224,0.875,bicubic
hrnet_w48,94.030,5.970,99.040,0.960,77.47,224,0.875,bilinear
regnety_120,94.010,5.990,99.030,0.970,51.82,224,0.875,bicubic
gluon_xception65,94.010,5.990,99.020,0.980,39.92,299,0.903,bicubic
dla102x2,94.000,6.000,99.030,0.970,41.28,224,0.875,bilinear
dpn107,93.960,6.040,98.840,1.160,86.92,224,0.875,bicubic
skresnext50_32x4d,93.950,6.050,98.820,1.180,27.48,224,0.875,bicubic
dpn98,93.940,6.060,98.920,1.080,61.57,224,0.875,bicubic
regnety_080,93.890,6.110,99.000,1.000,39.18,224,0.875,bicubic
xception71,93.890,6.110,98.950,1.050,42.34,299,0.903,bicubic
gluon_resnet152_v1c,93.880,6.120,98.800,1.200,60.21,224,0.875,bicubic
regnetx_160,93.880,6.120,99.090,0.910,54.28,224,0.875,bicubic
ese_vovnet39b,93.850,6.150,98.900,1.100,24.57,224,0.875,bicubic
resnext50_32x4d,93.840,6.160,98.830,1.170,25.03,224,0.875,bicubic
hrnet_w64,93.830,6.170,98.930,1.070,128.06,224,0.875,bilinear
ecaresnet50d_pruned,93.820,6.180,99.000,1.000,19.94,224,0.875,bicubic
resnext50d_32x4d,93.810,6.190,98.740,1.260,25.05,224,0.875,bicubic
efficientnet_b2_pruned,93.800,6.200,98.910,1.090,8.31,260,0.890,bicubic
dla169,93.800,6.200,98.840,1.160,53.39,224,0.875,bilinear
regnetx_080,93.790,6.210,98.910,1.090,39.57,224,0.875,bicubic
resnext101_32x8d,93.770,6.230,98.950,1.050,88.79,224,0.875,bilinear
cspresnext50,93.760,6.240,98.840,1.160,20.57,224,0.875,bilinear
dpn131,93.760,6.240,98.800,1.200,79.25,224,0.875,bicubic
gluon_resnet101_v1b,93.760,6.240,98.700,1.300,44.55,224,0.875,bicubic
xception65,93.760,6.240,98.860,1.140,39.92,299,0.903,bicubic
tf_efficientnet_b0_ns,93.740,6.260,98.980,1.020,5.29,224,0.875,bicubic
wide_resnet101_2,93.730,6.270,98.810,1.190,126.89,224,0.875,bilinear
hrnet_w40,93.710,6.290,98.800,1.200,57.56,224,0.875,bilinear
resnetblur50,93.710,6.290,98.810,1.190,25.56,224,0.875,bicubic
tf_efficientnet_b1,93.710,6.290,98.800,1.200,7.79,240,0.882,bicubic
gluon_resnet101_v1c,93.690,6.310,98.760,1.240,44.57,224,0.875,bicubic
regnetx_040,93.680,6.320,98.940,1.060,22.12,224,0.875,bicubic
rexnet_130,93.670,6.330,98.710,1.290,7.56,224,0.875,bicubic
gluon_resnext50_32x4d,93.650,6.350,98.690,1.310,25.03,224,0.875,bicubic
xception,93.640,6.360,98.770,1.230,22.86,299,0.897,bicubic
regnetx_064,93.630,6.370,99.050,0.950,26.21,224,0.875,bicubic
tf_efficientnet_b1_ap,93.630,6.370,98.800,1.200,7.79,240,0.882,bicubic
dpn68b,93.620,6.380,98.700,1.300,12.61,224,0.875,bicubic
hrnet_w44,93.620,6.380,98.960,1.040,67.06,224,0.875,bilinear
regnety_040,93.620,6.380,98.950,1.050,20.65,224,0.875,bicubic
gluon_resnet50_v1s,93.590,6.410,98.840,1.160,25.68,224,0.875,bicubic
res2net50_26w_6s,93.590,6.410,98.750,1.250,37.05,224,0.875,bilinear
dla60_res2next,93.570,6.430,98.800,1.200,17.03,224,0.875,bilinear
tf_efficientnet_cc_b1_8e,93.570,6.430,98.690,1.310,39.72,240,0.882,bicubic
gluon_inception_v3,93.540,6.460,98.830,1.170,23.83,299,0.875,bicubic
dla102x,93.530,6.470,98.850,1.150,26.31,224,0.875,bilinear
gluon_resnet50_v1d,93.530,6.470,98.710,1.290,25.58,224,0.875,bicubic
res2net101_26w_4s,93.520,6.480,98.600,1.400,45.21,224,0.875,bilinear
selecsls60b,93.500,6.500,98.840,1.160,32.77,224,0.875,bicubic
xception41,93.480,6.520,98.750,1.250,26.97,299,0.903,bicubic
tf_efficientnet_em,93.470,6.530,98.750,1.250,6.90,240,0.882,bicubic
regnety_032,93.460,6.540,98.950,1.050,19.44,224,0.875,bicubic
resnet50,93.460,6.540,98.600,1.400,25.56,224,0.875,bicubic
wide_resnet50_2,93.460,6.540,98.950,1.050,68.88,224,0.875,bilinear
res2net50_26w_8s,93.450,6.550,98.700,1.300,48.40,224,0.875,bilinear
dla60_res2net,93.380,6.620,98.860,1.140,20.85,224,0.875,bilinear
hrnet_w30,93.370,6.630,98.830,1.170,37.71,224,0.875,bilinear
dla102,93.260,6.740,98.780,1.220,33.27,224,0.875,bilinear
mixnet_l,93.260,6.740,98.700,1.300,7.33,224,0.875,bicubic
regnetx_032,93.250,6.750,98.730,1.270,15.30,224,0.875,bicubic
resnest26d,93.240,6.760,98.850,1.150,17.07,224,0.875,bilinear
resnet152,93.240,6.760,98.750,1.250,60.19,224,0.875,bilinear
tf_inception_v3,93.200,6.800,98.480,1.520,23.83,299,0.875,bicubic
dla60x,93.190,6.810,98.710,1.290,17.35,224,0.875,bilinear
res2net50_26w_4s,93.180,6.820,98.670,1.330,25.70,224,0.875,bilinear
res2next50,93.150,6.850,98.660,1.340,24.67,224,0.875,bilinear
efficientnet_b1,93.060,6.940,98.540,1.460,7.79,240,0.875,bicubic
tf_mixnet_l,93.040,6.960,98.540,1.460,7.33,224,0.875,bicubic
res2net50_14w_8s,93.030,6.970,98.700,1.300,25.06,224,0.875,bilinear
adv_inception_v3,93.010,6.990,98.490,1.510,23.83,299,0.875,bicubic
selecsls60,93.010,6.990,98.830,1.170,30.67,224,0.875,bicubic
regnety_016,93.000,7.000,98.680,1.320,11.20,224,0.875,bicubic
efficientnet_b1_pruned,92.980,7.020,98.530,1.470,6.33,240,0.882,bicubic
seresnext26t_32x4d,92.960,7.040,98.480,1.520,16.82,224,0.875,bicubic
hrnet_w32,92.950,7.050,98.840,1.160,41.23,224,0.875,bilinear
efficientnet_es,92.910,7.090,98.690,1.310,5.44,224,0.875,bicubic
gluon_resnet50_v1c,92.910,7.090,98.710,1.290,25.58,224,0.875,bicubic
inception_v3,92.900,7.100,98.330,1.670,23.83,299,0.875,bicubic
tv_resnext50_32x4d,92.900,7.100,98.720,1.280,25.03,224,0.875,bilinear
densenet161,92.900,7.100,98.810,1.190,28.68,224,0.875,bicubic
resnet101,92.880,7.120,98.660,1.340,44.55,224,0.875,bilinear
tf_efficientnet_cc_b0_8e,92.870,7.130,98.460,1.540,24.01,224,0.875,bicubic
rexnet_100,92.850,7.150,98.620,1.380,4.80,224,0.875,bicubic
tf_efficientnet_cc_b0_4e,92.840,7.160,98.440,1.560,13.31,224,0.875,bicubic
seresnext26tn_32x4d,92.820,7.180,98.560,1.440,16.81,224,0.875,bicubic
res2net50_48w_2s,92.790,7.210,98.470,1.530,25.29,224,0.875,bilinear
hrnet_w18,92.760,7.240,98.660,1.340,21.30,224,0.875,bilinear
densenet201,92.690,7.310,98.650,1.350,20.01,224,0.875,bicubic
dla60,92.670,7.330,98.630,1.370,22.04,224,0.875,bilinear
mobilenetv2_120d,92.610,7.390,98.510,1.490,5.83,224,0.875,bicubic
tf_efficientnet_b0_ap,92.610,7.390,98.370,1.630,5.29,224,0.875,bicubic
tf_efficientnet_lite2,92.590,7.410,98.550,1.450,6.09,260,0.890,bicubic
skresnet34,92.570,7.430,98.520,1.480,22.28,224,0.875,bicubic
gluon_resnet50_v1b,92.560,7.440,98.550,1.450,25.56,224,0.875,bicubic
tf_efficientnet_es,92.550,7.450,98.510,1.490,5.44,224,0.875,bicubic
regnetx_016,92.540,7.460,98.550,1.450,9.19,224,0.875,bicubic
efficientnet_b0,92.480,7.520,98.680,1.320,5.29,224,0.875,bicubic
selecsls42b,92.480,7.520,98.440,1.560,32.46,224,0.875,bicubic
seresnext26d_32x4d,92.440,7.560,98.540,1.460,16.81,224,0.875,bicubic
densenetblur121d,92.400,7.600,98.410,1.590,8.00,224,0.875,bicubic
tf_efficientnet_b0,92.400,7.600,98.470,1.530,5.29,224,0.875,bicubic
tf_efficientnet_lite1,92.310,7.690,98.490,1.510,5.42,240,0.882,bicubic
densenet169,92.300,7.700,98.590,1.410,14.15,224,0.875,bicubic
mixnet_m,92.270,7.730,98.350,1.650,5.01,224,0.875,bicubic
dpn68,92.240,7.760,98.610,1.390,12.61,224,0.875,bicubic
resnet26d,92.230,7.770,98.450,1.550,16.01,224,0.875,bicubic
tf_mixnet_m,92.200,7.800,98.420,1.580,5.01,224,0.875,bicubic
tv_resnet50,92.140,7.860,98.420,1.580,25.56,224,0.875,bilinear
mobilenetv2_140,92.030,7.970,98.250,1.750,6.11,224,0.875,bicubic
ese_vovnet19b_dw,92.010,7.990,98.510,1.490,6.54,224,0.875,bicubic
densenet121,91.940,8.060,98.280,1.720,7.98,224,0.875,bicubic
regnety_008,91.900,8.100,98.420,1.580,6.26,224,0.875,bicubic
mixnet_s,91.780,8.220,98.300,1.700,4.13,224,0.875,bicubic
tf_mixnet_s,91.680,8.320,98.240,1.760,4.13,224,0.875,bicubic
semnasnet_100,91.660,8.340,98.270,1.730,3.89,224,0.875,bicubic
regnety_006,91.570,8.430,98.430,1.570,6.06,224,0.875,bicubic
mobilenetv3_rw,91.550,8.450,98.270,1.730,5.48,224,0.875,bicubic
mobilenetv3_large_100,91.480,8.520,98.320,1.680,5.48,224,0.875,bicubic
resnet26,91.440,8.560,98.280,1.720,16.00,224,0.875,bicubic
tf_mobilenetv3_large_100,91.420,8.580,98.260,1.740,5.48,224,0.875,bilinear
tv_densenet121,91.400,8.600,98.250,1.750,7.98,224,0.875,bicubic
mobilenetv2_110d,91.350,8.650,98.190,1.810,4.52,224,0.875,bicubic
tf_efficientnet_lite0,91.300,8.700,98.090,1.910,4.65,224,0.875,bicubic
fbnetc_100,91.270,8.730,97.830,2.170,5.57,224,0.875,bilinear
efficientnet_lite0,91.260,8.740,98.250,1.750,4.65,224,0.875,bicubic
dla34,91.240,8.760,98.180,1.820,15.74,224,0.875,bilinear
mnasnet_100,91.200,8.800,98.050,1.950,4.38,224,0.875,bicubic
resnet34,91.200,8.800,98.240,1.760,21.80,224,0.875,bilinear
regnetx_008,91.180,8.820,98.380,1.620,7.26,224,0.875,bicubic
hrnet_w18_small_v2,91.170,8.830,98.340,1.660,15.60,224,0.875,bilinear
resnest14d,91.130,8.870,98.330,1.670,10.61,224,0.875,bilinear
gluon_resnet34_v1b,91.100,8.900,98.180,1.820,21.80,224,0.875,bicubic
swsl_resnet18,91.090,8.910,98.210,1.790,11.69,224,0.875,bilinear
regnety_004,90.780,9.220,98.080,1.920,4.34,224,0.875,bicubic
regnetx_006,90.760,9.240,98.100,1.900,6.20,224,0.875,bicubic
ssl_resnet18,90.700,9.300,98.020,1.980,11.69,224,0.875,bilinear
spnasnet_100,90.610,9.390,97.950,2.050,4.42,224,0.875,bilinear
tf_mobilenetv3_large_075,90.320,9.680,97.870,2.130,3.99,224,0.875,bilinear
tv_resnet34,90.290,9.710,97.980,2.020,21.80,224,0.875,bilinear
skresnet18,90.160,9.840,97.780,2.220,11.96,224,0.875,bicubic
hrnet_w18_small,89.880,10.120,97.900,2.100,13.19,224,0.875,bilinear
mobilenetv2_100,89.830,10.170,97.830,2.170,3.50,224,0.875,bicubic
regnetx_004,89.460,10.540,97.770,2.230,5.16,224,0.875,bicubic
tf_mobilenetv3_large_minimal_100,89.180,10.820,97.320,2.680,3.92,224,0.875,bilinear
gluon_resnet18_v1b,88.660,11.340,97.100,2.900,11.69,224,0.875,bicubic
regnety_002,88.200,11.800,97.430,2.570,3.16,224,0.875,bicubic
resnet18,88.150,11.850,97.120,2.880,11.69,224,0.875,bilinear
regnetx_002,87.380,12.620,96.990,3.010,2.68,224,0.875,bicubic
dla60x_c,87.110,12.890,97.140,2.860,1.32,224,0.875,bilinear
tf_mobilenetv3_small_100,85.960,14.040,96.400,3.600,2.54,224,0.875,bilinear
dla46x_c,85.480,14.520,96.440,3.560,1.07,224,0.875,bilinear
dla46_c,84.660,15.340,96.200,3.800,1.30,224,0.875,bilinear
tf_mobilenetv3_small_075,84.530,15.470,95.890,4.110,2.04,224,0.875,bilinear
tf_mobilenetv3_small_minimal_100,82.670,17.330,95.000,5.000,2.04,224,0.875,bilinear
1 model top1 top1_err top5 top5_err param_count img_size cropt_pct interpolation
2 tf_efficientnet_l2_ns 97.780 2.220 99.890 0.110 480.31 800 0.960 bicubic
3 tf_efficientnet_l2_ns_475 97.750 2.250 99.820 0.180 480.31 475 0.936 bicubic
4 tf_efficientnet_b7_ns 97.200 2.800 99.700 0.300 66.35 600 0.949 bicubic
5 tf_efficientnet_b6_ns 97.020 2.980 99.710 0.290 43.04 528 0.942 bicubic
6 ig_resnext101_32x48d 96.970 3.030 99.670 0.330 828.41 224 0.875 bilinear
7 tf_efficientnet_b5_ns 96.870 3.130 99.640 0.360 30.39 456 0.934 bicubic
8 ig_resnext101_32x32d 96.780 3.220 99.530 0.470 468.53 224 0.875 bilinear
9 tf_efficientnet_b4_ns 96.710 3.290 99.640 0.360 19.34 380 0.922 bicubic
10 tf_efficientnet_b8 96.700 3.300 99.530 0.470 87.41 672 0.954 bicubic
11 tf_efficientnet_b7 96.580 3.420 99.510 0.490 66.35 600 0.949 bicubic
12 tf_efficientnet_b8_ap 96.550 3.450 99.540 0.460 87.41 672 0.954 bicubic
13 ig_resnext101_32x16d 96.440 3.560 99.540 0.460 194.03 224 0.875 bilinear
14 tf_efficientnet_b6_ap 96.370 3.630 99.550 0.450 43.04 528 0.942 bicubic
15 tf_efficientnet_b7_ap 96.350 3.650 99.590 0.410 66.35 600 0.949 bicubic
16 tf_efficientnet_b6 96.290 3.710 99.520 0.480 43.04 528 0.942 bicubic
17 swsl_resnext101_32x16d 96.270 3.730 99.500 0.500 194.03 224 0.875 bilinear
18 swsl_resnext101_32x8d 96.240 3.760 99.590 0.410 88.79 224 0.875 bilinear
19 resnest269e 96.120 3.880 99.520 0.480 110.93 416 0.928 bicubic
20 tf_efficientnet_b3_ns 96.100 3.900 99.480 0.520 12.23 300 0.904 bicubic
21 tf_efficientnet_b5_ap 96.080 3.920 99.540 0.460 30.39 456 0.934 bicubic
22 resnest200e 96.070 3.930 99.480 0.520 70.20 320 0.909 bicubic
23 swsl_resnext101_32x4d 96.050 3.950 99.530 0.470 44.18 224 0.875 bilinear
24 tf_efficientnet_b5 95.980 4.020 99.450 0.550 30.39 456 0.934 bicubic
25 ig_resnext101_32x8d 95.930 4.070 99.380 0.620 88.79 224 0.875 bilinear
26 swsl_resnext50_32x4d 95.620 4.380 99.440 0.560 25.03 224 0.875 bilinear
27 tf_efficientnet_b4 95.590 4.410 99.330 0.670 19.34 380 0.922 bicubic
28 resnest101e 95.570 4.430 99.270 0.730 48.28 256 0.875 bilinear
29 tf_efficientnet_b2_ns 95.520 4.480 99.340 0.660 9.11 260 0.890 bicubic
30 tresnet_xl_448 95.510 4.490 99.340 0.660 78.44 448 0.875 bilinear
31 tf_efficientnet_b4_ap 95.490 4.510 99.390 0.610 19.34 380 0.922 bicubic
32 tresnet_l_448 95.410 4.590 99.300 0.700 55.99 448 0.875 bilinear
33 ssl_resnext101_32x16d 95.410 4.590 99.410 0.590 194.03 224 0.875 bilinear
34 pnasnet5large 95.360 4.640 99.130 0.870 86.06 331 0.911 bicubic
35 ssl_resnext101_32x8d 95.340 4.660 99.320 0.680 88.79 224 0.875 bilinear
36 swsl_resnet50 95.200 4.800 99.390 0.610 25.56 224 0.875 bilinear
37 ecaresnet101d 95.160 4.840 99.230 0.770 44.57 224 0.875 bicubic
38 ssl_resnext101_32x4d 95.160 4.840 99.300 0.700 44.18 224 0.875 bilinear
39 nasnetalarge 95.150 4.850 99.130 0.870 88.75 331 0.911 bicubic
40 efficientnet_b3a 95.120 4.880 99.120 0.880 12.23 320 1.000 bicubic
41 tresnet_xl 95.060 4.940 99.260 0.740 78.44 224 0.875 bilinear
42 tf_efficientnet_b3_ap 94.970 5.030 99.110 0.890 12.23 300 0.904 bicubic
43 efficientnet_b3 94.960 5.040 99.200 0.800 12.23 300 0.904 bicubic
44 tf_efficientnet_b3 94.910 5.090 99.110 0.890 12.23 300 0.904 bicubic
45 tresnet_l 94.900 5.100 99.030 0.970 55.99 224 0.875 bilinear
46 tf_efficientnet_lite4 94.870 5.130 99.090 0.910 13.01 380 0.920 bilinear
47 tf_efficientnet_b1_ns 94.860 5.140 99.250 0.750 7.79 240 0.882 bicubic
48 gluon_resnet152_v1s 94.720 5.280 99.060 0.940 60.32 224 0.875 bicubic
49 gluon_senet154 94.710 5.290 98.970 1.030 115.09 224 0.875 bicubic
50 resnest50d_4s2x40d 94.710 5.290 99.130 0.870 30.42 224 0.875 bicubic
51 ssl_resnext50_32x4d 94.700 5.300 99.240 0.760 25.03 224 0.875 bilinear
52 rexnet_200 94.660 5.340 99.090 0.910 16.37 224 0.875 bicubic
53 tresnet_m_448 94.660 5.340 99.150 0.850 31.39 448 0.875 bilinear
54 gluon_seresnext101_64x4d 94.650 5.350 98.980 1.020 88.23 224 0.875 bicubic
55 resnest50d 94.620 5.380 99.030 0.970 27.48 224 0.875 bilinear
56 efficientnet_b3_pruned 94.580 5.420 99.070 0.930 9.86 300 0.904 bicubic
57 regnety_320 94.520 5.480 99.170 0.830 145.05 224 0.875 bicubic
58 ecaresnet101d_pruned 94.450 5.550 99.100 0.900 24.88 224 0.875 bicubic
59 gluon_seresnext101_32x4d 94.450 5.550 99.090 0.910 48.96 224 0.875 bicubic
60 tf_efficientnet_el 94.450 5.550 99.080 0.920 10.59 300 0.904 bicubic
61 gluon_resnet152_v1d 94.440 5.560 99.010 0.990 60.21 224 0.875 bicubic
62 resnest50d_1s4x24d 94.390 5.610 99.070 0.930 25.68 224 0.875 bicubic
63 inception_v4 94.380 5.620 98.820 1.180 42.68 299 0.875 bicubic
64 efficientnet_b2a 94.370 5.630 99.050 0.950 9.11 288 1.000 bicubic
65 gluon_resnext101_64x4d 94.350 5.650 98.880 1.120 83.46 224 0.875 bicubic
66 efficientnet_b2 94.340 5.660 99.100 0.900 9.11 260 0.875 bicubic
67 inception_resnet_v2 94.340 5.660 98.800 1.200 55.84 299 0.897 bicubic
68 ssl_resnet50 94.310 5.690 99.150 0.850 25.56 224 0.875 bilinear
69 regnetx_120 94.270 5.730 99.190 0.810 46.11 224 0.875 bicubic
70 rexnet_150 94.270 5.730 99.080 0.920 9.73 224 0.875 bicubic
71 tf_efficientnet_b2_ap 94.270 5.730 98.950 1.050 9.11 260 0.890 bicubic
72 mixnet_xl 94.230 5.770 98.820 1.180 11.90 224 0.875 bicubic
73 regnetx_320 94.210 5.790 99.050 0.950 107.81 224 0.875 bicubic
74 tf_efficientnet_b2 94.210 5.790 99.030 0.970 9.11 260 0.890 bicubic
75 dpn92 94.190 5.810 98.930 1.070 37.67 224 0.875 bicubic
76 ecaresnet50d 94.190 5.810 99.020 0.980 25.58 224 0.875 bicubic
77 gluon_seresnext50_32x4d 94.170 5.830 98.910 1.090 27.56 224 0.875 bicubic
78 gluon_resnet101_v1d 94.170 5.830 98.940 1.060 44.57 224 0.875 bicubic
79 gluon_resnet101_v1s 94.170 5.830 99.010 0.990 44.67 224 0.875 bicubic
80 ecaresnetlight 94.140 5.860 98.950 1.050 30.16 224 0.875 bicubic
81 regnety_064 94.140 5.860 99.030 0.970 30.58 224 0.875 bicubic
82 ens_adv_inception_resnet_v2 94.130 5.870 98.790 1.210 55.84 299 0.897 bicubic
83 tf_efficientnet_lite3 94.130 5.870 98.960 1.040 8.20 300 0.904 bilinear
84 gluon_resnext101_32x4d 94.120 5.880 98.930 1.070 44.18 224 0.875 bicubic
85 regnety_160 94.120 5.880 99.020 0.980 83.59 224 0.875 bicubic
86 cspdarknet53 94.090 5.910 98.980 1.020 27.64 256 0.887 bilinear
87 seresnet50 94.080 5.920 98.970 1.030 28.09 224 0.875 bicubic
88 tresnet_m 94.070 5.930 98.830 1.170 31.39 224 0.875 bilinear
89 gluon_resnet152_v1b 94.030 5.970 98.740 1.260 60.19 224 0.875 bicubic
90 hrnet_w48 94.030 5.970 99.040 0.960 77.47 224 0.875 bilinear
91 regnety_120 94.010 5.990 99.030 0.970 51.82 224 0.875 bicubic
92 gluon_xception65 94.010 5.990 99.020 0.980 39.92 299 0.903 bicubic
93 dla102x2 94.000 6.000 99.030 0.970 41.28 224 0.875 bilinear
94 dpn107 93.960 6.040 98.840 1.160 86.92 224 0.875 bicubic
95 skresnext50_32x4d 93.950 6.050 98.820 1.180 27.48 224 0.875 bicubic
96 dpn98 93.940 6.060 98.920 1.080 61.57 224 0.875 bicubic
97 regnety_080 93.890 6.110 99.000 1.000 39.18 224 0.875 bicubic
98 xception71 93.890 6.110 98.950 1.050 42.34 299 0.903 bicubic
99 gluon_resnet152_v1c 93.880 6.120 98.800 1.200 60.21 224 0.875 bicubic
100 regnetx_160 93.880 6.120 99.090 0.910 54.28 224 0.875 bicubic
101 ese_vovnet39b 93.850 6.150 98.900 1.100 24.57 224 0.875 bicubic
102 resnext50_32x4d 93.840 6.160 98.830 1.170 25.03 224 0.875 bicubic
103 hrnet_w64 93.830 6.170 98.930 1.070 128.06 224 0.875 bilinear
104 ecaresnet50d_pruned 93.820 6.180 99.000 1.000 19.94 224 0.875 bicubic
105 resnext50d_32x4d 93.810 6.190 98.740 1.260 25.05 224 0.875 bicubic
106 efficientnet_b2_pruned 93.800 6.200 98.910 1.090 8.31 260 0.890 bicubic
107 dla169 93.800 6.200 98.840 1.160 53.39 224 0.875 bilinear
108 regnetx_080 93.790 6.210 98.910 1.090 39.57 224 0.875 bicubic
109 resnext101_32x8d 93.770 6.230 98.950 1.050 88.79 224 0.875 bilinear
110 cspresnext50 93.760 6.240 98.840 1.160 20.57 224 0.875 bilinear
111 dpn131 93.760 6.240 98.800 1.200 79.25 224 0.875 bicubic
112 gluon_resnet101_v1b 93.760 6.240 98.700 1.300 44.55 224 0.875 bicubic
113 xception65 93.760 6.240 98.860 1.140 39.92 299 0.903 bicubic
114 tf_efficientnet_b0_ns 93.740 6.260 98.980 1.020 5.29 224 0.875 bicubic
115 wide_resnet101_2 93.730 6.270 98.810 1.190 126.89 224 0.875 bilinear
116 hrnet_w40 93.710 6.290 98.800 1.200 57.56 224 0.875 bilinear
117 resnetblur50 93.710 6.290 98.810 1.190 25.56 224 0.875 bicubic
118 tf_efficientnet_b1 93.710 6.290 98.800 1.200 7.79 240 0.882 bicubic
119 gluon_resnet101_v1c 93.690 6.310 98.760 1.240 44.57 224 0.875 bicubic
120 regnetx_040 93.680 6.320 98.940 1.060 22.12 224 0.875 bicubic
121 rexnet_130 93.670 6.330 98.710 1.290 7.56 224 0.875 bicubic
122 gluon_resnext50_32x4d 93.650 6.350 98.690 1.310 25.03 224 0.875 bicubic
123 xception 93.640 6.360 98.770 1.230 22.86 299 0.897 bicubic
124 regnetx_064 93.630 6.370 99.050 0.950 26.21 224 0.875 bicubic
125 tf_efficientnet_b1_ap 93.630 6.370 98.800 1.200 7.79 240 0.882 bicubic
126 dpn68b 93.620 6.380 98.700 1.300 12.61 224 0.875 bicubic
127 hrnet_w44 93.620 6.380 98.960 1.040 67.06 224 0.875 bilinear
128 regnety_040 93.620 6.380 98.950 1.050 20.65 224 0.875 bicubic
129 gluon_resnet50_v1s 93.590 6.410 98.840 1.160 25.68 224 0.875 bicubic
130 res2net50_26w_6s 93.590 6.410 98.750 1.250 37.05 224 0.875 bilinear
131 dla60_res2next 93.570 6.430 98.800 1.200 17.03 224 0.875 bilinear
132 tf_efficientnet_cc_b1_8e 93.570 6.430 98.690 1.310 39.72 240 0.882 bicubic
133 gluon_inception_v3 93.540 6.460 98.830 1.170 23.83 299 0.875 bicubic
134 dla102x 93.530 6.470 98.850 1.150 26.31 224 0.875 bilinear
135 gluon_resnet50_v1d 93.530 6.470 98.710 1.290 25.58 224 0.875 bicubic
136 res2net101_26w_4s 93.520 6.480 98.600 1.400 45.21 224 0.875 bilinear
137 selecsls60b 93.500 6.500 98.840 1.160 32.77 224 0.875 bicubic
138 xception41 93.480 6.520 98.750 1.250 26.97 299 0.903 bicubic
139 tf_efficientnet_em 93.470 6.530 98.750 1.250 6.90 240 0.882 bicubic
140 regnety_032 93.460 6.540 98.950 1.050 19.44 224 0.875 bicubic
141 resnet50 93.460 6.540 98.600 1.400 25.56 224 0.875 bicubic
142 wide_resnet50_2 93.460 6.540 98.950 1.050 68.88 224 0.875 bilinear
143 res2net50_26w_8s 93.450 6.550 98.700 1.300 48.40 224 0.875 bilinear
144 dla60_res2net 93.380 6.620 98.860 1.140 20.85 224 0.875 bilinear
145 hrnet_w30 93.370 6.630 98.830 1.170 37.71 224 0.875 bilinear
146 dla102 93.260 6.740 98.780 1.220 33.27 224 0.875 bilinear
147 mixnet_l 93.260 6.740 98.700 1.300 7.33 224 0.875 bicubic
148 regnetx_032 93.250 6.750 98.730 1.270 15.30 224 0.875 bicubic
149 resnest26d 93.240 6.760 98.850 1.150 17.07 224 0.875 bilinear
150 resnet152 93.240 6.760 98.750 1.250 60.19 224 0.875 bilinear
151 tf_inception_v3 93.200 6.800 98.480 1.520 23.83 299 0.875 bicubic
152 dla60x 93.190 6.810 98.710 1.290 17.35 224 0.875 bilinear
153 res2net50_26w_4s 93.180 6.820 98.670 1.330 25.70 224 0.875 bilinear
154 res2next50 93.150 6.850 98.660 1.340 24.67 224 0.875 bilinear
155 efficientnet_b1 93.060 6.940 98.540 1.460 7.79 240 0.875 bicubic
156 tf_mixnet_l 93.040 6.960 98.540 1.460 7.33 224 0.875 bicubic
157 res2net50_14w_8s 93.030 6.970 98.700 1.300 25.06 224 0.875 bilinear
158 adv_inception_v3 93.010 6.990 98.490 1.510 23.83 299 0.875 bicubic
159 selecsls60 93.010 6.990 98.830 1.170 30.67 224 0.875 bicubic
160 regnety_016 93.000 7.000 98.680 1.320 11.20 224 0.875 bicubic
161 efficientnet_b1_pruned 92.980 7.020 98.530 1.470 6.33 240 0.882 bicubic
162 seresnext26t_32x4d 92.960 7.040 98.480 1.520 16.82 224 0.875 bicubic
163 hrnet_w32 92.950 7.050 98.840 1.160 41.23 224 0.875 bilinear
164 efficientnet_es 92.910 7.090 98.690 1.310 5.44 224 0.875 bicubic
165 gluon_resnet50_v1c 92.910 7.090 98.710 1.290 25.58 224 0.875 bicubic
166 inception_v3 92.900 7.100 98.330 1.670 23.83 299 0.875 bicubic
167 tv_resnext50_32x4d 92.900 7.100 98.720 1.280 25.03 224 0.875 bilinear
168 densenet161 92.900 7.100 98.810 1.190 28.68 224 0.875 bicubic
169 resnet101 92.880 7.120 98.660 1.340 44.55 224 0.875 bilinear
170 tf_efficientnet_cc_b0_8e 92.870 7.130 98.460 1.540 24.01 224 0.875 bicubic
171 rexnet_100 92.850 7.150 98.620 1.380 4.80 224 0.875 bicubic
172 tf_efficientnet_cc_b0_4e 92.840 7.160 98.440 1.560 13.31 224 0.875 bicubic
173 seresnext26tn_32x4d 92.820 7.180 98.560 1.440 16.81 224 0.875 bicubic
174 res2net50_48w_2s 92.790 7.210 98.470 1.530 25.29 224 0.875 bilinear
175 hrnet_w18 92.760 7.240 98.660 1.340 21.30 224 0.875 bilinear
176 densenet201 92.690 7.310 98.650 1.350 20.01 224 0.875 bicubic
177 dla60 92.670 7.330 98.630 1.370 22.04 224 0.875 bilinear
178 mobilenetv2_120d 92.610 7.390 98.510 1.490 5.83 224 0.875 bicubic
179 tf_efficientnet_b0_ap 92.610 7.390 98.370 1.630 5.29 224 0.875 bicubic
180 tf_efficientnet_lite2 92.590 7.410 98.550 1.450 6.09 260 0.890 bicubic
181 skresnet34 92.570 7.430 98.520 1.480 22.28 224 0.875 bicubic
182 gluon_resnet50_v1b 92.560 7.440 98.550 1.450 25.56 224 0.875 bicubic
183 tf_efficientnet_es 92.550 7.450 98.510 1.490 5.44 224 0.875 bicubic
184 regnetx_016 92.540 7.460 98.550 1.450 9.19 224 0.875 bicubic
185 efficientnet_b0 92.480 7.520 98.680 1.320 5.29 224 0.875 bicubic
186 selecsls42b 92.480 7.520 98.440 1.560 32.46 224 0.875 bicubic
187 seresnext26d_32x4d 92.440 7.560 98.540 1.460 16.81 224 0.875 bicubic
188 densenetblur121d 92.400 7.600 98.410 1.590 8.00 224 0.875 bicubic
189 tf_efficientnet_b0 92.400 7.600 98.470 1.530 5.29 224 0.875 bicubic
190 tf_efficientnet_lite1 92.310 7.690 98.490 1.510 5.42 240 0.882 bicubic
191 densenet169 92.300 7.700 98.590 1.410 14.15 224 0.875 bicubic
192 mixnet_m 92.270 7.730 98.350 1.650 5.01 224 0.875 bicubic
193 dpn68 92.240 7.760 98.610 1.390 12.61 224 0.875 bicubic
194 resnet26d 92.230 7.770 98.450 1.550 16.01 224 0.875 bicubic
195 tf_mixnet_m 92.200 7.800 98.420 1.580 5.01 224 0.875 bicubic
196 tv_resnet50 92.140 7.860 98.420 1.580 25.56 224 0.875 bilinear
197 mobilenetv2_140 92.030 7.970 98.250 1.750 6.11 224 0.875 bicubic
198 ese_vovnet19b_dw 92.010 7.990 98.510 1.490 6.54 224 0.875 bicubic
199 densenet121 91.940 8.060 98.280 1.720 7.98 224 0.875 bicubic
200 regnety_008 91.900 8.100 98.420 1.580 6.26 224 0.875 bicubic
201 mixnet_s 91.780 8.220 98.300 1.700 4.13 224 0.875 bicubic
202 tf_mixnet_s 91.680 8.320 98.240 1.760 4.13 224 0.875 bicubic
203 semnasnet_100 91.660 8.340 98.270 1.730 3.89 224 0.875 bicubic
204 regnety_006 91.570 8.430 98.430 1.570 6.06 224 0.875 bicubic
205 mobilenetv3_rw 91.550 8.450 98.270 1.730 5.48 224 0.875 bicubic
206 mobilenetv3_large_100 91.480 8.520 98.320 1.680 5.48 224 0.875 bicubic
207 resnet26 91.440 8.560 98.280 1.720 16.00 224 0.875 bicubic
208 tf_mobilenetv3_large_100 91.420 8.580 98.260 1.740 5.48 224 0.875 bilinear
209 tv_densenet121 91.400 8.600 98.250 1.750 7.98 224 0.875 bicubic
210 mobilenetv2_110d 91.350 8.650 98.190 1.810 4.52 224 0.875 bicubic
211 tf_efficientnet_lite0 91.300 8.700 98.090 1.910 4.65 224 0.875 bicubic
212 fbnetc_100 91.270 8.730 97.830 2.170 5.57 224 0.875 bilinear
213 efficientnet_lite0 91.260 8.740 98.250 1.750 4.65 224 0.875 bicubic
214 dla34 91.240 8.760 98.180 1.820 15.74 224 0.875 bilinear
215 mnasnet_100 91.200 8.800 98.050 1.950 4.38 224 0.875 bicubic
216 resnet34 91.200 8.800 98.240 1.760 21.80 224 0.875 bilinear
217 regnetx_008 91.180 8.820 98.380 1.620 7.26 224 0.875 bicubic
218 hrnet_w18_small_v2 91.170 8.830 98.340 1.660 15.60 224 0.875 bilinear
219 resnest14d 91.130 8.870 98.330 1.670 10.61 224 0.875 bilinear
220 gluon_resnet34_v1b 91.100 8.900 98.180 1.820 21.80 224 0.875 bicubic
221 swsl_resnet18 91.090 8.910 98.210 1.790 11.69 224 0.875 bilinear
222 regnety_004 90.780 9.220 98.080 1.920 4.34 224 0.875 bicubic
223 regnetx_006 90.760 9.240 98.100 1.900 6.20 224 0.875 bicubic
224 ssl_resnet18 90.700 9.300 98.020 1.980 11.69 224 0.875 bilinear
225 spnasnet_100 90.610 9.390 97.950 2.050 4.42 224 0.875 bilinear
226 tf_mobilenetv3_large_075 90.320 9.680 97.870 2.130 3.99 224 0.875 bilinear
227 tv_resnet34 90.290 9.710 97.980 2.020 21.80 224 0.875 bilinear
228 skresnet18 90.160 9.840 97.780 2.220 11.96 224 0.875 bicubic
229 hrnet_w18_small 89.880 10.120 97.900 2.100 13.19 224 0.875 bilinear
230 mobilenetv2_100 89.830 10.170 97.830 2.170 3.50 224 0.875 bicubic
231 regnetx_004 89.460 10.540 97.770 2.230 5.16 224 0.875 bicubic
232 tf_mobilenetv3_large_minimal_100 89.180 10.820 97.320 2.680 3.92 224 0.875 bilinear
233 gluon_resnet18_v1b 88.660 11.340 97.100 2.900 11.69 224 0.875 bicubic
234 regnety_002 88.200 11.800 97.430 2.570 3.16 224 0.875 bicubic
235 resnet18 88.150 11.850 97.120 2.880 11.69 224 0.875 bilinear
236 regnetx_002 87.380 12.620 96.990 3.010 2.68 224 0.875 bicubic
237 dla60x_c 87.110 12.890 97.140 2.860 1.32 224 0.875 bilinear
238 tf_mobilenetv3_small_100 85.960 14.040 96.400 3.600 2.54 224 0.875 bilinear
239 dla46x_c 85.480 14.520 96.440 3.560 1.07 224 0.875 bilinear
240 dla46_c 84.660 15.340 96.200 3.800 1.30 224 0.875 bilinear
241 tf_mobilenetv3_small_075 84.530 15.470 95.890 4.110 2.04 224 0.875 bilinear
242 tf_mobilenetv3_small_minimal_100 82.670 17.330 95.000 5.000 2.04 224 0.875 bilinear

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results/results-imagenet-r.csv
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model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff
ig_resnext101_32x48d,79.650,20.350,89.393,10.607,828.41,224,0.875,bilinear,-17.320,-10.277,+4
ig_resnext101_32x32d,79.457,20.543,89.183,10.817,468.53,224,0.875,bilinear,-17.323,-10.347,+5
ig_resnext101_32x16d,78.837,21.163,88.480,11.520,194.03,224,0.875,bilinear,-17.603,-11.060,+9
tf_efficientnet_l2_ns_475,76.480,23.520,88.653,11.347,480.31,475,0.936,bicubic,-21.270,-11.167,-2
swsl_resnext101_32x16d,76.303,23.697,87.733,12.267,194.03,224,0.875,bilinear,-19.967,-11.767,+11
ig_resnext101_32x8d,75.813,24.187,86.200,13.800,88.79,224,0.875,bilinear,-20.117,-13.180,+18
swsl_resnext101_32x8d,75.590,24.410,86.937,13.063,88.79,224,0.875,bilinear,-20.650,-12.653,+10
tf_efficientnet_l2_ns,74.650,25.350,87.543,12.457,480.31,800,0.960,bicubic,-23.130,-12.347,-7
swsl_resnext101_32x4d,72.660,27.340,85.157,14.843,44.18,224,0.875,bilinear,-23.390,-14.373,+13
swsl_resnext50_32x4d,68.977,31.023,82.810,17.190,25.03,224,0.875,bilinear,-26.643,-16.630,+15
swsl_resnet50,68.297,31.703,83.313,16.687,25.56,224,0.875,bilinear,-26.903,-16.077,+24
tf_efficientnet_b7_ns,67.510,32.490,81.383,18.617,66.35,600,0.949,bicubic,-29.690,-18.317,-9
tf_efficientnet_b6_ns,65.587,34.413,79.553,20.447,43.04,528,0.942,bicubic,-31.433,-20.157,-9
tf_efficientnet_b5_ns,63.047,36.953,77.777,22.223,30.39,456,0.934,bicubic,-33.823,-21.863,-8
tf_efficientnet_b4_ns,61.230,38.770,76.173,23.827,19.34,380,0.922,bicubic,-35.480,-23.467,-7
tf_efficientnet_b8_ap,57.830,42.170,72.957,27.043,87.41,672,0.954,bicubic,-38.720,-26.583,-5
tf_efficientnet_b3_ns,57.417,42.583,72.387,27.613,12.23,300,0.904,bicubic,-38.683,-27.093,+2
tf_efficientnet_b5_ap,53.870,46.130,69.160,30.840,30.39,456,0.934,bicubic,-42.210,-30.380,+2
tf_efficientnet_b2_ns,53.600,46.400,70.270,29.730,9.11,260,0.890,bicubic,-41.920,-29.070,+9
tf_efficientnet_b6_ap,53.560,46.440,68.550,31.450,43.04,528,0.942,bicubic,-42.810,-31.000,-7
tf_efficientnet_b8,53.410,46.590,69.090,30.910,87.41,672,0.954,bicubic,-43.290,-30.440,-12
tf_efficientnet_b7_ap,53.260,46.740,68.873,31.127,66.35,600,0.949,bicubic,-43.090,-30.717,-8
tf_efficientnet_b4_ap,53.090,46.910,68.210,31.790,19.34,380,0.922,bicubic,-42.400,-31.180,+7
tf_efficientnet_b7,52.393,47.607,68.233,31.767,66.35,600,0.949,bicubic,-44.187,-31.277,-14
swsl_resnet18,52.327,47.673,70.480,29.520,11.69,224,0.875,bilinear,-38.763,-27.730,+195
tf_efficientnet_b1_ns,50.883,49.117,67.910,32.090,7.79,240,0.882,bicubic,-43.977,-31.340,+20
ssl_resnext101_32x16d,50.257,49.743,66.033,33.967,194.03,224,0.875,bilinear,-45.153,-33.267,+5
resnest269e,50.153,49.847,64.670,35.330,110.93,416,0.928,bicubic,-45.967,-34.850,-10
tf_efficientnet_b3_ap,50.057,49.943,65.210,34.790,12.23,300,0.904,bicubic,-44.913,-33.900,+12
resnest200e,49.873,50.127,64.743,35.257,70.20,320,0.909,bicubic,-46.197,-34.737,-9
tf_efficientnet_b5,49.510,50.490,65.657,34.343,30.39,456,0.934,bicubic,-46.470,-33.793,-8
resnest101e,49.367,50.633,65.587,34.413,48.28,256,0.875,bilinear,-46.203,-33.683,-5
ssl_resnext101_32x8d,49.067,50.933,65.480,34.520,88.79,224,0.875,bilinear,-46.273,-33.840,+1
ecaresnet101d,48.527,51.473,64.100,35.900,44.57,224,0.875,bicubic,-46.633,-35.130,+2
resnest50d_4s2x40d,47.483,52.517,63.807,36.193,30.42,224,0.875,bicubic,-47.227,-35.323,+14
efficientnet_b3_pruned,47.447,52.553,62.793,37.207,9.86,300,0.904,bicubic,-47.133,-36.277,+19
tf_efficientnet_b6,47.213,52.787,63.110,36.890,43.04,528,0.942,bicubic,-49.077,-36.410,-22
ssl_resnext101_32x4d,47.177,52.823,63.367,36.633,44.18,224,0.875,bilinear,-47.983,-35.933,-1
tf_efficientnet_b4,47.083,52.917,62.867,37.133,19.34,380,0.922,bicubic,-48.507,-36.463,-13
gluon_seresnext101_64x4d,46.677,53.323,61.303,38.697,88.23,224,0.875,bicubic,-47.973,-37.677,+13
tresnet_xl,46.283,53.717,61.943,38.057,78.44,224,0.875,bilinear,-48.777,-37.317,-1
resnest50d_1s4x24d,46.083,53.917,62.377,37.623,25.68,224,0.875,bicubic,-48.307,-36.693,+19
tf_efficientnet_b0_ns,46.047,53.953,63.253,36.747,5.29,224,0.875,bicubic,-47.693,-35.727,+70
resnest50d,45.937,54.063,62.623,37.377,27.48,224,0.875,bilinear,-48.683,-36.407,+10
gluon_seresnext101_32x4d,45.590,54.410,61.143,38.857,48.96,224,0.875,bicubic,-48.860,-37.947,+13
gluon_resnet152_v1d,45.430,54.570,60.077,39.923,60.21,224,0.875,bicubic,-49.010,-38.933,+14
ssl_resnext50_32x4d,45.407,54.593,62.047,37.953,25.03,224,0.875,bilinear,-49.293,-37.193,+3
tresnet_xl_448,45.223,54.777,61.437,38.563,78.44,448,0.875,bilinear,-50.287,-37.903,-19
nasnetalarge,45.210,54.790,57.883,42.117,88.75,331,0.911,bicubic,-49.940,-41.247,-11
tf_efficientnet_b3,45.107,54.893,60.650,39.350,12.23,300,0.904,bicubic,-49.803,-38.460,-7
rexnet_200,45.047,54.953,62.317,37.683,16.37,224,0.875,bicubic,-49.613,-36.773,0
ecaresnetlight,44.890,55.110,60.770,39.230,30.16,224,0.875,bicubic,-49.250,-38.180,+27
tf_efficientnet_b2_ap,44.700,55.300,60.680,39.320,9.11,260,0.890,bicubic,-49.570,-38.270,+17
ens_adv_inception_resnet_v2,44.393,55.607,58.117,41.883,55.84,299,0.897,bicubic,-49.737,-40.673,+27
tresnet_l,44.363,55.637,59.953,40.047,55.99,224,0.875,bilinear,-50.537,-39.077,-11
gluon_resnext101_32x4d,44.290,55.710,59.090,40.910,44.18,224,0.875,bicubic,-49.830,-39.840,+27
cspresnext50,44.147,55.853,60.533,39.467,20.57,224,0.875,bilinear,-49.613,-38.307,+52
gluon_resnet152_v1s,44.073,55.927,58.703,41.297,60.32,224,0.875,bicubic,-50.647,-40.357,-11
ssl_resnet50,44.010,55.990,61.887,38.113,25.56,224,0.875,bilinear,-50.300,-37.263,+8
inception_resnet_v2,44.003,55.997,57.907,42.093,55.84,299,0.897,bicubic,-50.337,-40.893,+6
pnasnet5large,43.950,56.050,56.730,43.270,86.06,331,0.911,bicubic,-51.410,-42.400,-28
gluon_resnext101_64x4d,43.877,56.123,58.710,41.290,83.46,224,0.875,bicubic,-50.473,-40.170,+2
ecaresnet50d,43.750,56.250,60.387,39.613,25.58,224,0.875,bicubic,-50.440,-38.633,+12
ecaresnet101d_pruned,43.737,56.263,59.607,40.393,24.88,224,0.875,bicubic,-50.713,-39.493,-7
rexnet_150,43.690,56.310,60.897,39.103,9.73,224,0.875,bicubic,-50.580,-38.183,+4
efficientnet_b3a,43.677,56.323,59.897,40.103,12.23,320,1.000,bicubic,-51.443,-39.223,-27
efficientnet_b3,43.597,56.403,59.810,40.190,12.23,300,0.904,bicubic,-51.363,-39.390,-25
gluon_resnet101_v1d,43.440,56.560,58.613,41.387,44.57,224,0.875,bicubic,-50.730,-40.397,+9
gluon_resnet101_v1s,43.363,56.637,58.503,41.497,44.67,224,0.875,bicubic,-50.807,-40.407,+9
cspdarknet53,43.357,56.643,59.430,40.570,27.64,256,0.887,bilinear,-50.733,-39.550,+15
dpn68b,43.287,56.713,58.673,41.327,12.61,224,0.875,bicubic,-50.333,-40.027,+54
resnest26d,43.140,56.860,60.623,39.377,17.07,224,0.875,bilinear,-50.100,-38.227,+76
dpn131,43.047,56.953,57.440,42.560,79.25,224,0.875,bicubic,-50.713,-41.360,+37
tf_efficientnet_lite4,42.967,57.033,57.620,42.380,13.01,380,0.920,bilinear,-51.903,-41.470,-29
gluon_resnet152_v1b,42.903,57.097,57.750,42.250,60.19,224,0.875,bicubic,-51.127,-40.990,+13
dpn107,42.857,57.143,57.367,42.633,86.92,224,0.875,bicubic,-51.103,-41.473,+17
tf_efficientnet_b1_ap,42.803,57.197,58.813,41.187,7.79,240,0.882,bicubic,-50.827,-39.987,+47
gluon_resnet152_v1c,42.800,57.200,57.737,42.263,60.21,224,0.875,bicubic,-51.080,-41.063,+20
gluon_xception65,42.793,57.207,58.820,41.180,39.92,299,0.903,bicubic,-51.217,-40.210,+12
tresnet_l_448,42.753,57.247,58.947,41.053,55.99,448,0.875,bilinear,-52.657,-40.463,-49
tresnet_m,42.687,57.313,58.153,41.847,31.39,224,0.875,bilinear,-51.383,-40.677,+6
gluon_seresnext50_32x4d,42.683,57.317,58.710,41.290,27.56,224,0.875,bicubic,-51.487,-40.230,-6
resnext101_32x8d,42.557,57.443,58.317,41.683,88.79,224,0.875,bilinear,-51.213,-40.633,+25
seresnet50,42.510,57.490,58.667,41.333,28.09,224,0.875,bicubic,-51.570,-40.303,+2
dpn98,42.280,57.720,56.880,43.120,61.57,224,0.875,bicubic,-51.660,-42.040,+10
tf_efficientnet_cc_b1_8e,42.233,57.767,58.420,41.580,39.72,240,0.882,bicubic,-51.337,-40.270,+45
tf_efficientnet_b2,42.120,57.880,58.197,41.803,9.11,260,0.890,bicubic,-52.090,-40.833,-14
gluon_resnext50_32x4d,42.043,57.957,57.667,42.333,25.03,224,0.875,bicubic,-51.607,-41.023,+33
resnet50,42.013,57.987,56.000,44.000,25.56,224,0.875,bicubic,-51.447,-42.600,+51
ecaresnet50d_pruned,41.953,58.047,58.217,41.783,19.94,224,0.875,bicubic,-51.867,-40.783,+13
efficientnet_b2a,41.933,58.067,58.300,41.700,9.11,288,1.000,bicubic,-52.437,-40.750,-28
dla102x2,41.647,58.353,57.967,42.033,41.28,224,0.875,bilinear,-52.353,-41.063,0
hrnet_w64,41.637,58.363,57.130,42.870,128.06,224,0.875,bilinear,-52.193,-41.800,+9
efficientnet_b2,41.627,58.373,58.033,41.967,9.11,260,0.875,bicubic,-52.713,-41.067,-29
gluon_senet154,41.627,58.373,56.373,43.627,115.09,224,0.875,bicubic,-53.083,-42.597,-47
inception_v4,41.577,58.423,55.383,44.617,42.68,299,0.875,bicubic,-52.803,-43.437,-34
tf_efficientnet_cc_b0_8e,41.487,58.513,57.377,42.623,24.01,224,0.875,bicubic,-51.383,-41.083,+72
resnext50_32x4d,41.443,58.557,56.997,43.003,25.03,224,0.875,bicubic,-52.397,-41.833,+3
resnet152,41.327,58.673,57.520,42.480,60.19,224,0.875,bilinear,-51.913,-41.230,+50
xception71,41.270,58.730,55.873,44.127,42.34,299,0.903,bicubic,-52.620,-43.077,-3
dpn92,41.267,58.733,56.333,43.667,37.67,224,0.875,bicubic,-52.923,-42.597,-27
adv_inception_v3,41.263,58.737,56.317,43.683,23.83,299,0.875,bicubic,-51.747,-42.173,+55
resnetblur50,41.053,58.947,57.077,42.923,25.56,224,0.875,bicubic,-52.657,-41.733,+13
gluon_resnet50_v1d,40.970,59.030,57.137,42.863,25.58,224,0.875,bicubic,-52.560,-41.573,+30
gluon_inception_v3,40.907,59.093,55.617,44.383,23.83,299,0.875,bicubic,-52.633,-43.213,+27
ese_vovnet39b,40.867,59.133,56.950,43.050,24.57,224,0.875,bicubic,-52.983,-41.950,-6
regnety_320,40.813,59.187,56.117,43.883,145.05,224,0.875,bicubic,-53.707,-43.053,-51
xception,40.763,59.237,56.387,43.613,22.86,299,0.897,bicubic,-52.877,-42.383,+14
skresnext50_32x4d,40.700,59.300,56.023,43.977,27.48,224,0.875,bicubic,-53.250,-42.797,-15
gluon_resnet101_v1b,40.683,59.317,56.117,43.883,44.55,224,0.875,bicubic,-53.077,-42.583,+1
hrnet_w40,40.660,59.340,56.753,43.247,57.56,224,0.875,bilinear,-53.050,-42.047,+4
tf_efficientnet_lite3,40.563,59.437,56.477,43.523,8.20,300,0.904,bilinear,-53.567,-42.483,-30
tresnet_m_448,40.530,59.470,56.700,43.300,31.39,448,0.875,bilinear,-54.130,-42.450,-61
dla169,40.493,59.507,57.263,42.737,53.39,224,0.875,bilinear,-53.307,-41.647,-8
regnetx_320,40.443,59.557,55.660,44.340,107.81,224,0.875,bicubic,-53.767,-43.390,-43
skresnet34,40.397,59.603,56.737,43.263,22.28,224,0.875,bicubic,-52.173,-41.783,+64
efficientnet_b2_pruned,40.383,59.617,56.537,43.463,8.31,260,0.890,bicubic,-53.417,-42.303,-12
wide_resnet101_2,40.360,59.640,55.780,44.220,126.89,224,0.875,bilinear,-53.370,-43.030,-4
tf_efficientnet_b0_ap,40.337,59.663,56.787,43.213,5.29,224,0.875,bicubic,-52.273,-41.583,+59
xception65,40.273,59.727,55.283,44.717,39.92,299,0.903,bicubic,-53.487,-43.577,-8
regnetx_160,40.270,59.730,56.050,43.950,54.28,224,0.875,bicubic,-53.610,-43.040,-22
densenet201,40.267,59.733,56.710,43.290,20.01,224,0.875,bicubic,-52.423,-41.940,+53
resnext50d_32x4d,40.170,59.830,55.487,44.513,25.05,224,0.875,bicubic,-53.640,-43.253,-19
hrnet_w48,40.093,59.907,56.640,43.360,77.47,224,0.875,bilinear,-53.937,-42.400,-35
hrnet_w30,40.030,59.970,57.093,42.907,37.71,224,0.875,bilinear,-53.340,-41.737,+19
regnetx_080,40.000,60.000,55.977,44.023,39.57,224,0.875,bicubic,-53.790,-42.933,-19
tf_efficientnet_b1,39.977,60.023,56.137,43.863,7.79,240,0.882,bicubic,-53.733,-42.663,-10
gluon_resnet101_v1c,39.953,60.047,55.300,44.700,44.57,224,0.875,bicubic,-53.737,-43.460,-10
res2net101_26w_4s,39.717,60.283,54.550,45.450,45.21,224,0.875,bilinear,-53.803,-44.050,+6
regnetx_120,39.687,60.313,55.633,44.367,46.11,224,0.875,bicubic,-54.583,-43.557,-62
hrnet_w44,39.677,60.323,55.333,44.667,67.06,224,0.875,bilinear,-53.943,-43.627,-5
densenet161,39.620,60.380,56.133,43.867,28.68,224,0.875,bicubic,-53.280,-42.587,+35
mixnet_xl,39.617,60.383,55.887,44.113,11.90,224,0.875,bicubic,-54.613,-42.933,-62
xception41,39.610,60.390,55.037,44.963,26.97,299,0.903,bicubic,-53.870,-43.713,+3
res2net50_26w_8s,39.603,60.397,54.550,45.450,48.40,224,0.875,bilinear,-53.847,-44.150,+7
tf_efficientnet_el,39.563,60.437,55.310,44.690,10.59,300,0.904,bicubic,-54.887,-43.770,-77
dla102x,39.553,60.447,56.323,43.677,26.31,224,0.875,bilinear,-53.977,-42.527,-4
rexnet_130,39.487,60.513,56.640,43.360,7.56,224,0.875,bicubic,-54.183,-42.070,-18
hrnet_w32,39.463,60.537,56.123,43.877,41.23,224,0.875,bilinear,-53.487,-42.717,+23
regnety_064,39.403,60.597,55.773,44.227,30.58,224,0.875,bicubic,-54.737,-43.257,-60
densenetblur121d,39.380,60.620,56.640,43.360,8.00,224,0.875,bicubic,-53.020,-41.770,+46
regnety_120,39.347,60.653,55.277,44.723,51.82,224,0.875,bicubic,-54.663,-43.743,-52
resnet101,39.307,60.693,55.803,44.197,44.55,224,0.875,bilinear,-53.573,-42.857,+25
regnety_160,39.260,60.740,55.433,44.567,83.59,224,0.875,bicubic,-54.860,-43.587,-60
tf_inception_v3,39.237,60.763,54.300,45.700,23.83,299,0.875,bicubic,-53.963,-44.180,+5
gluon_resnet50_v1s,39.233,60.767,55.010,44.990,25.68,224,0.875,bicubic,-54.357,-43.830,-18
densenet169,39.167,60.833,55.843,44.157,14.15,224,0.875,bicubic,-53.133,-42.747,+43
efficientnet_b1_pruned,39.010,60.990,55.647,44.353,6.33,240,0.882,bicubic,-53.970,-42.883,+12
inception_v3,38.960,61.040,53.853,46.147,23.83,299,0.875,bicubic,-53.940,-44.957,+16
dpn68,38.933,61.067,54.933,45.067,12.61,224,0.875,bicubic,-53.307,-43.677,+42
regnety_080,38.917,61.083,55.213,44.787,39.18,224,0.875,bicubic,-54.973,-43.787,-55
dla102,38.833,61.167,55.323,44.677,33.27,224,0.875,bilinear,-54.427,-43.457,-7
regnety_040,38.820,61.180,55.557,44.443,20.65,224,0.875,bicubic,-54.800,-43.393,-26
densenet121,38.783,61.217,56.273,43.727,7.98,224,0.875,bicubic,-53.157,-42.007,+44
res2net50_14w_8s,38.710,61.290,54.077,45.923,25.06,224,0.875,bilinear,-54.320,-44.623,+1
regnetx_040,38.703,61.297,55.340,44.660,22.12,224,0.875,bicubic,-54.977,-43.600,-37
res2net50_26w_6s,38.687,61.313,53.743,46.257,37.05,224,0.875,bilinear,-54.903,-45.007,-28
regnetx_032,38.680,61.320,55.157,44.843,15.30,224,0.875,bicubic,-54.570,-43.573,-11
wide_resnet50_2,38.637,61.363,54.467,45.533,68.88,224,0.875,bilinear,-54.823,-44.483,-18
selecsls60,38.623,61.377,55.630,44.370,30.67,224,0.875,bicubic,-54.387,-43.200,-2
dla60x,38.617,61.383,55.383,44.617,17.35,224,0.875,bilinear,-54.573,-43.327,-10
tf_efficientnet_b0,38.600,61.400,55.957,44.043,5.29,224,0.875,bicubic,-53.800,-42.513,+26
dla60_res2net,38.590,61.410,54.560,45.440,20.85,224,0.875,bilinear,-54.790,-44.300,-20
selecsls60b,38.573,61.427,55.307,44.693,32.77,224,0.875,bicubic,-54.927,-43.533,-28
dla60_res2next,38.450,61.550,54.950,45.050,17.03,224,0.875,bilinear,-55.120,-43.850,-35
regnetx_064,38.430,61.570,54.990,45.010,26.21,224,0.875,bicubic,-55.200,-44.060,-43
tf_efficientnet_cc_b0_4e,38.413,61.587,55.150,44.850,13.31,224,0.875,bicubic,-54.427,-43.290,+4
gluon_resnet50_v1b,38.407,61.593,54.833,45.167,25.56,224,0.875,bicubic,-54.153,-43.717,+13
hrnet_w18,38.277,61.723,55.643,44.357,21.30,224,0.875,bilinear,-54.483,-43.017,+5
regnety_032,38.170,61.830,54.367,45.633,19.44,224,0.875,bicubic,-55.290,-44.583,-31
mixnet_l,38.160,61.840,54.757,45.243,7.33,224,0.875,bicubic,-55.100,-43.943,-25
efficientnet_b1,37.843,62.157,53.640,46.360,7.79,240,0.875,bicubic,-55.217,-44.900,-18
gluon_resnet50_v1c,37.843,62.157,54.123,45.877,25.58,224,0.875,bicubic,-55.067,-44.587,-9
res2net50_26w_4s,37.827,62.173,53.073,46.927,25.70,224,0.875,bilinear,-55.353,-45.597,-22
efficientnet_es,37.770,62.230,54.967,45.033,5.44,224,0.875,bicubic,-55.140,-43.723,-12
resnest14d,37.767,62.233,56.470,43.530,10.61,224,0.875,bilinear,-53.363,-41.860,+42
tv_resnext50_32x4d,37.750,62.250,54.113,45.887,25.03,224,0.875,bilinear,-55.150,-44.217,-11
res2next50,37.477,62.523,52.853,47.147,24.67,224,0.875,bilinear,-55.673,-45.807,-25
resnet34,37.443,62.557,54.297,45.703,21.80,224,0.875,bilinear,-53.757,-43.943,+36
tf_efficientnet_em,37.283,62.717,54.220,45.780,6.90,240,0.882,bicubic,-56.187,-44.530,-42
res2net50_48w_2s,37.117,62.883,53.333,46.667,25.29,224,0.875,bilinear,-55.673,-45.137,-8
dla60,37.073,62.927,54.200,45.800,22.04,224,0.875,bilinear,-55.597,-44.430,-6
rexnet_100,37.063,62.937,54.020,45.980,4.80,224,0.875,bicubic,-55.787,-44.600,-13
regnety_016,37.017,62.983,54.093,45.907,11.20,224,0.875,bicubic,-55.983,-44.587,-25
tf_mixnet_l,36.987,63.013,52.583,47.417,7.33,224,0.875,bicubic,-56.053,-45.957,-30
tv_densenet121,36.810,63.190,54.033,45.967,7.98,224,0.875,bicubic,-54.590,-44.217,+22
tf_efficientnet_lite2,36.807,63.193,53.320,46.680,6.09,260,0.890,bicubic,-55.783,-45.230,-8
mobilenetv2_120d,36.780,63.220,54.047,45.953,5.83,224,0.875,bicubic,-55.830,-44.463,-11
tf_efficientnet_lite1,36.737,63.263,53.590,46.410,5.42,240,0.882,bicubic,-55.573,-44.900,0
regnetx_016,36.683,63.317,53.297,46.703,9.19,224,0.875,bicubic,-55.857,-45.253,-7
efficientnet_b0,36.600,63.400,53.497,46.503,5.29,224,0.875,bicubic,-55.880,-45.183,-7
skresnet18,36.320,63.680,54.197,45.803,11.96,224,0.875,bicubic,-53.840,-43.583,+35
tv_resnet50,36.177,63.823,52.803,47.197,25.56,224,0.875,bilinear,-55.963,-45.617,+2
tv_resnet34,36.087,63.913,53.533,46.467,21.80,224,0.875,bilinear,-54.203,-44.447,+32
mobilenetv2_140,36.000,64.000,53.943,46.057,6.11,224,0.875,bicubic,-56.030,-44.307,+1
tf_efficientnet_lite0,35.930,64.070,53.480,46.520,4.65,224,0.875,bicubic,-55.370,-44.610,+14
selecsls42b,35.813,64.187,52.487,47.513,32.46,224,0.875,bicubic,-56.667,-45.953,-12
gluon_resnet34_v1b,35.763,64.237,52.187,47.813,21.80,224,0.875,bicubic,-55.337,-45.993,+21
dla34,35.643,64.357,52.783,47.217,15.74,224,0.875,bilinear,-55.597,-45.397,+14
mixnet_m,35.640,64.360,52.430,47.570,5.01,224,0.875,bicubic,-56.630,-45.920,-9
efficientnet_lite0,35.620,64.380,53.657,46.343,4.65,224,0.875,bicubic,-55.640,-44.593,+11
ssl_resnet18,35.597,64.403,53.740,46.260,11.69,224,0.875,bilinear,-55.103,-44.280,+21
tf_efficientnet_es,35.563,64.437,52.790,47.210,5.44,224,0.875,bicubic,-56.987,-45.720,-21
mobilenetv3_rw,35.547,64.453,53.713,46.287,5.48,224,0.875,bicubic,-56.003,-44.557,0
mobilenetv2_110d,35.293,64.707,52.830,47.170,4.52,224,0.875,bicubic,-56.057,-45.360,+4
tf_mixnet_m,35.180,64.820,50.987,49.013,5.01,224,0.875,bicubic,-57.020,-47.433,-12
hrnet_w18_small_v2,35.173,64.827,52.440,47.560,15.60,224,0.875,bilinear,-55.997,-45.900,+10
ese_vovnet19b_dw,34.840,65.160,52.030,47.970,6.54,224,0.875,bicubic,-57.170,-46.480,-11
regnety_008,34.807,65.193,51.743,48.257,6.26,224,0.875,bicubic,-57.093,-46.677,-10
mobilenetv3_large_100,34.603,65.397,52.860,47.140,5.48,224,0.875,bicubic,-56.877,-45.460,-5
seresnext26d_32x4d,34.543,65.457,51.543,48.457,16.81,224,0.875,bicubic,-57.897,-46.997,-25
seresnext26tn_32x4d,34.540,65.460,51.377,48.623,16.81,224,0.875,bicubic,-58.280,-47.183,-40
resnet26d,34.273,65.727,51.687,48.313,16.01,224,0.875,bicubic,-57.957,-46.763,-20
fbnetc_100,34.253,65.747,51.180,48.820,5.57,224,0.875,bilinear,-57.017,-46.650,-3
seresnext26t_32x4d,34.210,65.790,51.460,48.540,16.82,224,0.875,bicubic,-58.750,-47.020,-54
regnety_006,34.150,65.850,51.277,48.723,6.06,224,0.875,bicubic,-57.420,-47.153,-13
tf_mobilenetv3_large_100,33.950,66.050,51.490,48.510,5.48,224,0.875,bilinear,-57.470,-46.770,-10
regnetx_008,33.770,66.230,50.547,49.453,7.26,224,0.875,bicubic,-57.410,-47.833,-2
mnasnet_100,33.763,66.237,51.170,48.830,4.38,224,0.875,bicubic,-57.437,-46.880,-5
semnasnet_100,33.520,66.480,50.787,49.213,3.89,224,0.875,bicubic,-58.140,-47.483,-18
resnet26,33.500,66.500,50.927,49.073,16.00,224,0.875,bicubic,-57.940,-47.353,-15
mixnet_s,33.480,66.520,50.997,49.003,4.13,224,0.875,bicubic,-58.300,-47.303,-22
spnasnet_100,33.477,66.523,51.267,48.733,4.42,224,0.875,bilinear,-57.133,-46.683,+1
regnetx_006,33.157,66.843,50.250,49.750,6.20,224,0.875,bicubic,-57.603,-47.850,-2
resnet18,33.067,66.933,51.170,48.830,11.69,224,0.875,bilinear,-55.083,-45.950,+9
hrnet_w18_small,32.667,67.333,50.587,49.413,13.19,224,0.875,bilinear,-57.213,-47.313,+2
mobilenetv2_100,32.523,67.477,50.800,49.200,3.50,224,0.875,bicubic,-57.307,-47.030,+2
regnetx_004,32.517,67.483,49.343,50.657,5.16,224,0.875,bicubic,-56.943,-48.427,+2
gluon_resnet18_v1b,32.407,67.593,49.727,50.273,11.69,224,0.875,bicubic,-56.253,-47.373,+3
regnety_004,32.333,67.667,49.453,50.547,4.34,224,0.875,bicubic,-58.447,-48.627,-9
tf_mixnet_s,32.183,67.817,48.493,51.507,4.13,224,0.875,bicubic,-59.497,-49.747,-30
tf_mobilenetv3_large_075,31.867,68.133,49.110,50.890,3.99,224,0.875,bilinear,-58.453,-48.760,-7
tf_mobilenetv3_large_minimal_100,31.597,68.403,49.337,50.663,3.92,224,0.875,bilinear,-57.583,-47.983,-2
regnety_002,29.687,70.313,46.787,53.213,3.16,224,0.875,bicubic,-58.513,-50.643,-1
regnetx_002,28.860,71.140,45.420,54.580,2.68,224,0.875,bicubic,-58.520,-51.570,0
dla60x_c,28.447,71.553,46.193,53.807,1.32,224,0.875,bilinear,-58.663,-50.947,0
tf_mobilenetv3_small_100,27.297,72.703,44.420,55.580,2.54,224,0.875,bilinear,-58.663,-51.980,0
dla46x_c,26.217,73.783,43.780,56.220,1.07,224,0.875,bilinear,-59.263,-52.660,0
tf_mobilenetv3_small_075,26.200,73.800,43.637,56.363,2.04,224,0.875,bilinear,-58.330,-52.253,+1
dla46_c,25.490,74.510,43.800,56.200,1.30,224,0.875,bilinear,-59.170,-52.400,-1
tf_mobilenetv3_small_minimal_100,25.087,74.913,42.930,57.070,2.04,224,0.875,bilinear,-57.583,-52.070,0
1 model top1 top1_err top5 top5_err param_count img_size cropt_pct interpolation top1_diff top5_diff rank_diff
2 ig_resnext101_32x48d 79.650 20.350 89.393 10.607 828.41 224 0.875 bilinear -17.320 -10.277 +4
3 ig_resnext101_32x32d 79.457 20.543 89.183 10.817 468.53 224 0.875 bilinear -17.323 -10.347 +5
4 ig_resnext101_32x16d 78.837 21.163 88.480 11.520 194.03 224 0.875 bilinear -17.603 -11.060 +9
5 tf_efficientnet_l2_ns_475 76.480 23.520 88.653 11.347 480.31 475 0.936 bicubic -21.270 -11.167 -2
6 swsl_resnext101_32x16d 76.303 23.697 87.733 12.267 194.03 224 0.875 bilinear -19.967 -11.767 +11
7 ig_resnext101_32x8d 75.813 24.187 86.200 13.800 88.79 224 0.875 bilinear -20.117 -13.180 +18
8 swsl_resnext101_32x8d 75.590 24.410 86.937 13.063 88.79 224 0.875 bilinear -20.650 -12.653 +10
9 tf_efficientnet_l2_ns 74.650 25.350 87.543 12.457 480.31 800 0.960 bicubic -23.130 -12.347 -7
10 swsl_resnext101_32x4d 72.660 27.340 85.157 14.843 44.18 224 0.875 bilinear -23.390 -14.373 +13
11 swsl_resnext50_32x4d 68.977 31.023 82.810 17.190 25.03 224 0.875 bilinear -26.643 -16.630 +15
12 swsl_resnet50 68.297 31.703 83.313 16.687 25.56 224 0.875 bilinear -26.903 -16.077 +24
13 tf_efficientnet_b7_ns 67.510 32.490 81.383 18.617 66.35 600 0.949 bicubic -29.690 -18.317 -9
14 tf_efficientnet_b6_ns 65.587 34.413 79.553 20.447 43.04 528 0.942 bicubic -31.433 -20.157 -9
15 tf_efficientnet_b5_ns 63.047 36.953 77.777 22.223 30.39 456 0.934 bicubic -33.823 -21.863 -8
16 tf_efficientnet_b4_ns 61.230 38.770 76.173 23.827 19.34 380 0.922 bicubic -35.480 -23.467 -7
17 tf_efficientnet_b8_ap 57.830 42.170 72.957 27.043 87.41 672 0.954 bicubic -38.720 -26.583 -5
18 tf_efficientnet_b3_ns 57.417 42.583 72.387 27.613 12.23 300 0.904 bicubic -38.683 -27.093 +2
19 tf_efficientnet_b5_ap 53.870 46.130 69.160 30.840 30.39 456 0.934 bicubic -42.210 -30.380 +2
20 tf_efficientnet_b2_ns 53.600 46.400 70.270 29.730 9.11 260 0.890 bicubic -41.920 -29.070 +9
21 tf_efficientnet_b6_ap 53.560 46.440 68.550 31.450 43.04 528 0.942 bicubic -42.810 -31.000 -7
22 tf_efficientnet_b8 53.410 46.590 69.090 30.910 87.41 672 0.954 bicubic -43.290 -30.440 -12
23 tf_efficientnet_b7_ap 53.260 46.740 68.873 31.127 66.35 600 0.949 bicubic -43.090 -30.717 -8
24 tf_efficientnet_b4_ap 53.090 46.910 68.210 31.790 19.34 380 0.922 bicubic -42.400 -31.180 +7
25 tf_efficientnet_b7 52.393 47.607 68.233 31.767 66.35 600 0.949 bicubic -44.187 -31.277 -14
26 swsl_resnet18 52.327 47.673 70.480 29.520 11.69 224 0.875 bilinear -38.763 -27.730 +195
27 tf_efficientnet_b1_ns 50.883 49.117 67.910 32.090 7.79 240 0.882 bicubic -43.977 -31.340 +20
28 ssl_resnext101_32x16d 50.257 49.743 66.033 33.967 194.03 224 0.875 bilinear -45.153 -33.267 +5
29 resnest269e 50.153 49.847 64.670 35.330 110.93 416 0.928 bicubic -45.967 -34.850 -10
30 tf_efficientnet_b3_ap 50.057 49.943 65.210 34.790 12.23 300 0.904 bicubic -44.913 -33.900 +12
31 resnest200e 49.873 50.127 64.743 35.257 70.20 320 0.909 bicubic -46.197 -34.737 -9
32 tf_efficientnet_b5 49.510 50.490 65.657 34.343 30.39 456 0.934 bicubic -46.470 -33.793 -8
33 resnest101e 49.367 50.633 65.587 34.413 48.28 256 0.875 bilinear -46.203 -33.683 -5
34 ssl_resnext101_32x8d 49.067 50.933 65.480 34.520 88.79 224 0.875 bilinear -46.273 -33.840 +1
35 ecaresnet101d 48.527 51.473 64.100 35.900 44.57 224 0.875 bicubic -46.633 -35.130 +2
36 resnest50d_4s2x40d 47.483 52.517 63.807 36.193 30.42 224 0.875 bicubic -47.227 -35.323 +14
37 efficientnet_b3_pruned 47.447 52.553 62.793 37.207 9.86 300 0.904 bicubic -47.133 -36.277 +19
38 tf_efficientnet_b6 47.213 52.787 63.110 36.890 43.04 528 0.942 bicubic -49.077 -36.410 -22
39 ssl_resnext101_32x4d 47.177 52.823 63.367 36.633 44.18 224 0.875 bilinear -47.983 -35.933 -1
40 tf_efficientnet_b4 47.083 52.917 62.867 37.133 19.34 380 0.922 bicubic -48.507 -36.463 -13
41 gluon_seresnext101_64x4d 46.677 53.323 61.303 38.697 88.23 224 0.875 bicubic -47.973 -37.677 +13
42 tresnet_xl 46.283 53.717 61.943 38.057 78.44 224 0.875 bilinear -48.777 -37.317 -1
43 resnest50d_1s4x24d 46.083 53.917 62.377 37.623 25.68 224 0.875 bicubic -48.307 -36.693 +19
44 tf_efficientnet_b0_ns 46.047 53.953 63.253 36.747 5.29 224 0.875 bicubic -47.693 -35.727 +70
45 resnest50d 45.937 54.063 62.623 37.377 27.48 224 0.875 bilinear -48.683 -36.407 +10
46 gluon_seresnext101_32x4d 45.590 54.410 61.143 38.857 48.96 224 0.875 bicubic -48.860 -37.947 +13
47 gluon_resnet152_v1d 45.430 54.570 60.077 39.923 60.21 224 0.875 bicubic -49.010 -38.933 +14
48 ssl_resnext50_32x4d 45.407 54.593 62.047 37.953 25.03 224 0.875 bilinear -49.293 -37.193 +3
49 tresnet_xl_448 45.223 54.777 61.437 38.563 78.44 448 0.875 bilinear -50.287 -37.903 -19
50 nasnetalarge 45.210 54.790 57.883 42.117 88.75 331 0.911 bicubic -49.940 -41.247 -11
51 tf_efficientnet_b3 45.107 54.893 60.650 39.350 12.23 300 0.904 bicubic -49.803 -38.460 -7
52 rexnet_200 45.047 54.953 62.317 37.683 16.37 224 0.875 bicubic -49.613 -36.773 0
53 ecaresnetlight 44.890 55.110 60.770 39.230 30.16 224 0.875 bicubic -49.250 -38.180 +27
54 tf_efficientnet_b2_ap 44.700 55.300 60.680 39.320 9.11 260 0.890 bicubic -49.570 -38.270 +17
55 ens_adv_inception_resnet_v2 44.393 55.607 58.117 41.883 55.84 299 0.897 bicubic -49.737 -40.673 +27
56 tresnet_l 44.363 55.637 59.953 40.047 55.99 224 0.875 bilinear -50.537 -39.077 -11
57 gluon_resnext101_32x4d 44.290 55.710 59.090 40.910 44.18 224 0.875 bicubic -49.830 -39.840 +27
58 cspresnext50 44.147 55.853 60.533 39.467 20.57 224 0.875 bilinear -49.613 -38.307 +52
59 gluon_resnet152_v1s 44.073 55.927 58.703 41.297 60.32 224 0.875 bicubic -50.647 -40.357 -11
60 ssl_resnet50 44.010 55.990 61.887 38.113 25.56 224 0.875 bilinear -50.300 -37.263 +8
61 inception_resnet_v2 44.003 55.997 57.907 42.093 55.84 299 0.897 bicubic -50.337 -40.893 +6
62 pnasnet5large 43.950 56.050 56.730 43.270 86.06 331 0.911 bicubic -51.410 -42.400 -28
63 gluon_resnext101_64x4d 43.877 56.123 58.710 41.290 83.46 224 0.875 bicubic -50.473 -40.170 +2
64 ecaresnet50d 43.750 56.250 60.387 39.613 25.58 224 0.875 bicubic -50.440 -38.633 +12
65 ecaresnet101d_pruned 43.737 56.263 59.607 40.393 24.88 224 0.875 bicubic -50.713 -39.493 -7
66 rexnet_150 43.690 56.310 60.897 39.103 9.73 224 0.875 bicubic -50.580 -38.183 +4
67 efficientnet_b3a 43.677 56.323 59.897 40.103 12.23 320 1.000 bicubic -51.443 -39.223 -27
68 efficientnet_b3 43.597 56.403 59.810 40.190 12.23 300 0.904 bicubic -51.363 -39.390 -25
69 gluon_resnet101_v1d 43.440 56.560 58.613 41.387 44.57 224 0.875 bicubic -50.730 -40.397 +9
70 gluon_resnet101_v1s 43.363 56.637 58.503 41.497 44.67 224 0.875 bicubic -50.807 -40.407 +9
71 cspdarknet53 43.357 56.643 59.430 40.570 27.64 256 0.887 bilinear -50.733 -39.550 +15
72 dpn68b 43.287 56.713 58.673 41.327 12.61 224 0.875 bicubic -50.333 -40.027 +54
73 resnest26d 43.140 56.860 60.623 39.377 17.07 224 0.875 bilinear -50.100 -38.227 +76
74 dpn131 43.047 56.953 57.440 42.560 79.25 224 0.875 bicubic -50.713 -41.360 +37
75 tf_efficientnet_lite4 42.967 57.033 57.620 42.380 13.01 380 0.920 bilinear -51.903 -41.470 -29
76 gluon_resnet152_v1b 42.903 57.097 57.750 42.250 60.19 224 0.875 bicubic -51.127 -40.990 +13
77 dpn107 42.857 57.143 57.367 42.633 86.92 224 0.875 bicubic -51.103 -41.473 +17
78 tf_efficientnet_b1_ap 42.803 57.197 58.813 41.187 7.79 240 0.882 bicubic -50.827 -39.987 +47
79 gluon_resnet152_v1c 42.800 57.200 57.737 42.263 60.21 224 0.875 bicubic -51.080 -41.063 +20
80 gluon_xception65 42.793 57.207 58.820 41.180 39.92 299 0.903 bicubic -51.217 -40.210 +12
81 tresnet_l_448 42.753 57.247 58.947 41.053 55.99 448 0.875 bilinear -52.657 -40.463 -49
82 tresnet_m 42.687 57.313 58.153 41.847 31.39 224 0.875 bilinear -51.383 -40.677 +6
83 gluon_seresnext50_32x4d 42.683 57.317 58.710 41.290 27.56 224 0.875 bicubic -51.487 -40.230 -6
84 resnext101_32x8d 42.557 57.443 58.317 41.683 88.79 224 0.875 bilinear -51.213 -40.633 +25
85 seresnet50 42.510 57.490 58.667 41.333 28.09 224 0.875 bicubic -51.570 -40.303 +2
86 dpn98 42.280 57.720 56.880 43.120 61.57 224 0.875 bicubic -51.660 -42.040 +10
87 tf_efficientnet_cc_b1_8e 42.233 57.767 58.420 41.580 39.72 240 0.882 bicubic -51.337 -40.270 +45
88 tf_efficientnet_b2 42.120 57.880 58.197 41.803 9.11 260 0.890 bicubic -52.090 -40.833 -14
89 gluon_resnext50_32x4d 42.043 57.957 57.667 42.333 25.03 224 0.875 bicubic -51.607 -41.023 +33
90 resnet50 42.013 57.987 56.000 44.000 25.56 224 0.875 bicubic -51.447 -42.600 +51
91 ecaresnet50d_pruned 41.953 58.047 58.217 41.783 19.94 224 0.875 bicubic -51.867 -40.783 +13
92 efficientnet_b2a 41.933 58.067 58.300 41.700 9.11 288 1.000 bicubic -52.437 -40.750 -28
93 dla102x2 41.647 58.353 57.967 42.033 41.28 224 0.875 bilinear -52.353 -41.063 0
94 hrnet_w64 41.637 58.363 57.130 42.870 128.06 224 0.875 bilinear -52.193 -41.800 +9
95 efficientnet_b2 41.627 58.373 58.033 41.967 9.11 260 0.875 bicubic -52.713 -41.067 -29
96 gluon_senet154 41.627 58.373 56.373 43.627 115.09 224 0.875 bicubic -53.083 -42.597 -47
97 inception_v4 41.577 58.423 55.383 44.617 42.68 299 0.875 bicubic -52.803 -43.437 -34
98 tf_efficientnet_cc_b0_8e 41.487 58.513 57.377 42.623 24.01 224 0.875 bicubic -51.383 -41.083 +72
99 resnext50_32x4d 41.443 58.557 56.997 43.003 25.03 224 0.875 bicubic -52.397 -41.833 +3
100 resnet152 41.327 58.673 57.520 42.480 60.19 224 0.875 bilinear -51.913 -41.230 +50
101 xception71 41.270 58.730 55.873 44.127 42.34 299 0.903 bicubic -52.620 -43.077 -3
102 dpn92 41.267 58.733 56.333 43.667 37.67 224 0.875 bicubic -52.923 -42.597 -27
103 adv_inception_v3 41.263 58.737 56.317 43.683 23.83 299 0.875 bicubic -51.747 -42.173 +55
104 resnetblur50 41.053 58.947 57.077 42.923 25.56 224 0.875 bicubic -52.657 -41.733 +13
105 gluon_resnet50_v1d 40.970 59.030 57.137 42.863 25.58 224 0.875 bicubic -52.560 -41.573 +30
106 gluon_inception_v3 40.907 59.093 55.617 44.383 23.83 299 0.875 bicubic -52.633 -43.213 +27
107 ese_vovnet39b 40.867 59.133 56.950 43.050 24.57 224 0.875 bicubic -52.983 -41.950 -6
108 regnety_320 40.813 59.187 56.117 43.883 145.05 224 0.875 bicubic -53.707 -43.053 -51
109 xception 40.763 59.237 56.387 43.613 22.86 299 0.897 bicubic -52.877 -42.383 +14
110 skresnext50_32x4d 40.700 59.300 56.023 43.977 27.48 224 0.875 bicubic -53.250 -42.797 -15
111 gluon_resnet101_v1b 40.683 59.317 56.117 43.883 44.55 224 0.875 bicubic -53.077 -42.583 +1
112 hrnet_w40 40.660 59.340 56.753 43.247 57.56 224 0.875 bilinear -53.050 -42.047 +4
113 tf_efficientnet_lite3 40.563 59.437 56.477 43.523 8.20 300 0.904 bilinear -53.567 -42.483 -30
114 tresnet_m_448 40.530 59.470 56.700 43.300 31.39 448 0.875 bilinear -54.130 -42.450 -61
115 dla169 40.493 59.507 57.263 42.737 53.39 224 0.875 bilinear -53.307 -41.647 -8
116 regnetx_320 40.443 59.557 55.660 44.340 107.81 224 0.875 bicubic -53.767 -43.390 -43
117 skresnet34 40.397 59.603 56.737 43.263 22.28 224 0.875 bicubic -52.173 -41.783 +64
118 efficientnet_b2_pruned 40.383 59.617 56.537 43.463 8.31 260 0.890 bicubic -53.417 -42.303 -12
119 wide_resnet101_2 40.360 59.640 55.780 44.220 126.89 224 0.875 bilinear -53.370 -43.030 -4
120 tf_efficientnet_b0_ap 40.337 59.663 56.787 43.213 5.29 224 0.875 bicubic -52.273 -41.583 +59
121 xception65 40.273 59.727 55.283 44.717 39.92 299 0.903 bicubic -53.487 -43.577 -8
122 regnetx_160 40.270 59.730 56.050 43.950 54.28 224 0.875 bicubic -53.610 -43.040 -22
123 densenet201 40.267 59.733 56.710 43.290 20.01 224 0.875 bicubic -52.423 -41.940 +53
124 resnext50d_32x4d 40.170 59.830 55.487 44.513 25.05 224 0.875 bicubic -53.640 -43.253 -19
125 hrnet_w48 40.093 59.907 56.640 43.360 77.47 224 0.875 bilinear -53.937 -42.400 -35
126 hrnet_w30 40.030 59.970 57.093 42.907 37.71 224 0.875 bilinear -53.340 -41.737 +19
127 regnetx_080 40.000 60.000 55.977 44.023 39.57 224 0.875 bicubic -53.790 -42.933 -19
128 tf_efficientnet_b1 39.977 60.023 56.137 43.863 7.79 240 0.882 bicubic -53.733 -42.663 -10
129 gluon_resnet101_v1c 39.953 60.047 55.300 44.700 44.57 224 0.875 bicubic -53.737 -43.460 -10
130 res2net101_26w_4s 39.717 60.283 54.550 45.450 45.21 224 0.875 bilinear -53.803 -44.050 +6
131 regnetx_120 39.687 60.313 55.633 44.367 46.11 224 0.875 bicubic -54.583 -43.557 -62
132 hrnet_w44 39.677 60.323 55.333 44.667 67.06 224 0.875 bilinear -53.943 -43.627 -5
133 densenet161 39.620 60.380 56.133 43.867 28.68 224 0.875 bicubic -53.280 -42.587 +35
134 mixnet_xl 39.617 60.383 55.887 44.113 11.90 224 0.875 bicubic -54.613 -42.933 -62
135 xception41 39.610 60.390 55.037 44.963 26.97 299 0.903 bicubic -53.870 -43.713 +3
136 res2net50_26w_8s 39.603 60.397 54.550 45.450 48.40 224 0.875 bilinear -53.847 -44.150 +7
137 tf_efficientnet_el 39.563 60.437 55.310 44.690 10.59 300 0.904 bicubic -54.887 -43.770 -77
138 dla102x 39.553 60.447 56.323 43.677 26.31 224 0.875 bilinear -53.977 -42.527 -4
139 rexnet_130 39.487 60.513 56.640 43.360 7.56 224 0.875 bicubic -54.183 -42.070 -18
140 hrnet_w32 39.463 60.537 56.123 43.877 41.23 224 0.875 bilinear -53.487 -42.717 +23
141 regnety_064 39.403 60.597 55.773 44.227 30.58 224 0.875 bicubic -54.737 -43.257 -60
142 densenetblur121d 39.380 60.620 56.640 43.360 8.00 224 0.875 bicubic -53.020 -41.770 +46
143 regnety_120 39.347 60.653 55.277 44.723 51.82 224 0.875 bicubic -54.663 -43.743 -52
144 resnet101 39.307 60.693 55.803 44.197 44.55 224 0.875 bilinear -53.573 -42.857 +25
145 regnety_160 39.260 60.740 55.433 44.567 83.59 224 0.875 bicubic -54.860 -43.587 -60
146 tf_inception_v3 39.237 60.763 54.300 45.700 23.83 299 0.875 bicubic -53.963 -44.180 +5
147 gluon_resnet50_v1s 39.233 60.767 55.010 44.990 25.68 224 0.875 bicubic -54.357 -43.830 -18
148 densenet169 39.167 60.833 55.843 44.157 14.15 224 0.875 bicubic -53.133 -42.747 +43
149 efficientnet_b1_pruned 39.010 60.990 55.647 44.353 6.33 240 0.882 bicubic -53.970 -42.883 +12
150 inception_v3 38.960 61.040 53.853 46.147 23.83 299 0.875 bicubic -53.940 -44.957 +16
151 dpn68 38.933 61.067 54.933 45.067 12.61 224 0.875 bicubic -53.307 -43.677 +42
152 regnety_080 38.917 61.083 55.213 44.787 39.18 224 0.875 bicubic -54.973 -43.787 -55
153 dla102 38.833 61.167 55.323 44.677 33.27 224 0.875 bilinear -54.427 -43.457 -7
154 regnety_040 38.820 61.180 55.557 44.443 20.65 224 0.875 bicubic -54.800 -43.393 -26
155 densenet121 38.783 61.217 56.273 43.727 7.98 224 0.875 bicubic -53.157 -42.007 +44
156 res2net50_14w_8s 38.710 61.290 54.077 45.923 25.06 224 0.875 bilinear -54.320 -44.623 +1
157 regnetx_040 38.703 61.297 55.340 44.660 22.12 224 0.875 bicubic -54.977 -43.600 -37
158 res2net50_26w_6s 38.687 61.313 53.743 46.257 37.05 224 0.875 bilinear -54.903 -45.007 -28
159 regnetx_032 38.680 61.320 55.157 44.843 15.30 224 0.875 bicubic -54.570 -43.573 -11
160 wide_resnet50_2 38.637 61.363 54.467 45.533 68.88 224 0.875 bilinear -54.823 -44.483 -18
161 selecsls60 38.623 61.377 55.630 44.370 30.67 224 0.875 bicubic -54.387 -43.200 -2
162 dla60x 38.617 61.383 55.383 44.617 17.35 224 0.875 bilinear -54.573 -43.327 -10
163 tf_efficientnet_b0 38.600 61.400 55.957 44.043 5.29 224 0.875 bicubic -53.800 -42.513 +26
164 dla60_res2net 38.590 61.410 54.560 45.440 20.85 224 0.875 bilinear -54.790 -44.300 -20
165 selecsls60b 38.573 61.427 55.307 44.693 32.77 224 0.875 bicubic -54.927 -43.533 -28
166 dla60_res2next 38.450 61.550 54.950 45.050 17.03 224 0.875 bilinear -55.120 -43.850 -35
167 regnetx_064 38.430 61.570 54.990 45.010 26.21 224 0.875 bicubic -55.200 -44.060 -43
168 tf_efficientnet_cc_b0_4e 38.413 61.587 55.150 44.850 13.31 224 0.875 bicubic -54.427 -43.290 +4
169 gluon_resnet50_v1b 38.407 61.593 54.833 45.167 25.56 224 0.875 bicubic -54.153 -43.717 +13
170 hrnet_w18 38.277 61.723 55.643 44.357 21.30 224 0.875 bilinear -54.483 -43.017 +5
171 regnety_032 38.170 61.830 54.367 45.633 19.44 224 0.875 bicubic -55.290 -44.583 -31
172 mixnet_l 38.160 61.840 54.757 45.243 7.33 224 0.875 bicubic -55.100 -43.943 -25
173 efficientnet_b1 37.843 62.157 53.640 46.360 7.79 240 0.875 bicubic -55.217 -44.900 -18
174 gluon_resnet50_v1c 37.843 62.157 54.123 45.877 25.58 224 0.875 bicubic -55.067 -44.587 -9
175 res2net50_26w_4s 37.827 62.173 53.073 46.927 25.70 224 0.875 bilinear -55.353 -45.597 -22
176 efficientnet_es 37.770 62.230 54.967 45.033 5.44 224 0.875 bicubic -55.140 -43.723 -12
177 resnest14d 37.767 62.233 56.470 43.530 10.61 224 0.875 bilinear -53.363 -41.860 +42
178 tv_resnext50_32x4d 37.750 62.250 54.113 45.887 25.03 224 0.875 bilinear -55.150 -44.217 -11
179 res2next50 37.477 62.523 52.853 47.147 24.67 224 0.875 bilinear -55.673 -45.807 -25
180 resnet34 37.443 62.557 54.297 45.703 21.80 224 0.875 bilinear -53.757 -43.943 +36
181 tf_efficientnet_em 37.283 62.717 54.220 45.780 6.90 240 0.882 bicubic -56.187 -44.530 -42
182 res2net50_48w_2s 37.117 62.883 53.333 46.667 25.29 224 0.875 bilinear -55.673 -45.137 -8
183 dla60 37.073 62.927 54.200 45.800 22.04 224 0.875 bilinear -55.597 -44.430 -6
184 rexnet_100 37.063 62.937 54.020 45.980 4.80 224 0.875 bicubic -55.787 -44.600 -13
185 regnety_016 37.017 62.983 54.093 45.907 11.20 224 0.875 bicubic -55.983 -44.587 -25
186 tf_mixnet_l 36.987 63.013 52.583 47.417 7.33 224 0.875 bicubic -56.053 -45.957 -30
187 tv_densenet121 36.810 63.190 54.033 45.967 7.98 224 0.875 bicubic -54.590 -44.217 +22
188 tf_efficientnet_lite2 36.807 63.193 53.320 46.680 6.09 260 0.890 bicubic -55.783 -45.230 -8
189 mobilenetv2_120d 36.780 63.220 54.047 45.953 5.83 224 0.875 bicubic -55.830 -44.463 -11
190 tf_efficientnet_lite1 36.737 63.263 53.590 46.410 5.42 240 0.882 bicubic -55.573 -44.900 0
191 regnetx_016 36.683 63.317 53.297 46.703 9.19 224 0.875 bicubic -55.857 -45.253 -7
192 efficientnet_b0 36.600 63.400 53.497 46.503 5.29 224 0.875 bicubic -55.880 -45.183 -7
193 skresnet18 36.320 63.680 54.197 45.803 11.96 224 0.875 bicubic -53.840 -43.583 +35
194 tv_resnet50 36.177 63.823 52.803 47.197 25.56 224 0.875 bilinear -55.963 -45.617 +2
195 tv_resnet34 36.087 63.913 53.533 46.467 21.80 224 0.875 bilinear -54.203 -44.447 +32
196 mobilenetv2_140 36.000 64.000 53.943 46.057 6.11 224 0.875 bicubic -56.030 -44.307 +1
197 tf_efficientnet_lite0 35.930 64.070 53.480 46.520 4.65 224 0.875 bicubic -55.370 -44.610 +14
198 selecsls42b 35.813 64.187 52.487 47.513 32.46 224 0.875 bicubic -56.667 -45.953 -12
199 gluon_resnet34_v1b 35.763 64.237 52.187 47.813 21.80 224 0.875 bicubic -55.337 -45.993 +21
200 dla34 35.643 64.357 52.783 47.217 15.74 224 0.875 bilinear -55.597 -45.397 +14
201 mixnet_m 35.640 64.360 52.430 47.570 5.01 224 0.875 bicubic -56.630 -45.920 -9
202 efficientnet_lite0 35.620 64.380 53.657 46.343 4.65 224 0.875 bicubic -55.640 -44.593 +11
203 ssl_resnet18 35.597 64.403 53.740 46.260 11.69 224 0.875 bilinear -55.103 -44.280 +21
204 tf_efficientnet_es 35.563 64.437 52.790 47.210 5.44 224 0.875 bicubic -56.987 -45.720 -21
205 mobilenetv3_rw 35.547 64.453 53.713 46.287 5.48 224 0.875 bicubic -56.003 -44.557 0
206 mobilenetv2_110d 35.293 64.707 52.830 47.170 4.52 224 0.875 bicubic -56.057 -45.360 +4
207 tf_mixnet_m 35.180 64.820 50.987 49.013 5.01 224 0.875 bicubic -57.020 -47.433 -12
208 hrnet_w18_small_v2 35.173 64.827 52.440 47.560 15.60 224 0.875 bilinear -55.997 -45.900 +10
209 ese_vovnet19b_dw 34.840 65.160 52.030 47.970 6.54 224 0.875 bicubic -57.170 -46.480 -11
210 regnety_008 34.807 65.193 51.743 48.257 6.26 224 0.875 bicubic -57.093 -46.677 -10
211 mobilenetv3_large_100 34.603 65.397 52.860 47.140 5.48 224 0.875 bicubic -56.877 -45.460 -5
212 seresnext26d_32x4d 34.543 65.457 51.543 48.457 16.81 224 0.875 bicubic -57.897 -46.997 -25
213 seresnext26tn_32x4d 34.540 65.460 51.377 48.623 16.81 224 0.875 bicubic -58.280 -47.183 -40
214 resnet26d 34.273 65.727 51.687 48.313 16.01 224 0.875 bicubic -57.957 -46.763 -20
215 fbnetc_100 34.253 65.747 51.180 48.820 5.57 224 0.875 bilinear -57.017 -46.650 -3
216 seresnext26t_32x4d 34.210 65.790 51.460 48.540 16.82 224 0.875 bicubic -58.750 -47.020 -54
217 regnety_006 34.150 65.850 51.277 48.723 6.06 224 0.875 bicubic -57.420 -47.153 -13
218 tf_mobilenetv3_large_100 33.950 66.050 51.490 48.510 5.48 224 0.875 bilinear -57.470 -46.770 -10
219 regnetx_008 33.770 66.230 50.547 49.453 7.26 224 0.875 bicubic -57.410 -47.833 -2
220 mnasnet_100 33.763 66.237 51.170 48.830 4.38 224 0.875 bicubic -57.437 -46.880 -5
221 semnasnet_100 33.520 66.480 50.787 49.213 3.89 224 0.875 bicubic -58.140 -47.483 -18
222 resnet26 33.500 66.500 50.927 49.073 16.00 224 0.875 bicubic -57.940 -47.353 -15
223 mixnet_s 33.480 66.520 50.997 49.003 4.13 224 0.875 bicubic -58.300 -47.303 -22
224 spnasnet_100 33.477 66.523 51.267 48.733 4.42 224 0.875 bilinear -57.133 -46.683 +1
225 regnetx_006 33.157 66.843 50.250 49.750 6.20 224 0.875 bicubic -57.603 -47.850 -2
226 resnet18 33.067 66.933 51.170 48.830 11.69 224 0.875 bilinear -55.083 -45.950 +9
227 hrnet_w18_small 32.667 67.333 50.587 49.413 13.19 224 0.875 bilinear -57.213 -47.313 +2
228 mobilenetv2_100 32.523 67.477 50.800 49.200 3.50 224 0.875 bicubic -57.307 -47.030 +2
229 regnetx_004 32.517 67.483 49.343 50.657 5.16 224 0.875 bicubic -56.943 -48.427 +2
230 gluon_resnet18_v1b 32.407 67.593 49.727 50.273 11.69 224 0.875 bicubic -56.253 -47.373 +3
231 regnety_004 32.333 67.667 49.453 50.547 4.34 224 0.875 bicubic -58.447 -48.627 -9
232 tf_mixnet_s 32.183 67.817 48.493 51.507 4.13 224 0.875 bicubic -59.497 -49.747 -30
233 tf_mobilenetv3_large_075 31.867 68.133 49.110 50.890 3.99 224 0.875 bilinear -58.453 -48.760 -7
234 tf_mobilenetv3_large_minimal_100 31.597 68.403 49.337 50.663 3.92 224 0.875 bilinear -57.583 -47.983 -2
235 regnety_002 29.687 70.313 46.787 53.213 3.16 224 0.875 bicubic -58.513 -50.643 -1
236 regnetx_002 28.860 71.140 45.420 54.580 2.68 224 0.875 bicubic -58.520 -51.570 0
237 dla60x_c 28.447 71.553 46.193 53.807 1.32 224 0.875 bilinear -58.663 -50.947 0
238 tf_mobilenetv3_small_100 27.297 72.703 44.420 55.580 2.54 224 0.875 bilinear -58.663 -51.980 0
239 dla46x_c 26.217 73.783 43.780 56.220 1.07 224 0.875 bilinear -59.263 -52.660 0
240 tf_mobilenetv3_small_075 26.200 73.800 43.637 56.363 2.04 224 0.875 bilinear -58.330 -52.253 +1
241 dla46_c 25.490 74.510 43.800 56.200 1.30 224 0.875 bilinear -59.170 -52.400 -1
242 tf_mobilenetv3_small_minimal_100 25.087 74.913 42.930 57.070 2.04 224 0.875 bilinear -57.583 -52.070 0

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model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff
tf_efficientnet_l2_ns,90.563,9.437,98.779,1.221,480.31,800,0.960,bicubic,+2.211,+0.129,0
tf_efficientnet_l2_ns_475,90.537,9.463,98.710,1.290,480.31,475,0.936,bicubic,+2.303,+0.164,0
tf_efficientnet_b7_ns,90.100,9.900,98.614,1.386,66.35,600,0.949,bicubic,+3.260,+0.520,0
tf_efficientnet_b6_ns,89.782,10.218,98.510,1.490,43.04,528,0.942,bicubic,+3.330,+0.628,0
tf_efficientnet_b5_ns,89.651,10.349,98.482,1.518,30.39,456,0.934,bicubic,+3.563,+0.730,0
tf_efficientnet_b8_ap,89.581,10.419,98.305,1.695,87.41,672,0.954,bicubic,+4.211,+1.011,+2
tf_efficientnet_b7_ap,89.429,10.571,98.347,1.653,66.35,600,0.949,bicubic,+4.309,+1.095,+3
tf_efficientnet_b8,89.355,10.645,98.303,1.697,87.41,672,0.954,bicubic,+3.985,+0.913,-1
tf_efficientnet_b6_ap,89.342,10.658,98.281,1.719,43.04,528,0.942,bicubic,+4.554,+1.143,+4
tf_efficientnet_b4_ns,89.305,10.694,98.347,1.653,19.34,380,0.922,bicubic,+4.143,+0.877,-1
ig_resnext101_32x48d,89.120,10.880,98.130,1.870,828.41,224,0.875,bilinear,+3.692,+0.558,-5
ig_resnext101_32x32d,89.111,10.889,98.181,1.819,468.53,224,0.875,bilinear,+4.017,+0.743,-1
tf_efficientnet_b7,89.086,10.914,98.183,1.817,66.35,600,0.949,bicubic,+4.150,+0.979,-1
tf_efficientnet_b5_ap,88.938,11.062,98.164,1.836,30.39,456,0.934,bicubic,+4.686,+1.190,+2
ig_resnext101_32x16d,88.834,11.166,98.049,1.951,194.03,224,0.875,bilinear,+4.664,+0.853,+2
swsl_resnext101_32x8d,88.770,11.230,98.147,1.853,88.79,224,0.875,bilinear,+4.486,+0.971,-1
tf_efficientnet_b6,88.761,11.239,98.064,1.937,43.04,528,0.942,bicubic,+4.651,+1.177,+1
resnest269e,88.522,11.478,98.027,1.973,110.93,416,0.928,bicubic,+4.004,+1.041,-4
resnest200e,88.432,11.568,98.042,1.958,70.20,320,0.909,bicubic,+4.600,+1.148,+1
tf_efficientnet_b3_ns,88.426,11.574,98.029,1.971,12.23,300,0.904,bicubic,+4.378,+1.119,-1
tf_efficientnet_b4_ap,88.349,11.651,97.893,2.107,19.34,380,0.922,bicubic,+5.101,+1.501,+2
tf_efficientnet_b5,88.321,11.679,97.912,2.088,30.39,456,0.934,bicubic,+4.509,+1.164,-1
ig_resnext101_32x8d,88.146,11.854,97.856,2.144,88.79,224,0.875,bilinear,+5.458,+1.220,+6
swsl_resnext101_32x4d,88.099,11.901,97.967,2.033,44.18,224,0.875,bilinear,+4.869,+1.207,0
tf_efficientnet_b4,87.963,12.037,97.739,2.261,19.34,380,0.922,bicubic,+4.941,+1.439,+1
tresnet_xl_448,87.796,12.204,97.459,2.541,78.44,448,0.875,bilinear,+4.746,+1.285,-1
pnasnet5large,87.636,12.364,97.485,2.515,86.06,331,0.911,bicubic,+4.854,+1.445,+1
swsl_resnext101_32x16d,87.615,12.386,97.820,2.180,194.03,224,0.875,bilinear,+4.269,+0.974,-6
swsl_resnext50_32x4d,87.600,12.400,97.651,2.349,25.03,224,0.875,bilinear,+5.418,+1.421,+4
tf_efficientnet_b2_ns,87.557,12.443,97.628,2.372,9.11,260,0.890,bicubic,+5.177,+1.380,+1
tresnet_l_448,87.377,12.623,97.485,2.515,55.99,448,0.875,bilinear,+5.110,+1.509,+1
nasnetalarge,87.350,12.650,97.417,2.583,88.75,331,0.911,bicubic,+4.730,+1.371,-2
ecaresnet101d,87.288,12.712,97.562,2.438,44.57,224,0.875,bicubic,+5.116,+1.516,+1
resnest101e,87.284,12.716,97.560,2.440,48.28,256,0.875,bilinear,+4.394,+1.240,-7
tresnet_xl,87.224,12.776,97.400,2.600,78.44,224,0.875,bilinear,+5.170,+1.463,0
tf_efficientnet_b3_ap,87.192,12.808,97.380,2.620,12.23,300,0.904,bicubic,+5.370,+1.756,+2
efficientnet_b3a,86.993,13.007,97.397,2.603,12.23,320,1.000,bicubic,+5.127,+1.561,-1
ssl_resnext101_32x16d,86.856,13.143,97.517,2.483,194.03,224,0.875,bilinear,+5.013,+1.421,-1
rexnet_200,86.846,13.154,97.276,2.724,16.37,224,0.875,bicubic,+5.214,+1.608,+2
tf_efficientnet_b3,86.835,13.165,97.297,2.703,12.23,300,0.904,bicubic,+5.199,+1.579,0
tresnet_m_448,86.820,13.180,97.212,2.788,31.39,448,0.875,bilinear,+5.106,+1.640,-2
ssl_resnext101_32x8d,86.807,13.193,97.466,2.534,88.79,224,0.875,bilinear,+5.191,+1.428,0
swsl_resnet50,86.807,13.193,97.498,2.502,25.56,224,0.875,bilinear,+5.641,+1.526,+5
tf_efficientnet_lite4,86.803,13.197,97.263,2.737,13.01,380,0.920,bilinear,+5.267,+1.595,-1
efficientnet_b3,86.782,13.218,97.288,2.712,12.23,300,0.904,bicubic,+5.288,+1.572,-1
tresnet_l,86.767,13.233,97.271,2.729,55.99,224,0.875,bilinear,+5.279,+1.647,-1
tf_efficientnet_b1_ns,86.669,13.331,97.378,2.622,7.79,240,0.882,bicubic,+5.281,+1.640,-1
resnest50d_4s2x40d,86.592,13.408,97.269,2.731,30.42,224,0.875,bicubic,+5.484,+1.711,+1
efficientnet_b3_pruned,86.581,13.419,97.190,2.810,9.86,300,0.904,bicubic,+5.723,+1.948,+7
ssl_resnext101_32x4d,86.479,13.521,97.468,2.532,44.18,224,0.875,bilinear,+5.555,+1.740,+3
ecaresnet50d,86.470,13.530,97.186,2.814,25.58,224,0.875,bicubic,+5.878,+1.866,+11
gluon_resnet152_v1s,86.468,13.532,97.109,2.891,60.32,224,0.875,bicubic,+5.452,+1.697,-2
resnest50d_1s4x24d,86.447,13.553,97.148,2.852,25.68,224,0.875,bicubic,+5.459,+1.826,-2
efficientnet_b2a,86.304,13.696,96.990,3.010,9.11,288,1.000,bicubic,+5.692,+1.672,+6
gluon_senet154,86.278,13.722,96.949,3.051,115.09,224,0.875,bicubic,+5.044,+1.601,-8
resnest50d,86.240,13.761,97.073,2.927,27.48,224,0.875,bilinear,+5.266,+1.695,-4
ecaresnet101d_pruned,86.210,13.790,97.335,2.665,24.88,224,0.875,bicubic,+5.392,+1.707,0
tresnet_m,86.199,13.801,96.667,3.333,31.39,224,0.875,bilinear,+5.397,+1.807,+1
cspdarknet53,86.182,13.818,97.013,2.987,27.64,256,0.887,bilinear,+6.124,+1.929,+24
inception_v4,86.169,13.831,96.919,3.081,42.68,299,0.875,bicubic,+6.001,+1.951,+19
rexnet_150,86.154,13.846,97.058,2.942,9.73,224,0.875,bicubic,+5.844,+1.892,+12
tf_efficientnet_el,86.148,13.852,96.987,3.013,10.59,300,0.904,bicubic,+5.708,+1.823,+5
inception_resnet_v2,86.133,13.867,97.043,2.957,55.84,299,0.897,bicubic,+5.675,+1.737,+3
ssl_resnext50_32x4d,86.086,13.914,97.212,2.788,25.03,224,0.875,bilinear,+5.768,+1.806,+8
efficientnet_b2,86.056,13.944,96.917,3.083,9.11,260,0.875,bicubic,+5.664,+1.841,+4
gluon_resnet101_v1s,86.054,13.946,97.022,2.978,44.67,224,0.875,bicubic,+5.752,+1.862,+8
ecaresnetlight,86.052,13.948,97.069,2.931,30.16,224,0.875,bicubic,+5.590,+1.819,-2
gluon_seresnext101_32x4d,86.032,13.968,96.977,3.023,48.96,224,0.875,bicubic,+5.128,+1.683,-14
tf_efficientnet_b2_ap,85.975,14.025,96.810,3.190,9.11,260,0.890,bicubic,+5.675,+1.782,+6
gluon_seresnext101_64x4d,85.960,14.040,96.979,3.021,88.23,224,0.875,bicubic,+5.066,+1.671,-15
gluon_resnet152_v1d,85.917,14.083,96.812,3.188,60.21,224,0.875,bicubic,+5.443,+1.606,-7
tf_efficientnet_b2,85.902,14.098,96.862,3.139,9.11,260,0.890,bicubic,+5.816,+1.954,+10
seresnet50,85.857,14.143,97.004,2.995,28.09,224,0.875,bicubic,+5.583,+1.934,+4
gluon_resnet101_v1d,85.849,14.151,96.663,3.337,44.57,224,0.875,bicubic,+5.435,+1.649,-6
resnet50,85.804,14.196,96.712,3.288,25.56,224,0.875,bicubic,+6.766,+2.322,+50
mixnet_xl,85.798,14.202,96.712,3.288,11.90,224,0.875,bicubic,+5.322,+1.776,-13
ens_adv_inception_resnet_v2,85.781,14.220,96.759,3.241,55.84,299,0.897,bicubic,+5.799,+1.823,+9
tf_efficientnet_lite3,85.755,14.245,96.887,3.113,8.20,300,0.904,bilinear,+5.935,+1.973,+16
ese_vovnet39b,85.751,14.249,96.891,3.109,24.57,224,0.875,bicubic,+6.431,+2.179,+30
gluon_resnext101_32x4d,85.746,14.254,96.635,3.365,44.18,224,0.875,bicubic,+5.412,+1.709,-9
cspresnext50,85.740,14.260,96.840,3.160,20.57,224,0.875,bilinear,+5.700,+1.896,+3
regnety_320,85.727,14.273,96.725,3.275,145.05,224,0.875,bicubic,+4.915,+1.481,-24
xception71,85.697,14.303,96.776,3.224,42.34,299,0.903,bicubic,+5.823,+1.854,+8
gluon_resnext101_64x4d,85.693,14.307,96.644,3.356,83.46,224,0.875,bicubic,+5.089,+1.656,-23
efficientnet_b2_pruned,85.642,14.358,96.746,3.254,8.31,260,0.890,bicubic,+5.726,+1.890,+3
dpn107,85.640,14.360,96.729,3.271,86.92,224,0.875,bicubic,+5.484,+1.819,-6
ecaresnet50d_pruned,85.580,14.420,96.936,3.064,19.94,224,0.875,bicubic,+5.864,+2.056,+10
gluon_resnet152_v1c,85.580,14.420,96.646,3.354,60.21,224,0.875,bicubic,+5.670,+1.806,+1
resnext50d_32x4d,85.569,14.431,96.748,3.252,25.05,224,0.875,bicubic,+5.893,+1.882,+11
regnety_120,85.543,14.457,96.785,3.215,51.82,224,0.875,bicubic,+5.177,+1.659,-20
regnetx_320,85.524,14.476,96.669,3.331,107.81,224,0.875,bicubic,+5.278,+1.643,-13
regnety_160,85.501,14.499,96.620,3.380,83.59,224,0.875,bicubic,+5.205,+1.658,-16
dpn92,85.494,14.506,96.635,3.365,37.67,224,0.875,bicubic,+5.486,+1.799,-8
gluon_resnet152_v1b,85.475,14.525,96.550,3.450,60.19,224,0.875,bicubic,+5.789,+1.814,+5
rexnet_130,85.473,14.527,96.684,3.316,7.56,224,0.875,bicubic,+5.973,+2.002,+10
dpn131,85.398,14.602,96.639,3.361,79.25,224,0.875,bicubic,+5.576,+1.929,-3
regnetx_160,85.390,14.610,96.637,3.363,54.28,224,0.875,bicubic,+5.534,+1.807,-5
dla102x2,85.366,14.634,96.629,3.371,41.28,224,0.875,bilinear,+5.918,+1.989,+9
gluon_seresnext50_32x4d,85.336,14.664,96.667,3.333,27.56,224,0.875,bicubic,+5.418,+1.845,-12
xception65,85.315,14.685,96.637,3.363,39.92,299,0.903,bicubic,+5.763,+1.983,+3
skresnext50_32x4d,85.313,14.687,96.390,3.610,27.48,224,0.875,bicubic,+5.157,+1.748,-20
dpn98,85.311,14.689,96.469,3.531,61.57,224,0.875,bicubic,+5.669,+1.871,-1
gluon_resnet101_v1c,85.304,14.696,96.405,3.595,44.57,224,0.875,bicubic,+5.770,+1.827,+1
dpn68b,85.291,14.709,96.464,3.536,12.61,224,0.875,bicubic,+6.075,+2.050,+14
resnetblur50,85.283,14.717,96.531,3.470,25.56,224,0.875,bicubic,+5.997,+1.893,+8
regnety_064,85.283,14.717,96.639,3.361,30.58,224,0.875,bicubic,+5.561,+1.871,-9
regnety_080,85.245,14.755,96.633,3.367,39.18,224,0.875,bicubic,+5.369,+1.803,-17
resnext50_32x4d,85.221,14.779,96.526,3.474,25.03,224,0.875,bicubic,+5.453,+1.928,-13
resnext101_32x8d,85.187,14.813,96.445,3.555,88.79,224,0.875,bilinear,+5.879,+1.927,+1
gluon_inception_v3,85.183,14.817,96.526,3.474,23.83,299,0.875,bicubic,+6.377,+2.156,+22
hrnet_w48,85.151,14.849,96.492,3.508,77.47,224,0.875,bilinear,+5.851,+1.980,+2
gluon_xception65,85.148,14.851,96.597,3.403,39.92,299,0.903,bicubic,+5.432,+1.737,-14
gluon_resnet101_v1b,85.142,14.858,96.366,3.634,44.55,224,0.875,bicubic,+5.836,+1.842,-1
regnetx_120,85.131,14.869,96.477,3.523,46.11,224,0.875,bicubic,+5.535,+1.739,-12
xception,85.129,14.871,96.471,3.529,22.86,299,0.897,bicubic,+6.077,+2.079,+9
tf_efficientnet_b1_ap,85.127,14.873,96.405,3.595,7.79,240,0.882,bicubic,+5.847,+2.099,-1
hrnet_w64,85.119,14.881,96.744,3.256,128.06,224,0.875,bilinear,+5.645,+2.092,-11
ssl_resnet50,85.097,14.903,96.866,3.134,25.56,224,0.875,bilinear,+5.875,+2.034,-2
res2net101_26w_4s,85.093,14.907,96.381,3.619,45.21,224,0.875,bilinear,+5.895,+1.949,+1
tf_efficientnet_cc_b1_8e,85.063,14.937,96.422,3.578,39.72,240,0.882,bicubic,+5.755,+2.052,-9
res2net50_26w_8s,85.029,14.971,96.419,3.580,48.40,224,0.875,bilinear,+5.831,+2.052,-2
resnest26d,85.008,14.992,96.637,3.363,17.07,224,0.875,bilinear,+6.530,+2.339,+21
gluon_resnext50_32x4d,84.995,15.005,96.426,3.574,25.03,224,0.875,bicubic,+5.641,+2.000,-15
tf_efficientnet_b0_ns,84.984,15.016,96.503,3.497,5.29,224,0.875,bicubic,+6.326,+2.127,+14
regnety_040,84.948,15.052,96.612,3.388,20.65,224,0.875,bicubic,+5.728,+1.956,-8
tf_efficientnet_em,84.926,15.074,96.424,3.576,6.90,240,0.882,bicubic,+6.218,+2.110,+9
dla169,84.920,15.080,96.535,3.465,53.39,224,0.875,bilinear,+6.232,+2.199,+10
tf_efficientnet_b1,84.918,15.082,96.364,3.636,7.79,240,0.882,bicubic,+6.092,+2.166,+3
hrnet_w44,84.884,15.116,96.434,3.566,67.06,224,0.875,bilinear,+5.988,+2.066,-1
gluon_resnet50_v1s,84.862,15.138,96.443,3.557,25.68,224,0.875,bicubic,+6.150,+2.205,+4
regnetx_080,84.862,15.138,96.434,3.566,39.57,224,0.875,bicubic,+5.668,+1.874,-10
gluon_resnet50_v1d,84.832,15.168,96.398,3.602,25.58,224,0.875,bicubic,+5.758,+1.928,-10
dla60_res2next,84.830,15.170,96.411,3.589,17.03,224,0.875,bilinear,+6.390,+2.259,+14
mixnet_l,84.822,15.178,96.328,3.672,7.33,224,0.875,bicubic,+5.846,+2.146,-8
resnet152,84.815,15.185,96.225,3.775,60.19,224,0.875,bilinear,+6.503,+2.187,+14
dla102x,84.813,15.187,96.552,3.448,26.31,224,0.875,bilinear,+6.303,+2.324,+4
dla60_res2net,84.813,15.187,96.481,3.519,20.85,224,0.875,bilinear,+6.349,+2.275,+9
xception41,84.792,15.208,96.413,3.587,26.97,299,0.903,bicubic,+6.276,+2.135,+2
regnetx_064,84.781,15.219,96.490,3.510,26.21,224,0.875,bicubic,+5.709,+2.032,-16
hrnet_w40,84.743,15.257,96.554,3.446,57.56,224,0.875,bilinear,+5.823,+2.084,-13
res2net50_26w_6s,84.726,15.274,96.281,3.719,37.05,224,0.875,bilinear,+6.156,+2.157,-2
selecsls60b,84.657,15.343,96.300,3.700,32.77,224,0.875,bicubic,+6.245,+2.126,+6
hrnet_w32,84.651,15.349,96.407,3.593,41.23,224,0.875,bilinear,+6.201,+2.221,+3
regnety_032,84.606,15.394,96.424,3.576,19.44,224,0.875,bicubic,+5.720,+2.012,-15
regnetx_040,84.600,15.400,96.383,3.617,22.12,224,0.875,bicubic,+6.118,+2.139,-3
efficientnet_es,84.591,15.409,96.311,3.689,5.44,224,0.875,bicubic,+6.525,+2.385,+10
hrnet_w30,84.572,15.428,96.388,3.612,37.71,224,0.875,bilinear,+6.366,+2.165,+6
tf_mixnet_l,84.564,15.437,96.244,3.756,7.33,224,0.875,bicubic,+5.790,+2.246,-15
wide_resnet101_2,84.557,15.443,96.349,3.651,126.89,224,0.875,bilinear,+5.701,+2.067,-19
efficientnet_b1,84.531,15.469,96.153,3.847,7.79,240,0.875,bicubic,+5.833,+2.009,-14
dla60x,84.523,15.477,96.285,3.715,17.35,224,0.875,bilinear,+6.277,+2.267,-1
wide_resnet50_2,84.427,15.573,96.257,3.743,68.88,224,0.875,bilinear,+5.949,+2.163,-8
efficientnet_b1_pruned,84.393,15.607,96.140,3.860,6.33,240,0.882,bicubic,+6.157,+2.306,-1
res2net50_26w_4s,84.365,15.635,96.082,3.918,25.70,224,0.875,bilinear,+6.401,+2.228,+8
res2net50_14w_8s,84.309,15.691,96.072,3.929,25.06,224,0.875,bilinear,+6.159,+2.224,0
selecsls60,84.288,15.712,96.095,3.905,30.67,224,0.875,bicubic,+6.306,+2.267,+5
regnetx_032,84.237,15.763,96.247,3.753,15.30,224,0.875,bicubic,+6.065,+2.159,-3
res2next50,84.226,15.774,95.997,4.003,24.67,224,0.875,bilinear,+5.980,+2.105,-7
gluon_resnet50_v1c,84.207,15.793,96.161,3.839,25.58,224,0.875,bicubic,+6.195,+2.173,-1
dla102,84.190,15.810,96.206,3.794,33.27,224,0.875,bilinear,+6.158,+2.260,-3
rexnet_100,84.162,15.838,96.255,3.745,4.80,224,0.875,bicubic,+6.304,+2.385,+4
tf_inception_v3,84.136,15.864,95.918,4.082,23.83,299,0.875,bicubic,+6.278,+2.280,+4
res2net50_48w_2s,84.126,15.874,95.965,4.035,25.29,224,0.875,bilinear,+6.604,+2.411,+9
tf_efficientnet_lite2,84.094,15.906,96.069,3.931,6.09,260,0.890,bicubic,+6.626,+2.315,+9
efficientnet_b0,84.038,15.962,95.956,4.044,5.29,224,0.875,bicubic,+6.340,+2.424,+2
seresnext26t_32x4d,84.004,15.996,95.852,4.148,16.82,224,0.875,bicubic,+6.006,+2.144,-7
tf_efficientnet_cc_b0_8e,83.966,16.034,96.065,3.935,24.01,224,0.875,bicubic,+6.058,+2.411,-4
tv_resnext50_32x4d,83.959,16.041,95.960,4.040,25.03,224,0.875,bilinear,+6.339,+2.264,0
regnety_016,83.955,16.045,96.005,3.995,11.20,224,0.875,bicubic,+6.093,+2.285,-5
gluon_resnet50_v1b,83.940,16.060,96.012,3.988,25.56,224,0.875,bicubic,+6.360,+2.296,+1
densenet161,83.906,16.094,96.010,3.990,28.68,224,0.875,bicubic,+6.548,+2.372,+5
adv_inception_v3,83.902,16.098,95.935,4.065,23.83,299,0.875,bicubic,+6.320,+2.199,-2
mobilenetv2_120d,83.893,16.107,95.909,4.091,5.83,224,0.875,bicubic,+6.609,+2.417,+6
seresnext26tn_32x4d,83.878,16.122,95.931,4.069,16.81,224,0.875,bicubic,+5.892,+2.185,-14
resnet101,83.848,16.152,95.892,4.108,44.55,224,0.875,bilinear,+6.474,+2.352,0
inception_v3,83.761,16.239,95.879,4.121,23.83,299,0.875,bicubic,+6.321,+2.403,-2
seresnext26d_32x4d,83.754,16.246,95.849,4.151,16.81,224,0.875,bicubic,+6.152,+2.241,-8
dla60,83.729,16.271,95.933,4.067,22.04,224,0.875,bilinear,+6.697,+2.615,+6
tf_efficientnet_b0_ap,83.650,16.350,95.779,4.221,5.29,224,0.875,bicubic,+6.564,+2.523,+4
tf_efficientnet_es,83.647,16.352,95.939,4.061,5.44,224,0.875,bicubic,+6.389,+2.345,+1
skresnet34,83.641,16.359,95.933,4.067,22.28,224,0.875,bicubic,+6.729,+2.611,+6
tf_efficientnet_cc_b0_4e,83.639,16.361,95.740,4.260,13.31,224,0.875,bicubic,+6.333,+2.406,-5
densenet201,83.556,16.444,95.811,4.189,20.01,224,0.875,bicubic,+6.270,+2.333,-5
mixnet_m,83.515,16.485,95.689,4.311,5.01,224,0.875,bicubic,+6.255,+2.265,-4
tf_efficientnet_b0,83.515,16.485,95.719,4.281,5.29,224,0.875,bicubic,+6.667,+2.491,+3
hrnet_w18,83.500,16.500,95.907,4.093,21.30,224,0.875,bilinear,+6.742,+2.463,+4
densenetblur121d,83.472,16.527,95.822,4.178,8.00,224,0.875,bicubic,+6.884,+2.630,+6
selecsls42b,83.457,16.543,95.745,4.255,32.46,224,0.875,bicubic,+6.284,+2.355,-6
tf_efficientnet_lite1,83.344,16.656,95.642,4.358,5.42,240,0.882,bicubic,+6.702,+2.416,+3
regnetx_016,83.195,16.805,95.740,4.260,9.19,224,0.875,bicubic,+6.245,+2.320,-5
mobilenetv2_140,83.182,16.818,95.689,4.311,6.11,224,0.875,bicubic,+6.666,+2.693,+3
dpn68,83.178,16.822,95.597,4.402,12.61,224,0.875,bicubic,+6.860,+2.620,+3
tf_mixnet_m,83.176,16.824,95.461,4.539,5.01,224,0.875,bicubic,+6.234,+2.309,-7
ese_vovnet19b_dw,83.109,16.890,95.779,4.221,6.54,224,0.875,bicubic,+6.311,+2.511,-5
resnet26d,83.050,16.950,95.604,4.396,16.01,224,0.875,bicubic,+6.354,+2.454,-4
tv_resnet50,82.958,17.042,95.467,4.533,25.56,224,0.875,bilinear,+6.820,+2.603,+1
densenet121,82.823,17.177,95.585,4.415,7.98,224,0.875,bicubic,+7.245,+2.933,+6
densenet169,82.683,17.317,95.600,4.400,14.15,224,0.875,bicubic,+6.776,+2.574,+1
mixnet_s,82.525,17.476,95.356,4.644,4.13,224,0.875,bicubic,+6.532,+2.560,-1
regnety_008,82.493,17.508,95.487,4.513,6.26,224,0.875,bicubic,+6.177,+2.421,-4
efficientnet_lite0,82.382,17.619,95.279,4.721,4.65,224,0.875,bicubic,+6.898,+2.769,+5
resnest14d,82.352,17.648,95.339,4.661,10.61,224,0.875,bilinear,+6.846,+2.821,+3
mobilenetv3_rw,82.275,17.725,95.234,4.766,5.48,224,0.875,bicubic,+6.641,+2.526,-1
semnasnet_100,82.251,17.749,95.230,4.770,3.89,224,0.875,bicubic,+6.803,+2.626,+3
mobilenetv3_large_100,82.177,17.823,95.196,4.804,5.48,224,0.875,bicubic,+6.410,+2.654,-5
resnet34,82.138,17.862,95.130,4.870,21.80,224,0.875,bilinear,+7.028,+2.846,+6
mobilenetv2_110d,82.070,17.930,95.076,4.923,4.52,224,0.875,bicubic,+7.034,+2.890,+7
tf_mixnet_s,82.038,17.962,95.121,4.879,4.13,224,0.875,bicubic,+6.388,+2.493,-7
hrnet_w18_small_v2,81.961,18.039,95.164,4.836,15.60,224,0.875,bilinear,+6.847,+2.748,+2
tf_efficientnet_lite0,81.952,18.048,95.168,4.832,4.65,224,0.875,bicubic,+7.122,+2.992,+5
resnet26,81.944,18.056,95.241,4.759,16.00,224,0.875,bicubic,+6.652,+2.671,-3
tf_mobilenetv3_large_100,81.848,18.152,95.070,4.930,5.48,224,0.875,bilinear,+6.330,+2.464,-8
tv_densenet121,81.726,18.274,95.034,4.966,7.98,224,0.875,bicubic,+6.988,+2.884,+3
regnety_006,81.700,18.300,95.115,4.885,6.06,224,0.875,bicubic,+6.454,+2.583,-5
dla34,81.658,18.342,94.878,5.122,15.74,224,0.875,bilinear,+7.028,+2.800,+3
fbnetc_100,81.559,18.441,94.970,5.030,5.57,224,0.875,bilinear,+6.436,+2.584,-6
gluon_resnet34_v1b,81.500,18.500,94.810,5.190,21.80,224,0.875,bicubic,+6.912,+2.820,+2
regnetx_008,81.485,18.515,95.059,4.941,7.26,224,0.875,bicubic,+6.447,+2.724,-5
mnasnet_100,81.459,18.541,94.899,5.101,4.38,224,0.875,bicubic,+6.801,+2.785,-2
spnasnet_100,80.878,19.122,94.526,5.474,4.42,224,0.875,bilinear,+6.794,+2.708,0
regnety_004,80.659,19.341,94.686,5.314,4.34,224,0.875,bicubic,+6.625,+2.934,0
skresnet18,80.637,19.363,94.378,5.622,11.96,224,0.875,bicubic,+7.599,+3.210,+4
regnetx_006,80.629,19.371,94.524,5.476,6.20,224,0.875,bicubic,+6.777,+2.852,-1
swsl_resnet18,80.575,19.425,94.743,5.256,11.69,224,0.875,bilinear,+7.299,+3.010,+1
tv_resnet34,80.389,19.611,94.436,5.564,21.80,224,0.875,bilinear,+7.077,+3.010,-1
mobilenetv2_100,80.257,19.743,94.195,5.805,3.50,224,0.875,bicubic,+7.287,+3.179,+1
ssl_resnet18,80.101,19.899,94.590,5.410,11.69,224,0.875,bilinear,+7.491,+3.174,+1
tf_mobilenetv3_large_075,80.093,19.907,94.184,5.816,3.99,224,0.875,bilinear,+6.655,+2.834,-5
hrnet_w18_small,79.557,20.443,93.898,6.102,13.19,224,0.875,bilinear,+7.215,+3.220,+1
regnetx_004,79.435,20.565,93.853,6.147,5.16,224,0.875,bicubic,+7.039,+3.023,-1
tf_mobilenetv3_large_minimal_100,79.222,20.778,93.706,6.294,3.92,224,0.875,bilinear,+6.974,+3.076,0
gluon_resnet18_v1b,78.372,21.628,93.138,6.862,11.69,224,0.875,bicubic,+7.536,+3.376,0
regnety_002,77.405,22.595,92.914,7.086,3.16,224,0.875,bicubic,+7.153,+3.374,0
resnet18,77.276,22.724,92.756,7.244,11.69,224,0.875,bilinear,+7.528,+3.678,0
regnetx_002,76.124,23.876,92.211,7.789,2.68,224,0.875,bicubic,+7.362,+3.655,0
dla60x_c,75.637,24.363,92.177,7.823,1.32,224,0.875,bilinear,+7.745,+3.751,+1
tf_mobilenetv3_small_100,74.717,25.283,91.257,8.743,2.54,224,0.875,bilinear,+6.795,+3.593,-1
dla46x_c,73.647,26.353,91.095,8.905,1.07,224,0.875,bilinear,+7.677,+4.115,0
tf_mobilenetv3_small_075,72.812,27.188,90.036,9.964,2.04,224,0.875,bilinear,+7.096,+3.906,0
dla46_c,72.601,27.399,90.499,9.501,1.30,224,0.875,bilinear,+7.735,+4.207,0
tf_mobilenetv3_small_minimal_100,70.111,29.889,88.505,11.495,2.04,224,0.875,bilinear,+7.205,+4.275,0
1 model top1 top1_err top5 top5_err param_count img_size cropt_pct interpolation top1_diff top5_diff rank_diff
2 tf_efficientnet_l2_ns 90.563 9.437 98.779 1.221 480.31 800 0.960 bicubic +2.211 +0.129 0
3 tf_efficientnet_l2_ns_475 90.537 9.463 98.710 1.290 480.31 475 0.936 bicubic +2.303 +0.164 0
4 tf_efficientnet_b7_ns 90.100 9.900 98.614 1.386 66.35 600 0.949 bicubic +3.260 +0.520 0
5 tf_efficientnet_b6_ns 89.782 10.218 98.510 1.490 43.04 528 0.942 bicubic +3.330 +0.628 0
6 tf_efficientnet_b5_ns 89.651 10.349 98.482 1.518 30.39 456 0.934 bicubic +3.563 +0.730 0
7 tf_efficientnet_b8_ap 89.581 10.419 98.305 1.695 87.41 672 0.954 bicubic +4.211 +1.011 +2
8 tf_efficientnet_b7_ap 89.429 10.571 98.347 1.653 66.35 600 0.949 bicubic +4.309 +1.095 +3
9 tf_efficientnet_b8 89.355 10.645 98.303 1.697 87.41 672 0.954 bicubic +3.985 +0.913 -1
10 tf_efficientnet_b6_ap 89.342 10.658 98.281 1.719 43.04 528 0.942 bicubic +4.554 +1.143 +4
11 tf_efficientnet_b4_ns 89.305 10.694 98.347 1.653 19.34 380 0.922 bicubic +4.143 +0.877 -1
12 ig_resnext101_32x48d 89.120 10.880 98.130 1.870 828.41 224 0.875 bilinear +3.692 +0.558 -5
13 ig_resnext101_32x32d 89.111 10.889 98.181 1.819 468.53 224 0.875 bilinear +4.017 +0.743 -1
14 tf_efficientnet_b7 89.086 10.914 98.183 1.817 66.35 600 0.949 bicubic +4.150 +0.979 -1
15 tf_efficientnet_b5_ap 88.938 11.062 98.164 1.836 30.39 456 0.934 bicubic +4.686 +1.190 +2
16 ig_resnext101_32x16d 88.834 11.166 98.049 1.951 194.03 224 0.875 bilinear +4.664 +0.853 +2
17 swsl_resnext101_32x8d 88.770 11.230 98.147 1.853 88.79 224 0.875 bilinear +4.486 +0.971 -1
18 tf_efficientnet_b6 88.761 11.239 98.064 1.937 43.04 528 0.942 bicubic +4.651 +1.177 +1
19 resnest269e 88.522 11.478 98.027 1.973 110.93 416 0.928 bicubic +4.004 +1.041 -4
20 resnest200e 88.432 11.568 98.042 1.958 70.20 320 0.909 bicubic +4.600 +1.148 +1
21 tf_efficientnet_b3_ns 88.426 11.574 98.029 1.971 12.23 300 0.904 bicubic +4.378 +1.119 -1
22 tf_efficientnet_b4_ap 88.349 11.651 97.893 2.107 19.34 380 0.922 bicubic +5.101 +1.501 +2
23 tf_efficientnet_b5 88.321 11.679 97.912 2.088 30.39 456 0.934 bicubic +4.509 +1.164 -1
24 ig_resnext101_32x8d 88.146 11.854 97.856 2.144 88.79 224 0.875 bilinear +5.458 +1.220 +6
25 swsl_resnext101_32x4d 88.099 11.901 97.967 2.033 44.18 224 0.875 bilinear +4.869 +1.207 0
26 tf_efficientnet_b4 87.963 12.037 97.739 2.261 19.34 380 0.922 bicubic +4.941 +1.439 +1
27 tresnet_xl_448 87.796 12.204 97.459 2.541 78.44 448 0.875 bilinear +4.746 +1.285 -1
28 pnasnet5large 87.636 12.364 97.485 2.515 86.06 331 0.911 bicubic +4.854 +1.445 +1
29 swsl_resnext101_32x16d 87.615 12.386 97.820 2.180 194.03 224 0.875 bilinear +4.269 +0.974 -6
30 swsl_resnext50_32x4d 87.600 12.400 97.651 2.349 25.03 224 0.875 bilinear +5.418 +1.421 +4
31 tf_efficientnet_b2_ns 87.557 12.443 97.628 2.372 9.11 260 0.890 bicubic +5.177 +1.380 +1
32 tresnet_l_448 87.377 12.623 97.485 2.515 55.99 448 0.875 bilinear +5.110 +1.509 +1
33 nasnetalarge 87.350 12.650 97.417 2.583 88.75 331 0.911 bicubic +4.730 +1.371 -2
34 ecaresnet101d 87.288 12.712 97.562 2.438 44.57 224 0.875 bicubic +5.116 +1.516 +1
35 resnest101e 87.284 12.716 97.560 2.440 48.28 256 0.875 bilinear +4.394 +1.240 -7
36 tresnet_xl 87.224 12.776 97.400 2.600 78.44 224 0.875 bilinear +5.170 +1.463 0
37 tf_efficientnet_b3_ap 87.192 12.808 97.380 2.620 12.23 300 0.904 bicubic +5.370 +1.756 +2
38 efficientnet_b3a 86.993 13.007 97.397 2.603 12.23 320 1.000 bicubic +5.127 +1.561 -1
39 ssl_resnext101_32x16d 86.856 13.143 97.517 2.483 194.03 224 0.875 bilinear +5.013 +1.421 -1
40 rexnet_200 86.846 13.154 97.276 2.724 16.37 224 0.875 bicubic +5.214 +1.608 +2
41 tf_efficientnet_b3 86.835 13.165 97.297 2.703 12.23 300 0.904 bicubic +5.199 +1.579 0
42 tresnet_m_448 86.820 13.180 97.212 2.788 31.39 448 0.875 bilinear +5.106 +1.640 -2
43 ssl_resnext101_32x8d 86.807 13.193 97.466 2.534 88.79 224 0.875 bilinear +5.191 +1.428 0
44 swsl_resnet50 86.807 13.193 97.498 2.502 25.56 224 0.875 bilinear +5.641 +1.526 +5
45 tf_efficientnet_lite4 86.803 13.197 97.263 2.737 13.01 380 0.920 bilinear +5.267 +1.595 -1
46 efficientnet_b3 86.782 13.218 97.288 2.712 12.23 300 0.904 bicubic +5.288 +1.572 -1
47 tresnet_l 86.767 13.233 97.271 2.729 55.99 224 0.875 bilinear +5.279 +1.647 -1
48 tf_efficientnet_b1_ns 86.669 13.331 97.378 2.622 7.79 240 0.882 bicubic +5.281 +1.640 -1
49 resnest50d_4s2x40d 86.592 13.408 97.269 2.731 30.42 224 0.875 bicubic +5.484 +1.711 +1
50 efficientnet_b3_pruned 86.581 13.419 97.190 2.810 9.86 300 0.904 bicubic +5.723 +1.948 +7
51 ssl_resnext101_32x4d 86.479 13.521 97.468 2.532 44.18 224 0.875 bilinear +5.555 +1.740 +3
52 ecaresnet50d 86.470 13.530 97.186 2.814 25.58 224 0.875 bicubic +5.878 +1.866 +11
53 gluon_resnet152_v1s 86.468 13.532 97.109 2.891 60.32 224 0.875 bicubic +5.452 +1.697 -2
54 resnest50d_1s4x24d 86.447 13.553 97.148 2.852 25.68 224 0.875 bicubic +5.459 +1.826 -2
55 efficientnet_b2a 86.304 13.696 96.990 3.010 9.11 288 1.000 bicubic +5.692 +1.672 +6
56 gluon_senet154 86.278 13.722 96.949 3.051 115.09 224 0.875 bicubic +5.044 +1.601 -8
57 resnest50d 86.240 13.761 97.073 2.927 27.48 224 0.875 bilinear +5.266 +1.695 -4
58 ecaresnet101d_pruned 86.210 13.790 97.335 2.665 24.88 224 0.875 bicubic +5.392 +1.707 0
59 tresnet_m 86.199 13.801 96.667 3.333 31.39 224 0.875 bilinear +5.397 +1.807 +1
60 cspdarknet53 86.182 13.818 97.013 2.987 27.64 256 0.887 bilinear +6.124 +1.929 +24
61 inception_v4 86.169 13.831 96.919 3.081 42.68 299 0.875 bicubic +6.001 +1.951 +19
62 rexnet_150 86.154 13.846 97.058 2.942 9.73 224 0.875 bicubic +5.844 +1.892 +12
63 tf_efficientnet_el 86.148 13.852 96.987 3.013 10.59 300 0.904 bicubic +5.708 +1.823 +5
64 inception_resnet_v2 86.133 13.867 97.043 2.957 55.84 299 0.897 bicubic +5.675 +1.737 +3
65 ssl_resnext50_32x4d 86.086 13.914 97.212 2.788 25.03 224 0.875 bilinear +5.768 +1.806 +8
66 efficientnet_b2 86.056 13.944 96.917 3.083 9.11 260 0.875 bicubic +5.664 +1.841 +4
67 gluon_resnet101_v1s 86.054 13.946 97.022 2.978 44.67 224 0.875 bicubic +5.752 +1.862 +8
68 ecaresnetlight 86.052 13.948 97.069 2.931 30.16 224 0.875 bicubic +5.590 +1.819 -2
69 gluon_seresnext101_32x4d 86.032 13.968 96.977 3.023 48.96 224 0.875 bicubic +5.128 +1.683 -14
70 tf_efficientnet_b2_ap 85.975 14.025 96.810 3.190 9.11 260 0.890 bicubic +5.675 +1.782 +6
71 gluon_seresnext101_64x4d 85.960 14.040 96.979 3.021 88.23 224 0.875 bicubic +5.066 +1.671 -15
72 gluon_resnet152_v1d 85.917 14.083 96.812 3.188 60.21 224 0.875 bicubic +5.443 +1.606 -7
73 tf_efficientnet_b2 85.902 14.098 96.862 3.139 9.11 260 0.890 bicubic +5.816 +1.954 +10
74 seresnet50 85.857 14.143 97.004 2.995 28.09 224 0.875 bicubic +5.583 +1.934 +4
75 gluon_resnet101_v1d 85.849 14.151 96.663 3.337 44.57 224 0.875 bicubic +5.435 +1.649 -6
76 resnet50 85.804 14.196 96.712 3.288 25.56 224 0.875 bicubic +6.766 +2.322 +50
77 mixnet_xl 85.798 14.202 96.712 3.288 11.90 224 0.875 bicubic +5.322 +1.776 -13
78 ens_adv_inception_resnet_v2 85.781 14.220 96.759 3.241 55.84 299 0.897 bicubic +5.799 +1.823 +9
79 tf_efficientnet_lite3 85.755 14.245 96.887 3.113 8.20 300 0.904 bilinear +5.935 +1.973 +16
80 ese_vovnet39b 85.751 14.249 96.891 3.109 24.57 224 0.875 bicubic +6.431 +2.179 +30
81 gluon_resnext101_32x4d 85.746 14.254 96.635 3.365 44.18 224 0.875 bicubic +5.412 +1.709 -9
82 cspresnext50 85.740 14.260 96.840 3.160 20.57 224 0.875 bilinear +5.700 +1.896 +3
83 regnety_320 85.727 14.273 96.725 3.275 145.05 224 0.875 bicubic +4.915 +1.481 -24
84 xception71 85.697 14.303 96.776 3.224 42.34 299 0.903 bicubic +5.823 +1.854 +8
85 gluon_resnext101_64x4d 85.693 14.307 96.644 3.356 83.46 224 0.875 bicubic +5.089 +1.656 -23
86 efficientnet_b2_pruned 85.642 14.358 96.746 3.254 8.31 260 0.890 bicubic +5.726 +1.890 +3
87 dpn107 85.640 14.360 96.729 3.271 86.92 224 0.875 bicubic +5.484 +1.819 -6
88 ecaresnet50d_pruned 85.580 14.420 96.936 3.064 19.94 224 0.875 bicubic +5.864 +2.056 +10
89 gluon_resnet152_v1c 85.580 14.420 96.646 3.354 60.21 224 0.875 bicubic +5.670 +1.806 +1
90 resnext50d_32x4d 85.569 14.431 96.748 3.252 25.05 224 0.875 bicubic +5.893 +1.882 +11
91 regnety_120 85.543 14.457 96.785 3.215 51.82 224 0.875 bicubic +5.177 +1.659 -20
92 regnetx_320 85.524 14.476 96.669 3.331 107.81 224 0.875 bicubic +5.278 +1.643 -13
93 regnety_160 85.501 14.499 96.620 3.380 83.59 224 0.875 bicubic +5.205 +1.658 -16
94 dpn92 85.494 14.506 96.635 3.365 37.67 224 0.875 bicubic +5.486 +1.799 -8
95 gluon_resnet152_v1b 85.475 14.525 96.550 3.450 60.19 224 0.875 bicubic +5.789 +1.814 +5
96 rexnet_130 85.473 14.527 96.684 3.316 7.56 224 0.875 bicubic +5.973 +2.002 +10
97 dpn131 85.398 14.602 96.639 3.361 79.25 224 0.875 bicubic +5.576 +1.929 -3
98 regnetx_160 85.390 14.610 96.637 3.363 54.28 224 0.875 bicubic +5.534 +1.807 -5
99 dla102x2 85.366 14.634 96.629 3.371 41.28 224 0.875 bilinear +5.918 +1.989 +9
100 gluon_seresnext50_32x4d 85.336 14.664 96.667 3.333 27.56 224 0.875 bicubic +5.418 +1.845 -12
101 xception65 85.315 14.685 96.637 3.363 39.92 299 0.903 bicubic +5.763 +1.983 +3
102 skresnext50_32x4d 85.313 14.687 96.390 3.610 27.48 224 0.875 bicubic +5.157 +1.748 -20
103 dpn98 85.311 14.689 96.469 3.531 61.57 224 0.875 bicubic +5.669 +1.871 -1
104 gluon_resnet101_v1c 85.304 14.696 96.405 3.595 44.57 224 0.875 bicubic +5.770 +1.827 +1
105 dpn68b 85.291 14.709 96.464 3.536 12.61 224 0.875 bicubic +6.075 +2.050 +14
106 resnetblur50 85.283 14.717 96.531 3.470 25.56 224 0.875 bicubic +5.997 +1.893 +8
107 regnety_064 85.283 14.717 96.639 3.361 30.58 224 0.875 bicubic +5.561 +1.871 -9
108 regnety_080 85.245 14.755 96.633 3.367 39.18 224 0.875 bicubic +5.369 +1.803 -17
109 resnext50_32x4d 85.221 14.779 96.526 3.474 25.03 224 0.875 bicubic +5.453 +1.928 -13
110 resnext101_32x8d 85.187 14.813 96.445 3.555 88.79 224 0.875 bilinear +5.879 +1.927 +1
111 gluon_inception_v3 85.183 14.817 96.526 3.474 23.83 299 0.875 bicubic +6.377 +2.156 +22
112 hrnet_w48 85.151 14.849 96.492 3.508 77.47 224 0.875 bilinear +5.851 +1.980 +2
113 gluon_xception65 85.148 14.851 96.597 3.403 39.92 299 0.903 bicubic +5.432 +1.737 -14
114 gluon_resnet101_v1b 85.142 14.858 96.366 3.634 44.55 224 0.875 bicubic +5.836 +1.842 -1
115 regnetx_120 85.131 14.869 96.477 3.523 46.11 224 0.875 bicubic +5.535 +1.739 -12
116 xception 85.129 14.871 96.471 3.529 22.86 299 0.897 bicubic +6.077 +2.079 +9
117 tf_efficientnet_b1_ap 85.127 14.873 96.405 3.595 7.79 240 0.882 bicubic +5.847 +2.099 -1
118 hrnet_w64 85.119 14.881 96.744 3.256 128.06 224 0.875 bilinear +5.645 +2.092 -11
119 ssl_resnet50 85.097 14.903 96.866 3.134 25.56 224 0.875 bilinear +5.875 +2.034 -2
120 res2net101_26w_4s 85.093 14.907 96.381 3.619 45.21 224 0.875 bilinear +5.895 +1.949 +1
121 tf_efficientnet_cc_b1_8e 85.063 14.937 96.422 3.578 39.72 240 0.882 bicubic +5.755 +2.052 -9
122 res2net50_26w_8s 85.029 14.971 96.419 3.580 48.40 224 0.875 bilinear +5.831 +2.052 -2
123 resnest26d 85.008 14.992 96.637 3.363 17.07 224 0.875 bilinear +6.530 +2.339 +21
124 gluon_resnext50_32x4d 84.995 15.005 96.426 3.574 25.03 224 0.875 bicubic +5.641 +2.000 -15
125 tf_efficientnet_b0_ns 84.984 15.016 96.503 3.497 5.29 224 0.875 bicubic +6.326 +2.127 +14
126 regnety_040 84.948 15.052 96.612 3.388 20.65 224 0.875 bicubic +5.728 +1.956 -8
127 tf_efficientnet_em 84.926 15.074 96.424 3.576 6.90 240 0.882 bicubic +6.218 +2.110 +9
128 dla169 84.920 15.080 96.535 3.465 53.39 224 0.875 bilinear +6.232 +2.199 +10
129 tf_efficientnet_b1 84.918 15.082 96.364 3.636 7.79 240 0.882 bicubic +6.092 +2.166 +3
130 hrnet_w44 84.884 15.116 96.434 3.566 67.06 224 0.875 bilinear +5.988 +2.066 -1
131 gluon_resnet50_v1s 84.862 15.138 96.443 3.557 25.68 224 0.875 bicubic +6.150 +2.205 +4
132 regnetx_080 84.862 15.138 96.434 3.566 39.57 224 0.875 bicubic +5.668 +1.874 -10
133 gluon_resnet50_v1d 84.832 15.168 96.398 3.602 25.58 224 0.875 bicubic +5.758 +1.928 -10
134 dla60_res2next 84.830 15.170 96.411 3.589 17.03 224 0.875 bilinear +6.390 +2.259 +14
135 mixnet_l 84.822 15.178 96.328 3.672 7.33 224 0.875 bicubic +5.846 +2.146 -8
136 resnet152 84.815 15.185 96.225 3.775 60.19 224 0.875 bilinear +6.503 +2.187 +14
137 dla102x 84.813 15.187 96.552 3.448 26.31 224 0.875 bilinear +6.303 +2.324 +4
138 dla60_res2net 84.813 15.187 96.481 3.519 20.85 224 0.875 bilinear +6.349 +2.275 +9
139 xception41 84.792 15.208 96.413 3.587 26.97 299 0.903 bicubic +6.276 +2.135 +2
140 regnetx_064 84.781 15.219 96.490 3.510 26.21 224 0.875 bicubic +5.709 +2.032 -16
141 hrnet_w40 84.743 15.257 96.554 3.446 57.56 224 0.875 bilinear +5.823 +2.084 -13
142 res2net50_26w_6s 84.726 15.274 96.281 3.719 37.05 224 0.875 bilinear +6.156 +2.157 -2
143 selecsls60b 84.657 15.343 96.300 3.700 32.77 224 0.875 bicubic +6.245 +2.126 +6
144 hrnet_w32 84.651 15.349 96.407 3.593 41.23 224 0.875 bilinear +6.201 +2.221 +3
145 regnety_032 84.606 15.394 96.424 3.576 19.44 224 0.875 bicubic +5.720 +2.012 -15
146 regnetx_040 84.600 15.400 96.383 3.617 22.12 224 0.875 bicubic +6.118 +2.139 -3
147 efficientnet_es 84.591 15.409 96.311 3.689 5.44 224 0.875 bicubic +6.525 +2.385 +10
148 hrnet_w30 84.572 15.428 96.388 3.612 37.71 224 0.875 bilinear +6.366 +2.165 +6
149 tf_mixnet_l 84.564 15.437 96.244 3.756 7.33 224 0.875 bicubic +5.790 +2.246 -15
150 wide_resnet101_2 84.557 15.443 96.349 3.651 126.89 224 0.875 bilinear +5.701 +2.067 -19
151 efficientnet_b1 84.531 15.469 96.153 3.847 7.79 240 0.875 bicubic +5.833 +2.009 -14
152 dla60x 84.523 15.477 96.285 3.715 17.35 224 0.875 bilinear +6.277 +2.267 -1
153 wide_resnet50_2 84.427 15.573 96.257 3.743 68.88 224 0.875 bilinear +5.949 +2.163 -8
154 efficientnet_b1_pruned 84.393 15.607 96.140 3.860 6.33 240 0.882 bicubic +6.157 +2.306 -1
155 res2net50_26w_4s 84.365 15.635 96.082 3.918 25.70 224 0.875 bilinear +6.401 +2.228 +8
156 res2net50_14w_8s 84.309 15.691 96.072 3.929 25.06 224 0.875 bilinear +6.159 +2.224 0
157 selecsls60 84.288 15.712 96.095 3.905 30.67 224 0.875 bicubic +6.306 +2.267 +5
158 regnetx_032 84.237 15.763 96.247 3.753 15.30 224 0.875 bicubic +6.065 +2.159 -3
159 res2next50 84.226 15.774 95.997 4.003 24.67 224 0.875 bilinear +5.980 +2.105 -7
160 gluon_resnet50_v1c 84.207 15.793 96.161 3.839 25.58 224 0.875 bicubic +6.195 +2.173 -1
161 dla102 84.190 15.810 96.206 3.794 33.27 224 0.875 bilinear +6.158 +2.260 -3
162 rexnet_100 84.162 15.838 96.255 3.745 4.80 224 0.875 bicubic +6.304 +2.385 +4
163 tf_inception_v3 84.136 15.864 95.918 4.082 23.83 299 0.875 bicubic +6.278 +2.280 +4
164 res2net50_48w_2s 84.126 15.874 95.965 4.035 25.29 224 0.875 bilinear +6.604 +2.411 +9
165 tf_efficientnet_lite2 84.094 15.906 96.069 3.931 6.09 260 0.890 bicubic +6.626 +2.315 +9
166 efficientnet_b0 84.038 15.962 95.956 4.044 5.29 224 0.875 bicubic +6.340 +2.424 +2
167 seresnext26t_32x4d 84.004 15.996 95.852 4.148 16.82 224 0.875 bicubic +6.006 +2.144 -7
168 tf_efficientnet_cc_b0_8e 83.966 16.034 96.065 3.935 24.01 224 0.875 bicubic +6.058 +2.411 -4
169 tv_resnext50_32x4d 83.959 16.041 95.960 4.040 25.03 224 0.875 bilinear +6.339 +2.264 0
170 regnety_016 83.955 16.045 96.005 3.995 11.20 224 0.875 bicubic +6.093 +2.285 -5
171 gluon_resnet50_v1b 83.940 16.060 96.012 3.988 25.56 224 0.875 bicubic +6.360 +2.296 +1
172 densenet161 83.906 16.094 96.010 3.990 28.68 224 0.875 bicubic +6.548 +2.372 +5
173 adv_inception_v3 83.902 16.098 95.935 4.065 23.83 299 0.875 bicubic +6.320 +2.199 -2
174 mobilenetv2_120d 83.893 16.107 95.909 4.091 5.83 224 0.875 bicubic +6.609 +2.417 +6
175 seresnext26tn_32x4d 83.878 16.122 95.931 4.069 16.81 224 0.875 bicubic +5.892 +2.185 -14
176 resnet101 83.848 16.152 95.892 4.108 44.55 224 0.875 bilinear +6.474 +2.352 0
177 inception_v3 83.761 16.239 95.879 4.121 23.83 299 0.875 bicubic +6.321 +2.403 -2
178 seresnext26d_32x4d 83.754 16.246 95.849 4.151 16.81 224 0.875 bicubic +6.152 +2.241 -8
179 dla60 83.729 16.271 95.933 4.067 22.04 224 0.875 bilinear +6.697 +2.615 +6
180 tf_efficientnet_b0_ap 83.650 16.350 95.779 4.221 5.29 224 0.875 bicubic +6.564 +2.523 +4
181 tf_efficientnet_es 83.647 16.352 95.939 4.061 5.44 224 0.875 bicubic +6.389 +2.345 +1
182 skresnet34 83.641 16.359 95.933 4.067 22.28 224 0.875 bicubic +6.729 +2.611 +6
183 tf_efficientnet_cc_b0_4e 83.639 16.361 95.740 4.260 13.31 224 0.875 bicubic +6.333 +2.406 -5
184 densenet201 83.556 16.444 95.811 4.189 20.01 224 0.875 bicubic +6.270 +2.333 -5
185 mixnet_m 83.515 16.485 95.689 4.311 5.01 224 0.875 bicubic +6.255 +2.265 -4
186 tf_efficientnet_b0 83.515 16.485 95.719 4.281 5.29 224 0.875 bicubic +6.667 +2.491 +3
187 hrnet_w18 83.500 16.500 95.907 4.093 21.30 224 0.875 bilinear +6.742 +2.463 +4
188 densenetblur121d 83.472 16.527 95.822 4.178 8.00 224 0.875 bicubic +6.884 +2.630 +6
189 selecsls42b 83.457 16.543 95.745 4.255 32.46 224 0.875 bicubic +6.284 +2.355 -6
190 tf_efficientnet_lite1 83.344 16.656 95.642 4.358 5.42 240 0.882 bicubic +6.702 +2.416 +3
191 regnetx_016 83.195 16.805 95.740 4.260 9.19 224 0.875 bicubic +6.245 +2.320 -5
192 mobilenetv2_140 83.182 16.818 95.689 4.311 6.11 224 0.875 bicubic +6.666 +2.693 +3
193 dpn68 83.178 16.822 95.597 4.402 12.61 224 0.875 bicubic +6.860 +2.620 +3
194 tf_mixnet_m 83.176 16.824 95.461 4.539 5.01 224 0.875 bicubic +6.234 +2.309 -7
195 ese_vovnet19b_dw 83.109 16.890 95.779 4.221 6.54 224 0.875 bicubic +6.311 +2.511 -5
196 resnet26d 83.050 16.950 95.604 4.396 16.01 224 0.875 bicubic +6.354 +2.454 -4
197 tv_resnet50 82.958 17.042 95.467 4.533 25.56 224 0.875 bilinear +6.820 +2.603 +1
198 densenet121 82.823 17.177 95.585 4.415 7.98 224 0.875 bicubic +7.245 +2.933 +6
199 densenet169 82.683 17.317 95.600 4.400 14.15 224 0.875 bicubic +6.776 +2.574 +1
200 mixnet_s 82.525 17.476 95.356 4.644 4.13 224 0.875 bicubic +6.532 +2.560 -1
201 regnety_008 82.493 17.508 95.487 4.513 6.26 224 0.875 bicubic +6.177 +2.421 -4
202 efficientnet_lite0 82.382 17.619 95.279 4.721 4.65 224 0.875 bicubic +6.898 +2.769 +5
203 resnest14d 82.352 17.648 95.339 4.661 10.61 224 0.875 bilinear +6.846 +2.821 +3
204 mobilenetv3_rw 82.275 17.725 95.234 4.766 5.48 224 0.875 bicubic +6.641 +2.526 -1
205 semnasnet_100 82.251 17.749 95.230 4.770 3.89 224 0.875 bicubic +6.803 +2.626 +3
206 mobilenetv3_large_100 82.177 17.823 95.196 4.804 5.48 224 0.875 bicubic +6.410 +2.654 -5
207 resnet34 82.138 17.862 95.130 4.870 21.80 224 0.875 bilinear +7.028 +2.846 +6
208 mobilenetv2_110d 82.070 17.930 95.076 4.923 4.52 224 0.875 bicubic +7.034 +2.890 +7
209 tf_mixnet_s 82.038 17.962 95.121 4.879 4.13 224 0.875 bicubic +6.388 +2.493 -7
210 hrnet_w18_small_v2 81.961 18.039 95.164 4.836 15.60 224 0.875 bilinear +6.847 +2.748 +2
211 tf_efficientnet_lite0 81.952 18.048 95.168 4.832 4.65 224 0.875 bicubic +7.122 +2.992 +5
212 resnet26 81.944 18.056 95.241 4.759 16.00 224 0.875 bicubic +6.652 +2.671 -3
213 tf_mobilenetv3_large_100 81.848 18.152 95.070 4.930 5.48 224 0.875 bilinear +6.330 +2.464 -8
214 tv_densenet121 81.726 18.274 95.034 4.966 7.98 224 0.875 bicubic +6.988 +2.884 +3
215 regnety_006 81.700 18.300 95.115 4.885 6.06 224 0.875 bicubic +6.454 +2.583 -5
216 dla34 81.658 18.342 94.878 5.122 15.74 224 0.875 bilinear +7.028 +2.800 +3
217 fbnetc_100 81.559 18.441 94.970 5.030 5.57 224 0.875 bilinear +6.436 +2.584 -6
218 gluon_resnet34_v1b 81.500 18.500 94.810 5.190 21.80 224 0.875 bicubic +6.912 +2.820 +2
219 regnetx_008 81.485 18.515 95.059 4.941 7.26 224 0.875 bicubic +6.447 +2.724 -5
220 mnasnet_100 81.459 18.541 94.899 5.101 4.38 224 0.875 bicubic +6.801 +2.785 -2
221 spnasnet_100 80.878 19.122 94.526 5.474 4.42 224 0.875 bilinear +6.794 +2.708 0
222 regnety_004 80.659 19.341 94.686 5.314 4.34 224 0.875 bicubic +6.625 +2.934 0
223 skresnet18 80.637 19.363 94.378 5.622 11.96 224 0.875 bicubic +7.599 +3.210 +4
224 regnetx_006 80.629 19.371 94.524 5.476 6.20 224 0.875 bicubic +6.777 +2.852 -1
225 swsl_resnet18 80.575 19.425 94.743 5.256 11.69 224 0.875 bilinear +7.299 +3.010 +1
226 tv_resnet34 80.389 19.611 94.436 5.564 21.80 224 0.875 bilinear +7.077 +3.010 -1
227 mobilenetv2_100 80.257 19.743 94.195 5.805 3.50 224 0.875 bicubic +7.287 +3.179 +1
228 ssl_resnet18 80.101 19.899 94.590 5.410 11.69 224 0.875 bilinear +7.491 +3.174 +1
229 tf_mobilenetv3_large_075 80.093 19.907 94.184 5.816 3.99 224 0.875 bilinear +6.655 +2.834 -5
230 hrnet_w18_small 79.557 20.443 93.898 6.102 13.19 224 0.875 bilinear +7.215 +3.220 +1
231 regnetx_004 79.435 20.565 93.853 6.147 5.16 224 0.875 bicubic +7.039 +3.023 -1
232 tf_mobilenetv3_large_minimal_100 79.222 20.778 93.706 6.294 3.92 224 0.875 bilinear +6.974 +3.076 0
233 gluon_resnet18_v1b 78.372 21.628 93.138 6.862 11.69 224 0.875 bicubic +7.536 +3.376 0
234 regnety_002 77.405 22.595 92.914 7.086 3.16 224 0.875 bicubic +7.153 +3.374 0
235 resnet18 77.276 22.724 92.756 7.244 11.69 224 0.875 bilinear +7.528 +3.678 0
236 regnetx_002 76.124 23.876 92.211 7.789 2.68 224 0.875 bicubic +7.362 +3.655 0
237 dla60x_c 75.637 24.363 92.177 7.823 1.32 224 0.875 bilinear +7.745 +3.751 +1
238 tf_mobilenetv3_small_100 74.717 25.283 91.257 8.743 2.54 224 0.875 bilinear +6.795 +3.593 -1
239 dla46x_c 73.647 26.353 91.095 8.905 1.07 224 0.875 bilinear +7.677 +4.115 0
240 tf_mobilenetv3_small_075 72.812 27.188 90.036 9.964 2.04 224 0.875 bilinear +7.096 +3.906 0
241 dla46_c 72.601 27.399 90.499 9.501 1.30 224 0.875 bilinear +7.735 +4.207 0
242 tf_mobilenetv3_small_minimal_100 70.111 29.889 88.505 11.495 2.04 224 0.875 bilinear +7.205 +4.275 0

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model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation
tf_efficientnet_l2_ns,88.352,11.648,98.648,1.352,480.31,800,0.96,bicubic
tf_efficientnet_l2_ns,88.352,11.648,98.650,1.350,480.31,800,0.960,bicubic
tf_efficientnet_l2_ns_475,88.234,11.766,98.546,1.454,480.31,475,0.936,bicubic
tf_efficientnet_b7_ns,86.838,13.162,98.094,1.906,66.35,600,0.949,bicubic
tf_efficientnet_b6_ns,86.462,13.538,97.884,2.116,43.04,528,0.942,bicubic
tf_efficientnet_b5_ns,86.08,13.92,97.754,2.246,30.39,456,0.934,bicubic
ig_resnext101_32x48d,85.442,14.558,97.572,2.428,828.41,224,0.875,bilinear
tf_efficientnet_b8,85.37,14.63,97.392,2.608,87.41,672,0.954,bicubic
tf_efficientnet_b8_ap,85.368,14.632,97.294,2.706,87.41,672,0.954,bicubic
tf_efficientnet_b4_ns,85.158,14.842,97.468,2.532,19.34,380,0.922,bicubic
tf_efficientnet_b7_ap,85.118,14.882,97.252,2.748,66.35,600,0.949,bicubic
ig_resnext101_32x32d,85.092,14.908,97.436,2.564,468.53,224,0.875,bilinear
tf_efficientnet_b7,84.932,15.068,97.208,2.792,66.35,600,0.949,bicubic
tf_efficientnet_b6_ap,84.786,15.214,97.138,2.862,43.04,528,0.942,bicubic
swsl_resnext101_32x8d,84.294,15.706,97.174,2.826,88.79,224,0.875,bilinear
tf_efficientnet_b5_ap,84.254,15.746,96.976,3.024,30.39,456,0.934,bicubic
resnest269e,84.186,15.814,96.922,3.078,110.93,416,0.875,bilinear
ig_resnext101_32x16d,84.176,15.824,97.196,2.804,194.03,224,0.875,bilinear
tf_efficientnet_b6,84.112,15.888,96.884,3.116,43.04,528,0.942,bicubic
tf_efficientnet_b3_ns,84.054,15.946,96.912,3.088,12.23,300,0.904,bicubic
resnest200e,83.834,16.166,96.838,3.162,70.2,320,0.875,bilinear
tf_efficientnet_b5,83.816,16.184,96.75,3.25,30.39,456,0.934,bicubic
swsl_resnext101_32x16d,83.338,16.662,96.852,3.148,194.03,224,0.875,bilinear
tf_efficientnet_b4_ap,83.248,16.752,96.388,3.612,19.34,380,0.922,bicubic
swsl_resnext101_32x4d,83.234,16.766,96.756,3.244,44.18,224,0.875,bilinear
tresnet_xl_448,83.048,16.952,96.174,3.826,78.44,448,0.875,bilinear
tf_efficientnet_b4,83.016,16.984,96.298,3.702,19.34,380,0.922,bicubic
resnest101e,82.89,17.11,96.324,3.676,48.28,256,0.875,bilinear
pnasnet5large,82.74,17.26,96.04,3.96,86.06,331,0.875,bicubic
ig_resnext101_32x8d,82.688,17.312,96.632,3.368,88.79,224,0.875,bilinear
nasnetalarge,82.558,17.442,96.036,3.964,88.75,331,0.875,bicubic
tf_efficientnet_b2_ns,82.38,17.62,96.252,3.748,9.11,260,0.89,bicubic
tresnet_l_448,82.268,17.732,95.978,4.022,55.99,448,0.875,bilinear
swsl_resnext50_32x4d,82.18,17.82,96.228,3.772,25.03,224,0.875,bilinear
ecaresnet101d,82.166,17.834,96.052,3.948,44.57,224,0.875,bicubic
tresnet_xl,82.07,17.93,95.928,4.072,78.44,224,0.875,bilinear
efficientnet_b3a,81.874,18.126,95.84,4.16,12.23,320,1.0,bicubic
ssl_resnext101_32x16d,81.836,18.164,96.094,3.906,194.03,224,0.875,bilinear
tf_efficientnet_b3_ap,81.828,18.172,95.624,4.376,12.23,300,0.904,bicubic
tresnet_m_448,81.712,18.288,95.57,4.43,31.39,448,0.875,bilinear
tf_efficientnet_b3,81.64,18.36,95.722,4.278,12.23,300,0.904,bicubic
ssl_resnext101_32x8d,81.626,18.374,96.038,3.962,88.79,224,0.875,bilinear
tf_efficientnet_lite4,81.528,18.472,95.668,4.332,13.01,380,0.92,bilinear
efficientnet_b3,81.498,18.502,95.718,4.282,12.23,300,0.904,bicubic
tresnet_l,81.488,18.512,95.628,4.372,55.99,224,0.875,bilinear
tf_efficientnet_b1_ns,81.386,18.614,95.738,4.262,7.79,240,0.882,bicubic
senet154,81.304,18.696,95.498,4.502,115.09,224,0.875,bilinear
gluon_senet154,81.224,18.776,95.356,4.644,115.09,224,0.875,bicubic
swsl_resnet50,81.18,18.82,95.986,4.014,25.56,224,0.875,bilinear
resnest50d_4s2x40d,81.114,18.886,95.568,4.432,30.42,224,0.875,bicubic
gluon_resnet152_v1s,81.012,18.988,95.416,4.584,60.32,224,0.875,bicubic
resnest50d_1s4x24d,80.99,19.01,95.322,4.678,25.68,224,0.875,bicubic
resnest50d,80.958,19.042,95.382,4.618,27.48,224,0.875,bilinear
ssl_resnext101_32x4d,80.928,19.072,95.728,4.272,44.18,224,0.875,bilinear
gluon_seresnext101_32x4d,80.902,19.098,95.294,4.706,48.96,224,0.875,bicubic
gluon_seresnext101_64x4d,80.89,19.11,95.304,4.696,88.23,224,0.875,bicubic
efficientnet_b3_pruned,80.856,19.144,95.24,4.76,9.86,300,0.904,bicubic
regnety_320,80.814,19.186,95.24,4.76,145.05,224,0.875,bicubic
ecaresnet101d_pruned,80.808,19.192,95.628,4.372,24.88,224,0.875,bicubic
tresnet_m,80.796,19.204,94.856,5.144,31.39,224,0.875,bilinear
efficientnet_b2a,80.608,19.392,95.31,4.69,9.11,288,1.0,bicubic
ecaresnet50d,80.604,19.396,95.322,4.678,25.58,224,0.875,bicubic
gluon_resnext101_64x4d,80.602,19.398,94.994,5.006,83.46,224,0.875,bicubic
mixnet_xl,80.478,19.522,94.932,5.068,11.9,224,0.875,bicubic
gluon_resnet152_v1d,80.47,19.53,95.206,4.794,60.21,224,0.875,bicubic
inception_resnet_v2,80.46,19.54,95.31,4.69,55.84,299,0.8975,bicubic
ecaresnetlight,80.454,19.546,95.256,4.744,30.16,224,0.875,bicubic
tf_efficientnet_el,80.448,19.552,95.16,4.84,10.59,300,0.904,bicubic
gluon_resnet101_v1d,80.424,19.576,95.02,4.98,44.57,224,0.875,bicubic
efficientnet_b2,80.402,19.598,95.076,4.924,9.11,260,0.875,bicubic
regnety_120,80.382,19.618,95.128,4.872,51.82,224,0.875,bicubic
tf_efficientnet_b7_ns,86.840,13.160,98.094,1.906,66.35,600,0.949,bicubic
tf_efficientnet_b6_ns,86.452,13.548,97.882,2.118,43.04,528,0.942,bicubic
tf_efficientnet_b5_ns,86.088,13.912,97.752,2.248,30.39,456,0.934,bicubic
ig_resnext101_32x48d,85.428,14.572,97.572,2.428,828.41,224,0.875,bilinear
tf_efficientnet_b8,85.370,14.630,97.390,2.610,87.41,672,0.954,bicubic
tf_efficientnet_b8_ap,85.370,14.630,97.294,2.706,87.41,672,0.954,bicubic
tf_efficientnet_b4_ns,85.162,14.838,97.470,2.530,19.34,380,0.922,bicubic
tf_efficientnet_b7_ap,85.120,14.880,97.252,2.748,66.35,600,0.949,bicubic
ig_resnext101_32x32d,85.094,14.906,97.438,2.562,468.53,224,0.875,bilinear
tf_efficientnet_b7,84.936,15.064,97.204,2.796,66.35,600,0.949,bicubic
tf_efficientnet_b6_ap,84.788,15.212,97.138,2.862,43.04,528,0.942,bicubic
resnest269e,84.518,15.482,96.986,3.014,110.93,416,0.928,bicubic
swsl_resnext101_32x8d,84.284,15.716,97.176,2.824,88.79,224,0.875,bilinear
tf_efficientnet_b5_ap,84.252,15.748,96.974,3.026,30.39,456,0.934,bicubic
ig_resnext101_32x16d,84.170,15.830,97.196,2.804,194.03,224,0.875,bilinear
tf_efficientnet_b6,84.110,15.890,96.886,3.114,43.04,528,0.942,bicubic
tf_efficientnet_b3_ns,84.048,15.952,96.910,3.090,12.23,300,0.904,bicubic
resnest200e,83.832,16.168,96.894,3.106,70.20,320,0.909,bicubic
tf_efficientnet_b5,83.812,16.188,96.748,3.252,30.39,456,0.934,bicubic
swsl_resnext101_32x16d,83.346,16.654,96.846,3.154,194.03,224,0.875,bilinear
tf_efficientnet_b4_ap,83.248,16.752,96.392,3.608,19.34,380,0.922,bicubic
swsl_resnext101_32x4d,83.230,16.770,96.760,3.240,44.18,224,0.875,bilinear
tresnet_xl_448,83.050,16.950,96.174,3.826,78.44,448,0.875,bilinear
tf_efficientnet_b4,83.022,16.978,96.300,3.700,19.34,380,0.922,bicubic
resnest101e,82.890,17.110,96.320,3.680,48.28,256,0.875,bilinear
pnasnet5large,82.782,17.218,96.040,3.960,86.06,331,0.911,bicubic
ig_resnext101_32x8d,82.688,17.312,96.636,3.364,88.79,224,0.875,bilinear
nasnetalarge,82.620,17.380,96.046,3.954,88.75,331,0.911,bicubic
tf_efficientnet_b2_ns,82.380,17.620,96.248,3.752,9.11,260,0.890,bicubic
tresnet_l_448,82.268,17.732,95.976,4.024,55.99,448,0.875,bilinear
swsl_resnext50_32x4d,82.182,17.818,96.230,3.770,25.03,224,0.875,bilinear
ecaresnet101d,82.172,17.828,96.046,3.954,44.57,224,0.875,bicubic
tresnet_xl,82.054,17.946,95.936,4.064,78.44,224,0.875,bilinear
efficientnet_b3a,81.866,18.134,95.836,4.164,12.23,320,1.000,bicubic
ssl_resnext101_32x16d,81.844,18.156,96.096,3.904,194.03,224,0.875,bilinear
tf_efficientnet_b3_ap,81.822,18.178,95.624,4.376,12.23,300,0.904,bicubic
tresnet_m_448,81.714,18.286,95.572,4.428,31.39,448,0.875,bilinear
tf_efficientnet_b3,81.636,18.364,95.718,4.282,12.23,300,0.904,bicubic
rexnet_200,81.632,18.368,95.668,4.332,16.37,224,0.875,bicubic
ssl_resnext101_32x8d,81.616,18.384,96.038,3.962,88.79,224,0.875,bilinear
tf_efficientnet_lite4,81.536,18.464,95.668,4.332,13.01,380,0.920,bilinear
efficientnet_b3,81.494,18.506,95.716,4.284,12.23,300,0.904,bicubic
tresnet_l,81.488,18.512,95.624,4.376,55.99,224,0.875,bilinear
tf_efficientnet_b1_ns,81.388,18.612,95.738,4.262,7.79,240,0.882,bicubic
gluon_senet154,81.234,18.766,95.348,4.652,115.09,224,0.875,bicubic
swsl_resnet50,81.166,18.834,95.972,4.028,25.56,224,0.875,bilinear
resnest50d_4s2x40d,81.108,18.892,95.558,4.442,30.42,224,0.875,bicubic
gluon_resnet152_v1s,81.016,18.984,95.412,4.588,60.32,224,0.875,bicubic
resnest50d_1s4x24d,80.988,19.012,95.322,4.678,25.68,224,0.875,bicubic
resnest50d,80.974,19.026,95.378,4.622,27.48,224,0.875,bilinear
ssl_resnext101_32x4d,80.924,19.076,95.728,4.272,44.18,224,0.875,bilinear
gluon_seresnext101_32x4d,80.904,19.096,95.294,4.706,48.96,224,0.875,bicubic
gluon_seresnext101_64x4d,80.894,19.106,95.308,4.692,88.23,224,0.875,bicubic
efficientnet_b3_pruned,80.858,19.142,95.242,4.758,9.86,300,0.904,bicubic
ecaresnet101d_pruned,80.818,19.182,95.628,4.372,24.88,224,0.875,bicubic
regnety_320,80.812,19.188,95.244,4.756,145.05,224,0.875,bicubic
tresnet_m,80.802,19.198,94.860,5.140,31.39,224,0.875,bilinear
efficientnet_b2a,80.612,19.388,95.318,4.682,9.11,288,1.000,bicubic
gluon_resnext101_64x4d,80.604,19.396,94.988,5.012,83.46,224,0.875,bicubic
ecaresnet50d,80.592,19.408,95.320,4.680,25.58,224,0.875,bicubic
mixnet_xl,80.476,19.524,94.936,5.064,11.90,224,0.875,bicubic
gluon_resnet152_v1d,80.474,19.526,95.206,4.794,60.21,224,0.875,bicubic
ecaresnetlight,80.462,19.538,95.250,4.750,30.16,224,0.875,bicubic
inception_resnet_v2,80.458,19.542,95.306,4.694,55.84,299,0.897,bicubic
tf_efficientnet_el,80.440,19.560,95.164,4.836,10.59,300,0.904,bicubic
gluon_resnet101_v1d,80.414,19.586,95.014,4.986,44.57,224,0.875,bicubic
efficientnet_b2,80.392,19.608,95.076,4.924,9.11,260,0.875,bicubic
regnety_120,80.366,19.634,95.126,4.874,51.82,224,0.875,bicubic
gluon_resnext101_32x4d,80.334,19.666,94.926,5.074,44.18,224,0.875,bicubic
ssl_resnext50_32x4d,80.328,19.672,95.404,4.596,25.03,224,0.875,bilinear
tf_efficientnet_b2_ap,80.306,19.694,95.028,4.972,9.11,260,0.89,bicubic
gluon_resnet101_v1s,80.3,19.7,95.15,4.85,44.67,224,0.875,bicubic
regnety_160,80.3,19.7,94.962,5.038,83.59,224,0.875,bicubic
regnetx_320,80.246,19.754,95.022,4.978,107.81,224,0.875,bicubic
seresnext101_32x4d,80.236,19.764,95.028,4.972,48.96,224,0.875,bilinear
dpn107,80.164,19.836,94.912,5.088,86.92,224,0.875,bicubic
inception_v4,80.156,19.844,94.974,5.026,42.68,299,0.875,bicubic
skresnext50_32x4d,80.15,19.85,94.644,5.356,27.48,224,0.875,bicubic
tf_efficientnet_b2,80.09,19.91,94.906,5.094,9.11,260,0.89,bicubic
dpn92,80.016,19.984,94.838,5.162,37.67,224,0.875,bicubic
ens_adv_inception_resnet_v2,79.976,20.024,94.946,5.054,55.84,299,0.8975,bicubic
efficientnet_b2_pruned,79.918,20.082,94.848,5.152,8.31,260,0.89,bicubic
gluon_resnet152_v1c,79.916,20.084,94.842,5.158,60.21,224,0.875,bicubic
gluon_seresnext50_32x4d,79.912,20.088,94.818,5.182,27.56,224,0.875,bicubic
regnety_080,79.868,20.132,94.832,5.168,39.18,224,0.875,bicubic
regnetx_160,79.866,20.134,94.828,5.172,54.28,224,0.875,bicubic
dpn131,79.828,20.172,94.704,5.296,79.25,224,0.875,bicubic
tf_efficientnet_lite3,79.812,20.188,94.914,5.086,8.2,300,0.904,bilinear
resnext50_32x4d,79.762,20.238,94.6,5.4,25.03,224,0.875,bicubic
ecaresnet50d_pruned,79.718,20.282,94.89,5.11,19.94,224,0.875,bicubic
regnety_064,79.712,20.288,94.774,5.226,30.58,224,0.875,bicubic
gluon_resnet152_v1b,79.692,20.308,94.738,5.262,60.19,224,0.875,bicubic
resnext50d_32x4d,79.674,20.326,94.868,5.132,25.05,224,0.875,bicubic
dpn98,79.636,20.364,94.594,5.406,61.57,224,0.875,bicubic
gluon_xception65,79.604,20.396,94.748,5.252,39.92,299,0.875,bicubic
regnetx_120,79.59,20.41,94.74,5.26,46.11,224,0.875,bicubic
gluon_resnet101_v1c,79.544,20.456,94.586,5.414,44.57,224,0.875,bicubic
hrnet_w64,79.472,20.528,94.65,5.35,128.06,224,0.875,bilinear
dla102x2,79.452,20.548,94.644,5.356,41.75,224,0.875,bilinear
gluon_resnext50_32x4d,79.356,20.644,94.424,5.576,25.03,224,0.875,bicubic
ese_vovnet39b,79.32,20.68,94.71,5.29,24.57,224,0.875,bicubic
resnext101_32x8d,79.312,20.688,94.526,5.474,88.79,224,0.875,bilinear
hrnet_w48,79.31,20.69,94.518,5.482,77.47,224,0.875,bilinear
gluon_resnet101_v1b,79.304,20.696,94.524,5.476,44.55,224,0.875,bicubic
tf_efficientnet_cc_b1_8e,79.298,20.702,94.364,5.636,39.72,240,0.882,bicubic
resnetblur50,79.29,20.71,94.632,5.368,25.56,224,0.875,bicubic
tf_efficientnet_b1_ap,79.278,20.722,94.308,5.692,7.79,240,0.882,bicubic
ssl_resnet50,79.228,20.772,94.832,5.168,25.56,224,0.875,bilinear
regnety_040,79.222,20.778,94.656,5.344,20.65,224,0.875,bicubic
res2net50_26w_8s,79.21,20.79,94.362,5.638,48.4,224,0.875,bilinear
regnetx_080,79.198,20.802,94.558,5.442,39.57,224,0.875,bicubic
res2net101_26w_4s,79.196,20.804,94.44,5.56,45.21,224,0.875,bilinear
seresnext50_32x4d,79.076,20.924,94.434,5.566,27.56,224,0.875,bilinear
gluon_resnet50_v1d,79.074,20.926,94.476,5.524,25.58,224,0.875,bicubic
regnetx_064,79.066,20.934,94.456,5.544,26.21,224,0.875,bicubic
xception,79.048,20.952,94.392,5.608,22.86,299,0.8975,bicubic
resnet50,79.032,20.968,94.384,5.616,25.56,224,0.875,bicubic
mixnet_l,78.976,21.024,94.184,5.816,7.33,224,0.875,bicubic
hrnet_w40,78.934,21.066,94.466,5.534,57.56,224,0.875,bilinear
hrnet_w44,78.894,21.106,94.37,5.63,67.06,224,0.875,bilinear
regnety_032,78.87,21.13,94.402,5.598,19.44,224,0.875,bicubic
wide_resnet101_2,78.846,21.154,94.284,5.716,126.89,224,0.875,bilinear
tf_efficientnet_b1,78.832,21.168,94.196,5.804,7.79,240,0.882,bicubic
gluon_inception_v3,78.804,21.196,94.38,5.62,23.83,299,0.875,bicubic
tf_mixnet_l,78.77,21.23,94.004,5.996,7.33,224,0.875,bicubic
gluon_resnet50_v1s,78.712,21.288,94.242,5.758,25.68,224,0.875,bicubic
dla169,78.71,21.29,94.338,5.662,53.99,224,0.875,bilinear
efficientnet_b1,78.698,21.302,94.152,5.848,7.79,240,0.875,bicubic
tf_efficientnet_em,78.698,21.302,94.32,5.68,6.9,240,0.882,bicubic
seresnet152,78.658,21.342,94.374,5.626,66.82,224,0.875,bilinear
tf_efficientnet_b0_ns,78.652,21.348,94.368,5.632,5.29,224,0.875,bicubic
res2net50_26w_6s,78.574,21.426,94.126,5.874,37.05,224,0.875,bilinear
dla102x,78.508,21.492,94.234,5.766,26.77,224,0.875,bilinear
regnetx_040,78.486,21.514,94.242,5.758,22.12,224,0.875,bicubic
resnest26d,78.482,21.518,94.29,5.71,17.07,224,0.875,bilinear
dla60_res2net,78.472,21.528,94.204,5.796,21.15,224,0.875,bilinear
wide_resnet50_2,78.468,21.532,94.086,5.914,68.88,224,0.875,bilinear
dla60_res2next,78.448,21.552,94.144,5.856,17.33,224,0.875,bilinear
hrnet_w32,78.448,21.552,94.188,5.812,41.23,224,0.875,bilinear
selecsls60b,78.418,21.582,94.166,5.834,32.77,224,0.875,bicubic
seresnet101,78.396,21.604,94.258,5.742,49.33,224,0.875,bilinear
resnet152,78.312,21.688,94.046,5.954,60.19,224,0.875,bilinear
dla60x,78.242,21.758,94.022,5.978,17.65,224,0.875,bilinear
efficientnet_b1_pruned,78.242,21.758,93.832,6.168,6.33,240,0.882,bicubic
res2next50,78.242,21.758,93.892,6.108,24.67,224,0.875,bilinear
hrnet_w30,78.196,21.804,94.22,5.78,37.71,224,0.875,bilinear
regnetx_032,78.166,21.834,94.08,5.92,15.3,224,0.875,bicubic
res2net50_14w_8s,78.152,21.848,93.842,6.158,25.06,224,0.875,bilinear
efficientnet_es,78.054,21.946,93.93,6.07,5.44,224,0.875,bicubic
dla102,78.026,21.974,93.95,6.05,33.73,224,0.875,bilinear
gluon_resnet50_v1c,78.01,21.99,93.988,6.012,25.58,224,0.875,bicubic
seresnext26tn_32x4d,77.99,22.01,93.748,6.252,16.81,224,0.875,bicubic
seresnext26t_32x4d,77.988,22.012,93.706,6.294,16.82,224,0.875,bicubic
selecsls60,77.982,22.018,93.832,6.168,30.67,224,0.875,bicubic
res2net50_26w_4s,77.946,22.054,93.852,6.148,25.7,224,0.875,bilinear
tf_efficientnet_cc_b0_8e,77.908,22.092,93.656,6.344,24.01,224,0.875,bicubic
tf_inception_v3,77.856,22.144,93.644,6.356,23.83,299,0.875,bicubic
regnety_016,77.852,22.148,93.716,6.284,11.2,224,0.875,bicubic
efficientnet_b0,77.692,22.308,93.532,6.468,5.29,224,0.875,bicubic
seresnet50,77.636,22.364,93.752,6.248,28.09,224,0.875,bilinear
tv_resnext50_32x4d,77.618,22.382,93.698,6.302,25.03,224,0.875,bilinear
seresnext26d_32x4d,77.604,22.396,93.612,6.388,16.81,224,0.875,bicubic
adv_inception_v3,77.58,22.42,93.724,6.276,23.83,299,0.875,bicubic
gluon_resnet50_v1b,77.578,22.422,93.718,6.282,25.56,224,0.875,bicubic
dpn68b,77.514,22.486,93.822,6.178,12.61,224,0.875,bicubic
res2net50_48w_2s,77.514,22.486,93.548,6.452,25.29,224,0.875,bilinear
tf_efficientnet_lite2,77.46,22.54,93.746,6.254,6.09,260,0.89,bicubic
inception_v3,77.436,22.564,93.476,6.524,23.83,299,0.875,bicubic
resnet101,77.374,22.626,93.546,6.454,44.55,224,0.875,bilinear
densenet161,77.348,22.652,93.648,6.352,28.68,224,0.875,bicubic
tf_efficientnet_cc_b0_4e,77.304,22.696,93.332,6.668,13.31,224,0.875,bicubic
mobilenetv2_120d,77.294,22.706,93.502,6.498,5.83,224,0.875,bicubic
densenet201,77.29,22.71,93.478,6.522,20.01,224,0.875,bicubic
tf_efficientnet_es,77.264,22.736,93.6,6.4,5.44,224,0.875,bicubic
mixnet_m,77.256,22.744,93.418,6.582,5.01,224,0.875,bicubic
selecsls42b,77.176,22.824,93.392,6.608,32.46,224,0.875,bicubic
seresnext26_32x4d,77.1,22.9,93.31,6.69,16.79,224,0.875,bicubic
tf_efficientnet_b0_ap,77.084,22.916,93.254,6.746,5.29,224,0.875,bicubic
dla60,77.024,22.976,93.308,6.692,22.33,224,0.875,bilinear
tf_mixnet_m,76.95,23.05,93.156,6.844,5.01,224,0.875,bicubic
regnetx_016,76.93,23.07,93.418,6.582,9.19,224,0.875,bicubic
skresnet34,76.91,23.09,93.316,6.684,22.28,224,0.875,bicubic
tf_efficientnet_b0,76.84,23.16,93.226,6.774,5.29,224,0.875,bicubic
hrnet_w18,76.756,23.244,93.442,6.558,21.3,224,0.875,bilinear
resnet26d,76.68,23.32,93.166,6.834,16.01,224,0.875,bicubic
tf_efficientnet_lite1,76.638,23.362,93.232,6.768,5.42,240,0.882,bicubic
densenetblur121d,76.576,23.424,93.19,6.81,8.0,224,0.875,bicubic
mobilenetv2_140,76.524,23.476,92.99,7.01,6.11,224,0.875,bicubic
regnety_008,76.314,23.686,93.062,6.938,6.26,224,0.875,bicubic
dpn68,76.306,23.694,92.97,7.03,12.61,224,0.875,bicubic
tv_resnet50,76.13,23.87,92.862,7.138,25.56,224,0.875,bilinear
mixnet_s,75.988,24.012,92.794,7.206,4.13,224,0.875,bicubic
densenet169,75.912,24.088,93.024,6.976,14.15,224,0.875,bicubic
mobilenetv3_large_100,75.768,24.232,92.54,7.46,5.48,224,0.875,bicubic
tf_mixnet_s,75.648,24.352,92.636,7.364,4.13,224,0.875,bicubic
mobilenetv3_rw,75.628,24.372,92.71,7.29,5.48,224,0.875,bicubic
densenet121,75.574,24.426,92.656,7.344,7.98,224,0.875,bicubic
tf_mobilenetv3_large_100,75.516,24.484,92.6,7.4,5.48,224,0.875,bilinear
resnest14d,75.504,24.496,92.514,7.486,10.61,224,0.875,bilinear
semnasnet_100,75.456,24.544,92.592,7.408,3.89,224,0.875,bicubic
resnet26,75.292,24.708,92.57,7.43,16.0,224,0.875,bicubic
regnety_006,75.26,24.74,92.528,7.472,6.06,224,0.875,bicubic
hrnet_w18_small_v2,75.126,24.874,92.416,7.584,15.6,224,0.875,bilinear
fbnetc_100,75.12,24.88,92.386,7.614,5.57,224,0.875,bilinear
resnet34,75.112,24.888,92.288,7.712,21.8,224,0.875,bilinear
mobilenetv2_110d,75.052,24.948,92.18,7.82,4.52,224,0.875,bicubic
regnetx_008,75.022,24.978,92.344,7.656,7.26,224,0.875,bicubic
tf_efficientnet_lite0,74.842,25.158,92.17,7.83,4.65,224,0.875,bicubic
seresnet34,74.808,25.192,92.126,7.874,21.96,224,0.875,bilinear
tv_densenet121,74.752,25.248,92.152,7.848,7.98,224,0.875,bicubic
mnasnet_100,74.656,25.344,92.126,7.874,4.38,224,0.875,bicubic
dla34,74.636,25.364,92.064,7.936,15.78,224,0.875,bilinear
gluon_resnet34_v1b,74.58,25.42,91.988,8.012,21.8,224,0.875,bicubic
spnasnet_100,74.08,25.92,91.832,8.168,4.42,224,0.875,bilinear
regnety_004,74.026,25.974,91.748,8.252,4.34,224,0.875,bicubic
regnetx_006,73.862,26.138,91.68,8.32,6.2,224,0.875,bicubic
tf_mobilenetv3_large_075,73.442,26.558,91.352,8.648,3.99,224,0.875,bilinear
tv_resnet34,73.314,26.686,91.42,8.58,21.8,224,0.875,bilinear
swsl_resnet18,73.286,26.714,91.732,8.268,11.69,224,0.875,bilinear
skresnet18,73.044,26.956,91.178,8.822,11.96,224,0.875,bicubic
mobilenetv2_100,72.978,27.022,91.016,8.984,3.5,224,0.875,bicubic
ssl_resnet18,72.6,27.4,91.416,8.584,11.69,224,0.875,bilinear
regnetx_004,72.406,27.594,90.83,9.17,5.16,224,0.875,bicubic
hrnet_w18_small,72.342,27.658,90.672,9.328,13.19,224,0.875,bilinear
tf_mobilenetv3_large_minimal_100,72.244,27.756,90.636,9.364,3.92,224,0.875,bilinear
seresnet18,71.758,28.242,90.334,9.666,11.78,224,0.875,bicubic
gluon_resnet18_v1b,70.83,29.17,89.756,10.244,11.69,224,0.875,bicubic
regnety_002,70.282,29.718,89.54,10.46,3.16,224,0.875,bicubic
resnet18,69.758,30.242,89.078,10.922,11.69,224,0.875,bilinear
regnetx_002,68.754,31.246,88.548,11.452,2.68,224,0.875,bicubic
tf_mobilenetv3_small_100,67.918,32.082,87.662,12.338,2.54,224,0.875,bilinear
dla60x_c,67.908,32.092,88.434,11.566,1.34,224,0.875,bilinear
dla46x_c,65.98,34.02,86.98,13.02,1.08,224,0.875,bilinear
tf_mobilenetv3_small_075,65.718,34.282,86.136,13.864,2.04,224,0.875,bilinear
dla46_c,64.878,35.122,86.286,13.714,1.31,224,0.875,bilinear
tf_mobilenetv3_small_minimal_100,62.898,37.102,84.23,15.77,2.04,224,0.875,bilinear
ssl_resnext50_32x4d,80.318,19.682,95.406,4.594,25.03,224,0.875,bilinear
rexnet_150,80.310,19.690,95.166,4.834,9.73,224,0.875,bicubic
gluon_resnet101_v1s,80.302,19.698,95.160,4.840,44.67,224,0.875,bicubic
tf_efficientnet_b2_ap,80.300,19.700,95.028,4.972,9.11,260,0.890,bicubic
regnety_160,80.296,19.704,94.962,5.038,83.59,224,0.875,bicubic
seresnet50,80.274,19.726,95.070,4.930,28.09,224,0.875,bicubic
regnetx_320,80.246,19.754,95.026,4.974,107.81,224,0.875,bicubic
inception_v4,80.168,19.832,94.968,5.032,42.68,299,0.875,bicubic
dpn107,80.156,19.844,94.910,5.090,86.92,224,0.875,bicubic
skresnext50_32x4d,80.156,19.844,94.642,5.358,27.48,224,0.875,bicubic
tf_efficientnet_b2,80.086,19.914,94.908,5.092,9.11,260,0.890,bicubic
cspdarknet53,80.058,19.942,95.084,4.916,27.64,256,0.887,bilinear
cspresnext50,80.040,19.960,94.944,5.056,20.57,224,0.875,bilinear
dpn92,80.008,19.992,94.836,5.164,37.67,224,0.875,bicubic
ens_adv_inception_resnet_v2,79.982,20.018,94.936,5.064,55.84,299,0.897,bicubic
gluon_seresnext50_32x4d,79.918,20.082,94.822,5.178,27.56,224,0.875,bicubic
efficientnet_b2_pruned,79.916,20.084,94.856,5.144,8.31,260,0.890,bicubic
gluon_resnet152_v1c,79.910,20.090,94.840,5.160,60.21,224,0.875,bicubic
regnety_080,79.876,20.124,94.830,5.170,39.18,224,0.875,bicubic
xception71,79.874,20.126,94.922,5.078,42.34,299,0.903,bicubic
regnetx_160,79.856,20.144,94.830,5.170,54.28,224,0.875,bicubic
dpn131,79.822,20.178,94.710,5.290,79.25,224,0.875,bicubic
tf_efficientnet_lite3,79.820,20.180,94.914,5.086,8.20,300,0.904,bilinear
resnext50_32x4d,79.768,20.232,94.598,5.402,25.03,224,0.875,bicubic
regnety_064,79.722,20.278,94.768,5.232,30.58,224,0.875,bicubic
ecaresnet50d_pruned,79.716,20.284,94.880,5.120,19.94,224,0.875,bicubic
gluon_xception65,79.716,20.284,94.860,5.140,39.92,299,0.903,bicubic
gluon_resnet152_v1b,79.686,20.314,94.736,5.264,60.19,224,0.875,bicubic
resnext50d_32x4d,79.676,20.324,94.866,5.134,25.05,224,0.875,bicubic
dpn98,79.642,20.358,94.598,5.402,61.57,224,0.875,bicubic
regnetx_120,79.596,20.404,94.738,5.262,46.11,224,0.875,bicubic
xception65,79.552,20.448,94.654,5.346,39.92,299,0.903,bicubic
gluon_resnet101_v1c,79.534,20.466,94.578,5.422,44.57,224,0.875,bicubic
rexnet_130,79.500,20.500,94.682,5.318,7.56,224,0.875,bicubic
hrnet_w64,79.474,20.526,94.652,5.348,128.06,224,0.875,bilinear
dla102x2,79.448,20.552,94.640,5.360,41.28,224,0.875,bilinear
gluon_resnext50_32x4d,79.354,20.646,94.426,5.574,25.03,224,0.875,bicubic
ese_vovnet39b,79.320,20.680,94.712,5.288,24.57,224,0.875,bicubic
resnext101_32x8d,79.308,20.692,94.518,5.482,88.79,224,0.875,bilinear
tf_efficientnet_cc_b1_8e,79.308,20.692,94.370,5.630,39.72,240,0.882,bicubic
gluon_resnet101_v1b,79.306,20.694,94.524,5.476,44.55,224,0.875,bicubic
hrnet_w48,79.300,20.700,94.512,5.488,77.47,224,0.875,bilinear
resnetblur50,79.286,20.714,94.638,5.362,25.56,224,0.875,bicubic
tf_efficientnet_b1_ap,79.280,20.720,94.306,5.694,7.79,240,0.882,bicubic
ssl_resnet50,79.222,20.778,94.832,5.168,25.56,224,0.875,bilinear
regnety_040,79.220,20.780,94.656,5.344,20.65,224,0.875,bicubic
dpn68b,79.216,20.784,94.414,5.586,12.61,224,0.875,bicubic
res2net50_26w_8s,79.198,20.802,94.368,5.632,48.40,224,0.875,bilinear
res2net101_26w_4s,79.198,20.802,94.432,5.568,45.21,224,0.875,bilinear
regnetx_080,79.194,20.806,94.560,5.440,39.57,224,0.875,bicubic
gluon_resnet50_v1d,79.074,20.926,94.470,5.530,25.58,224,0.875,bicubic
regnetx_064,79.072,20.928,94.458,5.542,26.21,224,0.875,bicubic
xception,79.052,20.948,94.392,5.608,22.86,299,0.897,bicubic
resnet50,79.038,20.962,94.390,5.610,25.56,224,0.875,bicubic
mixnet_l,78.976,21.024,94.182,5.818,7.33,224,0.875,bicubic
hrnet_w40,78.920,21.080,94.470,5.530,57.56,224,0.875,bilinear
hrnet_w44,78.896,21.104,94.368,5.632,67.06,224,0.875,bilinear
regnety_032,78.886,21.114,94.412,5.588,19.44,224,0.875,bicubic
wide_resnet101_2,78.856,21.144,94.282,5.718,126.89,224,0.875,bilinear
tf_efficientnet_b1,78.826,21.174,94.198,5.802,7.79,240,0.882,bicubic
gluon_inception_v3,78.806,21.194,94.370,5.630,23.83,299,0.875,bicubic
tf_mixnet_l,78.774,21.226,93.998,6.002,7.33,224,0.875,bicubic
gluon_resnet50_v1s,78.712,21.288,94.238,5.762,25.68,224,0.875,bicubic
tf_efficientnet_em,78.708,21.292,94.314,5.686,6.90,240,0.882,bicubic
efficientnet_b1,78.698,21.302,94.144,5.856,7.79,240,0.875,bicubic
dla169,78.688,21.312,94.336,5.664,53.39,224,0.875,bilinear
tf_efficientnet_b0_ns,78.658,21.342,94.376,5.624,5.29,224,0.875,bicubic
res2net50_26w_6s,78.570,21.430,94.124,5.876,37.05,224,0.875,bilinear
xception41,78.516,21.484,94.278,5.722,26.97,299,0.903,bicubic
dla102x,78.510,21.490,94.228,5.772,26.31,224,0.875,bilinear
regnetx_040,78.482,21.518,94.244,5.756,22.12,224,0.875,bicubic
resnest26d,78.478,21.522,94.298,5.702,17.07,224,0.875,bilinear
wide_resnet50_2,78.478,21.522,94.094,5.906,68.88,224,0.875,bilinear
dla60_res2net,78.464,21.536,94.206,5.794,20.85,224,0.875,bilinear
hrnet_w32,78.450,21.550,94.186,5.814,41.23,224,0.875,bilinear
dla60_res2next,78.440,21.560,94.152,5.848,17.03,224,0.875,bilinear
selecsls60b,78.412,21.588,94.174,5.826,32.77,224,0.875,bicubic
resnet152,78.312,21.688,94.038,5.962,60.19,224,0.875,bilinear
dla60x,78.246,21.754,94.018,5.982,17.35,224,0.875,bilinear
res2next50,78.246,21.754,93.892,6.108,24.67,224,0.875,bilinear
efficientnet_b1_pruned,78.236,21.764,93.834,6.166,6.33,240,0.882,bicubic
hrnet_w30,78.206,21.794,94.222,5.778,37.71,224,0.875,bilinear
regnetx_032,78.172,21.828,94.088,5.912,15.30,224,0.875,bicubic
res2net50_14w_8s,78.150,21.850,93.848,6.152,25.06,224,0.875,bilinear
efficientnet_es,78.066,21.934,93.926,6.074,5.44,224,0.875,bicubic
dla102,78.032,21.968,93.946,6.054,33.27,224,0.875,bilinear
gluon_resnet50_v1c,78.012,21.988,93.988,6.012,25.58,224,0.875,bicubic
seresnext26t_32x4d,77.998,22.002,93.708,6.292,16.82,224,0.875,bicubic
seresnext26tn_32x4d,77.986,22.014,93.746,6.254,16.81,224,0.875,bicubic
selecsls60,77.982,22.018,93.828,6.172,30.67,224,0.875,bicubic
res2net50_26w_4s,77.964,22.036,93.854,6.146,25.70,224,0.875,bilinear
tf_efficientnet_cc_b0_8e,77.908,22.092,93.654,6.346,24.01,224,0.875,bicubic
regnety_016,77.862,22.138,93.720,6.280,11.20,224,0.875,bicubic
rexnet_100,77.858,22.142,93.870,6.130,4.80,224,0.875,bicubic
tf_inception_v3,77.858,22.142,93.638,6.362,23.83,299,0.875,bicubic
efficientnet_b0,77.698,22.302,93.532,6.468,5.29,224,0.875,bicubic
tv_resnext50_32x4d,77.620,22.380,93.696,6.304,25.03,224,0.875,bilinear
seresnext26d_32x4d,77.602,22.398,93.608,6.392,16.81,224,0.875,bicubic
adv_inception_v3,77.582,22.418,93.736,6.264,23.83,299,0.875,bicubic
gluon_resnet50_v1b,77.580,22.420,93.716,6.284,25.56,224,0.875,bicubic
res2net50_48w_2s,77.522,22.478,93.554,6.446,25.29,224,0.875,bilinear
tf_efficientnet_lite2,77.468,22.532,93.754,6.246,6.09,260,0.890,bicubic
inception_v3,77.440,22.560,93.476,6.524,23.83,299,0.875,bicubic
resnet101,77.374,22.626,93.540,6.460,44.55,224,0.875,bilinear
densenet161,77.358,22.642,93.638,6.362,28.68,224,0.875,bicubic
tf_efficientnet_cc_b0_4e,77.306,22.694,93.334,6.666,13.31,224,0.875,bicubic
densenet201,77.286,22.714,93.478,6.522,20.01,224,0.875,bicubic
mobilenetv2_120d,77.284,22.716,93.492,6.508,5.83,224,0.875,bicubic
mixnet_m,77.260,22.740,93.424,6.576,5.01,224,0.875,bicubic
tf_efficientnet_es,77.258,22.742,93.594,6.406,5.44,224,0.875,bicubic
selecsls42b,77.174,22.826,93.390,6.610,32.46,224,0.875,bicubic
tf_efficientnet_b0_ap,77.086,22.914,93.256,6.744,5.29,224,0.875,bicubic
dla60,77.032,22.968,93.318,6.682,22.04,224,0.875,bilinear
regnetx_016,76.950,23.050,93.420,6.580,9.19,224,0.875,bicubic
tf_mixnet_m,76.942,23.058,93.152,6.848,5.01,224,0.875,bicubic
skresnet34,76.912,23.088,93.322,6.678,22.28,224,0.875,bicubic
tf_efficientnet_b0,76.848,23.152,93.228,6.772,5.29,224,0.875,bicubic
ese_vovnet19b_dw,76.798,23.202,93.268,6.732,6.54,224,0.875,bicubic
hrnet_w18,76.758,23.242,93.444,6.556,21.30,224,0.875,bilinear
resnet26d,76.696,23.304,93.150,6.850,16.01,224,0.875,bicubic
tf_efficientnet_lite1,76.642,23.358,93.226,6.774,5.42,240,0.882,bicubic
densenetblur121d,76.588,23.412,93.192,6.808,8.00,224,0.875,bicubic
mobilenetv2_140,76.516,23.484,92.996,7.004,6.11,224,0.875,bicubic
dpn68,76.318,23.682,92.978,7.022,12.61,224,0.875,bicubic
regnety_008,76.316,23.684,93.066,6.934,6.26,224,0.875,bicubic
tv_resnet50,76.138,23.862,92.864,7.136,25.56,224,0.875,bilinear
mixnet_s,75.992,24.008,92.796,7.204,4.13,224,0.875,bicubic
densenet169,75.906,24.094,93.026,6.974,14.15,224,0.875,bicubic
mobilenetv3_large_100,75.766,24.234,92.542,7.458,5.48,224,0.875,bicubic
tf_mixnet_s,75.650,24.350,92.628,7.372,4.13,224,0.875,bicubic
mobilenetv3_rw,75.634,24.366,92.708,7.292,5.48,224,0.875,bicubic
densenet121,75.578,24.422,92.652,7.348,7.98,224,0.875,bicubic
tf_mobilenetv3_large_100,75.518,24.482,92.606,7.394,5.48,224,0.875,bilinear
resnest14d,75.506,24.494,92.518,7.482,10.61,224,0.875,bilinear
efficientnet_lite0,75.484,24.516,92.510,7.490,4.65,224,0.875,bicubic
semnasnet_100,75.448,24.552,92.604,7.396,3.89,224,0.875,bicubic
resnet26,75.292,24.708,92.570,7.430,16.00,224,0.875,bicubic
regnety_006,75.246,24.754,92.532,7.468,6.06,224,0.875,bicubic
fbnetc_100,75.124,24.876,92.386,7.614,5.57,224,0.875,bilinear
hrnet_w18_small_v2,75.114,24.886,92.416,7.584,15.60,224,0.875,bilinear
resnet34,75.110,24.890,92.284,7.716,21.80,224,0.875,bilinear
regnetx_008,75.038,24.962,92.336,7.664,7.26,224,0.875,bicubic
mobilenetv2_110d,75.036,24.964,92.186,7.814,4.52,224,0.875,bicubic
tf_efficientnet_lite0,74.830,25.170,92.176,7.824,4.65,224,0.875,bicubic
tv_densenet121,74.738,25.262,92.150,7.850,7.98,224,0.875,bicubic
mnasnet_100,74.658,25.342,92.114,7.886,4.38,224,0.875,bicubic
dla34,74.630,25.370,92.078,7.922,15.74,224,0.875,bilinear
gluon_resnet34_v1b,74.588,25.412,91.990,8.010,21.80,224,0.875,bicubic
spnasnet_100,74.084,25.916,91.818,8.182,4.42,224,0.875,bilinear
regnety_004,74.034,25.966,91.752,8.248,4.34,224,0.875,bicubic
regnetx_006,73.852,26.148,91.672,8.328,6.20,224,0.875,bicubic
tf_mobilenetv3_large_075,73.438,26.562,91.350,8.650,3.99,224,0.875,bilinear
tv_resnet34,73.312,26.688,91.426,8.574,21.80,224,0.875,bilinear
swsl_resnet18,73.276,26.724,91.734,8.266,11.69,224,0.875,bilinear
skresnet18,73.038,26.962,91.168,8.832,11.96,224,0.875,bicubic
mobilenetv2_100,72.970,27.030,91.016,8.984,3.50,224,0.875,bicubic
ssl_resnet18,72.610,27.390,91.416,8.584,11.69,224,0.875,bilinear
regnetx_004,72.396,27.604,90.830,9.170,5.16,224,0.875,bicubic
hrnet_w18_small,72.342,27.658,90.678,9.322,13.19,224,0.875,bilinear
tf_mobilenetv3_large_minimal_100,72.248,27.752,90.630,9.370,3.92,224,0.875,bilinear
gluon_resnet18_v1b,70.836,29.164,89.762,10.238,11.69,224,0.875,bicubic
regnety_002,70.252,29.748,89.540,10.460,3.16,224,0.875,bicubic
resnet18,69.748,30.252,89.078,10.922,11.69,224,0.875,bilinear
regnetx_002,68.762,31.238,88.556,11.444,2.68,224,0.875,bicubic
tf_mobilenetv3_small_100,67.922,32.078,87.664,12.336,2.54,224,0.875,bilinear
dla60x_c,67.892,32.108,88.426,11.574,1.32,224,0.875,bilinear
dla46x_c,65.970,34.030,86.980,13.020,1.07,224,0.875,bilinear
tf_mobilenetv3_small_075,65.716,34.284,86.130,13.870,2.04,224,0.875,bilinear
dla46_c,64.866,35.134,86.292,13.708,1.30,224,0.875,bilinear
tf_mobilenetv3_small_minimal_100,62.906,37.094,84.230,15.770,2.04,224,0.875,bilinear

1 model top1 top1_err top5 top5_err param_count img_size cropt_pct interpolation
2 tf_efficientnet_l2_ns 88.352 11.648 98.648 98.650 1.352 1.350 480.31 800 0.96 0.960 bicubic
3 tf_efficientnet_l2_ns_475 88.234 11.766 98.546 1.454 480.31 475 0.936 bicubic
4 tf_efficientnet_b7_ns 86.838 86.840 13.162 13.160 98.094 1.906 66.35 600 0.949 bicubic
5 tf_efficientnet_b6_ns 86.462 86.452 13.538 13.548 97.884 97.882 2.116 2.118 43.04 528 0.942 bicubic
6 tf_efficientnet_b5_ns 86.08 86.088 13.92 13.912 97.754 97.752 2.246 2.248 30.39 456 0.934 bicubic
7 ig_resnext101_32x48d 85.442 85.428 14.558 14.572 97.572 2.428 828.41 224 0.875 bilinear
8 tf_efficientnet_b8 85.37 85.370 14.63 14.630 97.392 97.390 2.608 2.610 87.41 672 0.954 bicubic
9 tf_efficientnet_b8_ap 85.368 85.370 14.632 14.630 97.294 2.706 87.41 672 0.954 bicubic
10 tf_efficientnet_b4_ns 85.158 85.162 14.842 14.838 97.468 97.470 2.532 2.530 19.34 380 0.922 bicubic
11 tf_efficientnet_b7_ap 85.118 85.120 14.882 14.880 97.252 2.748 66.35 600 0.949 bicubic
12 ig_resnext101_32x32d 85.092 85.094 14.908 14.906 97.436 97.438 2.564 2.562 468.53 224 0.875 bilinear
13 tf_efficientnet_b7 84.932 84.936 15.068 15.064 97.208 97.204 2.792 2.796 66.35 600 0.949 bicubic
14 tf_efficientnet_b6_ap 84.786 84.788 15.214 15.212 97.138 2.862 43.04 528 0.942 bicubic
15 swsl_resnext101_32x8d resnest269e 84.294 84.518 15.706 15.482 97.174 96.986 2.826 3.014 88.79 110.93 224 416 0.875 0.928 bilinear bicubic
16 tf_efficientnet_b5_ap swsl_resnext101_32x8d 84.254 84.284 15.746 15.716 96.976 97.176 3.024 2.824 30.39 88.79 456 224 0.934 0.875 bicubic bilinear
17 resnest269e tf_efficientnet_b5_ap 84.186 84.252 15.814 15.748 96.922 96.974 3.078 3.026 110.93 30.39 416 456 0.875 0.934 bilinear bicubic
18 ig_resnext101_32x16d 84.176 84.170 15.824 15.830 97.196 2.804 194.03 224 0.875 bilinear
19 tf_efficientnet_b6 84.112 84.110 15.888 15.890 96.884 96.886 3.116 3.114 43.04 528 0.942 bicubic
20 tf_efficientnet_b3_ns 84.054 84.048 15.946 15.952 96.912 96.910 3.088 3.090 12.23 300 0.904 bicubic
21 resnest200e 83.834 83.832 16.166 16.168 96.838 96.894 3.162 3.106 70.2 70.20 320 0.875 0.909 bilinear bicubic
22 tf_efficientnet_b5 83.816 83.812 16.184 16.188 96.75 96.748 3.25 3.252 30.39 456 0.934 bicubic
23 swsl_resnext101_32x16d 83.338 83.346 16.662 16.654 96.852 96.846 3.148 3.154 194.03 224 0.875 bilinear
24 tf_efficientnet_b4_ap 83.248 16.752 96.388 96.392 3.612 3.608 19.34 380 0.922 bicubic
25 swsl_resnext101_32x4d 83.234 83.230 16.766 16.770 96.756 96.760 3.244 3.240 44.18 224 0.875 bilinear
26 tresnet_xl_448 83.048 83.050 16.952 16.950 96.174 3.826 78.44 448 0.875 bilinear
27 tf_efficientnet_b4 83.016 83.022 16.984 16.978 96.298 96.300 3.702 3.700 19.34 380 0.922 bicubic
28 resnest101e 82.89 82.890 17.11 17.110 96.324 96.320 3.676 3.680 48.28 256 0.875 bilinear
29 pnasnet5large 82.74 82.782 17.26 17.218 96.04 96.040 3.96 3.960 86.06 331 0.875 0.911 bicubic
30 ig_resnext101_32x8d 82.688 17.312 96.632 96.636 3.368 3.364 88.79 224 0.875 bilinear
31 nasnetalarge 82.558 82.620 17.442 17.380 96.036 96.046 3.964 3.954 88.75 331 0.875 0.911 bicubic
32 tf_efficientnet_b2_ns 82.38 82.380 17.62 17.620 96.252 96.248 3.748 3.752 9.11 260 0.89 0.890 bicubic
33 tresnet_l_448 82.268 17.732 95.978 95.976 4.022 4.024 55.99 448 0.875 bilinear
34 swsl_resnext50_32x4d 82.18 82.182 17.82 17.818 96.228 96.230 3.772 3.770 25.03 224 0.875 bilinear
35 ecaresnet101d 82.166 82.172 17.834 17.828 96.052 96.046 3.948 3.954 44.57 224 0.875 bicubic
36 tresnet_xl 82.07 82.054 17.93 17.946 95.928 95.936 4.072 4.064 78.44 224 0.875 bilinear
37 efficientnet_b3a 81.874 81.866 18.126 18.134 95.84 95.836 4.16 4.164 12.23 320 1.0 1.000 bicubic
38 ssl_resnext101_32x16d 81.836 81.844 18.164 18.156 96.094 96.096 3.906 3.904 194.03 224 0.875 bilinear
39 tf_efficientnet_b3_ap 81.828 81.822 18.172 18.178 95.624 4.376 12.23 300 0.904 bicubic
40 tresnet_m_448 81.712 81.714 18.288 18.286 95.57 95.572 4.43 4.428 31.39 448 0.875 bilinear
41 tf_efficientnet_b3 81.64 81.636 18.36 18.364 95.722 95.718 4.278 4.282 12.23 300 0.904 bicubic
42 ssl_resnext101_32x8d rexnet_200 81.626 81.632 18.374 18.368 96.038 95.668 3.962 4.332 88.79 16.37 224 0.875 bilinear bicubic
43 tf_efficientnet_lite4 ssl_resnext101_32x8d 81.528 81.616 18.472 18.384 95.668 96.038 4.332 3.962 13.01 88.79 380 224 0.92 0.875 bilinear
44 efficientnet_b3 tf_efficientnet_lite4 81.498 81.536 18.502 18.464 95.718 95.668 4.282 4.332 12.23 13.01 300 380 0.904 0.920 bicubic bilinear
45 tresnet_l efficientnet_b3 81.488 81.494 18.512 18.506 95.628 95.716 4.372 4.284 55.99 12.23 224 300 0.875 0.904 bilinear bicubic
46 tf_efficientnet_b1_ns tresnet_l 81.386 81.488 18.614 18.512 95.738 95.624 4.262 4.376 7.79 55.99 240 224 0.882 0.875 bicubic bilinear
47 senet154 tf_efficientnet_b1_ns 81.304 81.388 18.696 18.612 95.498 95.738 4.502 4.262 115.09 7.79 224 240 0.875 0.882 bilinear bicubic
48 gluon_senet154 81.224 81.234 18.776 18.766 95.356 95.348 4.644 4.652 115.09 224 0.875 bicubic
49 swsl_resnet50 81.18 81.166 18.82 18.834 95.986 95.972 4.014 4.028 25.56 224 0.875 bilinear
50 resnest50d_4s2x40d 81.114 81.108 18.886 18.892 95.568 95.558 4.432 4.442 30.42 224 0.875 bicubic
51 gluon_resnet152_v1s 81.012 81.016 18.988 18.984 95.416 95.412 4.584 4.588 60.32 224 0.875 bicubic
52 resnest50d_1s4x24d 80.99 80.988 19.01 19.012 95.322 4.678 25.68 224 0.875 bicubic
53 resnest50d 80.958 80.974 19.042 19.026 95.382 95.378 4.618 4.622 27.48 224 0.875 bilinear
54 ssl_resnext101_32x4d 80.928 80.924 19.072 19.076 95.728 4.272 44.18 224 0.875 bilinear
55 gluon_seresnext101_32x4d 80.902 80.904 19.098 19.096 95.294 4.706 48.96 224 0.875 bicubic
56 gluon_seresnext101_64x4d 80.89 80.894 19.11 19.106 95.304 95.308 4.696 4.692 88.23 224 0.875 bicubic
57 efficientnet_b3_pruned 80.856 80.858 19.144 19.142 95.24 95.242 4.76 4.758 9.86 300 0.904 bicubic
58 regnety_320 ecaresnet101d_pruned 80.814 80.818 19.186 19.182 95.24 95.628 4.76 4.372 145.05 24.88 224 0.875 bicubic
59 ecaresnet101d_pruned regnety_320 80.808 80.812 19.192 19.188 95.628 95.244 4.372 4.756 24.88 145.05 224 0.875 bicubic
60 tresnet_m 80.796 80.802 19.204 19.198 94.856 94.860 5.144 5.140 31.39 224 0.875 bilinear
61 efficientnet_b2a 80.608 80.612 19.392 19.388 95.31 95.318 4.69 4.682 9.11 288 1.0 1.000 bicubic
62 ecaresnet50d gluon_resnext101_64x4d 80.604 19.396 95.322 94.988 4.678 5.012 25.58 83.46 224 0.875 bicubic
63 gluon_resnext101_64x4d ecaresnet50d 80.602 80.592 19.398 19.408 94.994 95.320 5.006 4.680 83.46 25.58 224 0.875 bicubic
64 mixnet_xl 80.478 80.476 19.522 19.524 94.932 94.936 5.068 5.064 11.9 11.90 224 0.875 bicubic
65 gluon_resnet152_v1d 80.47 80.474 19.53 19.526 95.206 4.794 60.21 224 0.875 bicubic
66 inception_resnet_v2 ecaresnetlight 80.46 80.462 19.54 19.538 95.31 95.250 4.69 4.750 55.84 30.16 299 224 0.8975 0.875 bicubic
67 ecaresnetlight inception_resnet_v2 80.454 80.458 19.546 19.542 95.256 95.306 4.744 4.694 30.16 55.84 224 299 0.875 0.897 bicubic
68 tf_efficientnet_el 80.448 80.440 19.552 19.560 95.16 95.164 4.84 4.836 10.59 300 0.904 bicubic
69 gluon_resnet101_v1d 80.424 80.414 19.576 19.586 95.02 95.014 4.98 4.986 44.57 224 0.875 bicubic
70 efficientnet_b2 80.402 80.392 19.598 19.608 95.076 4.924 9.11 260 0.875 bicubic
71 regnety_120 80.382 80.366 19.618 19.634 95.128 95.126 4.872 4.874 51.82 224 0.875 bicubic
72 gluon_resnext101_32x4d 80.334 19.666 94.926 5.074 44.18 224 0.875 bicubic
73 ssl_resnext50_32x4d 80.328 80.318 19.672 19.682 95.404 95.406 4.596 4.594 25.03 224 0.875 bilinear
74 tf_efficientnet_b2_ap rexnet_150 80.306 80.310 19.694 19.690 95.028 95.166 4.972 4.834 9.11 9.73 260 224 0.89 0.875 bicubic
75 gluon_resnet101_v1s 80.3 80.302 19.7 19.698 95.15 95.160 4.85 4.840 44.67 224 0.875 bicubic
76 regnety_160 tf_efficientnet_b2_ap 80.3 80.300 19.7 19.700 94.962 95.028 5.038 4.972 83.59 9.11 224 260 0.875 0.890 bicubic
77 regnetx_320 regnety_160 80.246 80.296 19.754 19.704 95.022 94.962 4.978 5.038 107.81 83.59 224 0.875 bicubic
78 seresnext101_32x4d seresnet50 80.236 80.274 19.764 19.726 95.028 95.070 4.972 4.930 48.96 28.09 224 0.875 bilinear bicubic
79 dpn107 regnetx_320 80.164 80.246 19.836 19.754 94.912 95.026 5.088 4.974 86.92 107.81 224 0.875 bicubic
80 inception_v4 80.156 80.168 19.844 19.832 94.974 94.968 5.026 5.032 42.68 299 0.875 bicubic
81 skresnext50_32x4d dpn107 80.15 80.156 19.85 19.844 94.644 94.910 5.356 5.090 27.48 86.92 224 0.875 bicubic
82 tf_efficientnet_b2 skresnext50_32x4d 80.09 80.156 19.91 19.844 94.906 94.642 5.094 5.358 9.11 27.48 260 224 0.89 0.875 bicubic
83 dpn92 tf_efficientnet_b2 80.016 80.086 19.984 19.914 94.838 94.908 5.162 5.092 37.67 9.11 224 260 0.875 0.890 bicubic
84 ens_adv_inception_resnet_v2 cspdarknet53 79.976 80.058 20.024 19.942 94.946 95.084 5.054 4.916 55.84 27.64 299 256 0.8975 0.887 bicubic bilinear
85 efficientnet_b2_pruned cspresnext50 79.918 80.040 20.082 19.960 94.848 94.944 5.152 5.056 8.31 20.57 260 224 0.89 0.875 bicubic bilinear
86 gluon_resnet152_v1c dpn92 79.916 80.008 20.084 19.992 94.842 94.836 5.158 5.164 60.21 37.67 224 0.875 bicubic
87 gluon_seresnext50_32x4d ens_adv_inception_resnet_v2 79.912 79.982 20.088 20.018 94.818 94.936 5.182 5.064 27.56 55.84 224 299 0.875 0.897 bicubic
88 regnety_080 gluon_seresnext50_32x4d 79.868 79.918 20.132 20.082 94.832 94.822 5.168 5.178 39.18 27.56 224 0.875 bicubic
89 regnetx_160 efficientnet_b2_pruned 79.866 79.916 20.134 20.084 94.828 94.856 5.172 5.144 54.28 8.31 224 260 0.875 0.890 bicubic
90 dpn131 gluon_resnet152_v1c 79.828 79.910 20.172 20.090 94.704 94.840 5.296 5.160 79.25 60.21 224 0.875 bicubic
91 tf_efficientnet_lite3 regnety_080 79.812 79.876 20.188 20.124 94.914 94.830 5.086 5.170 8.2 39.18 300 224 0.904 0.875 bilinear bicubic
92 resnext50_32x4d xception71 79.762 79.874 20.238 20.126 94.6 94.922 5.4 5.078 25.03 42.34 224 299 0.875 0.903 bicubic
93 ecaresnet50d_pruned regnetx_160 79.718 79.856 20.282 20.144 94.89 94.830 5.11 5.170 19.94 54.28 224 0.875 bicubic
94 regnety_064 dpn131 79.712 79.822 20.288 20.178 94.774 94.710 5.226 5.290 30.58 79.25 224 0.875 bicubic
95 gluon_resnet152_v1b tf_efficientnet_lite3 79.692 79.820 20.308 20.180 94.738 94.914 5.262 5.086 60.19 8.20 224 300 0.875 0.904 bicubic bilinear
96 resnext50d_32x4d resnext50_32x4d 79.674 79.768 20.326 20.232 94.868 94.598 5.132 5.402 25.05 25.03 224 0.875 bicubic
97 dpn98 regnety_064 79.636 79.722 20.364 20.278 94.594 94.768 5.406 5.232 61.57 30.58 224 0.875 bicubic
98 gluon_xception65 ecaresnet50d_pruned 79.604 79.716 20.396 20.284 94.748 94.880 5.252 5.120 39.92 19.94 299 224 0.875 bicubic
99 regnetx_120 gluon_xception65 79.59 79.716 20.41 20.284 94.74 94.860 5.26 5.140 46.11 39.92 224 299 0.875 0.903 bicubic
100 gluon_resnet101_v1c gluon_resnet152_v1b 79.544 79.686 20.456 20.314 94.586 94.736 5.414 5.264 44.57 60.19 224 0.875 bicubic
101 hrnet_w64 resnext50d_32x4d 79.472 79.676 20.528 20.324 94.65 94.866 5.35 5.134 128.06 25.05 224 0.875 bilinear bicubic
102 dla102x2 dpn98 79.452 79.642 20.548 20.358 94.644 94.598 5.356 5.402 41.75 61.57 224 0.875 bilinear bicubic
103 gluon_resnext50_32x4d regnetx_120 79.356 79.596 20.644 20.404 94.424 94.738 5.576 5.262 25.03 46.11 224 0.875 bicubic
104 ese_vovnet39b xception65 79.32 79.552 20.68 20.448 94.71 94.654 5.29 5.346 24.57 39.92 224 299 0.875 0.903 bicubic
105 resnext101_32x8d gluon_resnet101_v1c 79.312 79.534 20.688 20.466 94.526 94.578 5.474 5.422 88.79 44.57 224 0.875 bilinear bicubic
106 hrnet_w48 rexnet_130 79.31 79.500 20.69 20.500 94.518 94.682 5.482 5.318 77.47 7.56 224 0.875 bilinear bicubic
107 gluon_resnet101_v1b hrnet_w64 79.304 79.474 20.696 20.526 94.524 94.652 5.476 5.348 44.55 128.06 224 0.875 bicubic bilinear
108 tf_efficientnet_cc_b1_8e dla102x2 79.298 79.448 20.702 20.552 94.364 94.640 5.636 5.360 39.72 41.28 240 224 0.882 0.875 bicubic bilinear
109 resnetblur50 gluon_resnext50_32x4d 79.29 79.354 20.71 20.646 94.632 94.426 5.368 5.574 25.56 25.03 224 0.875 bicubic
110 tf_efficientnet_b1_ap ese_vovnet39b 79.278 79.320 20.722 20.680 94.308 94.712 5.692 5.288 7.79 24.57 240 224 0.882 0.875 bicubic
111 ssl_resnet50 resnext101_32x8d 79.228 79.308 20.772 20.692 94.832 94.518 5.168 5.482 25.56 88.79 224 0.875 bilinear
112 regnety_040 tf_efficientnet_cc_b1_8e 79.222 79.308 20.778 20.692 94.656 94.370 5.344 5.630 20.65 39.72 224 240 0.875 0.882 bicubic
113 res2net50_26w_8s gluon_resnet101_v1b 79.21 79.306 20.79 20.694 94.362 94.524 5.638 5.476 48.4 44.55 224 0.875 bilinear bicubic
114 regnetx_080 hrnet_w48 79.198 79.300 20.802 20.700 94.558 94.512 5.442 5.488 39.57 77.47 224 0.875 bicubic bilinear
115 res2net101_26w_4s resnetblur50 79.196 79.286 20.804 20.714 94.44 94.638 5.56 5.362 45.21 25.56 224 0.875 bilinear bicubic
116 seresnext50_32x4d tf_efficientnet_b1_ap 79.076 79.280 20.924 20.720 94.434 94.306 5.566 5.694 27.56 7.79 224 240 0.875 0.882 bilinear bicubic
117 gluon_resnet50_v1d ssl_resnet50 79.074 79.222 20.926 20.778 94.476 94.832 5.524 5.168 25.58 25.56 224 0.875 bicubic bilinear
118 regnetx_064 regnety_040 79.066 79.220 20.934 20.780 94.456 94.656 5.544 5.344 26.21 20.65 224 0.875 bicubic
119 xception dpn68b 79.048 79.216 20.952 20.784 94.392 94.414 5.608 5.586 22.86 12.61 299 224 0.8975 0.875 bicubic
120 resnet50 res2net50_26w_8s 79.032 79.198 20.968 20.802 94.384 94.368 5.616 5.632 25.56 48.40 224 0.875 bicubic bilinear
121 mixnet_l res2net101_26w_4s 78.976 79.198 21.024 20.802 94.184 94.432 5.816 5.568 7.33 45.21 224 0.875 bicubic bilinear
122 hrnet_w40 regnetx_080 78.934 79.194 21.066 20.806 94.466 94.560 5.534 5.440 57.56 39.57 224 0.875 bilinear bicubic
123 hrnet_w44 gluon_resnet50_v1d 78.894 79.074 21.106 20.926 94.37 94.470 5.63 5.530 67.06 25.58 224 0.875 bilinear bicubic
124 regnety_032 regnetx_064 78.87 79.072 21.13 20.928 94.402 94.458 5.598 5.542 19.44 26.21 224 0.875 bicubic
125 wide_resnet101_2 xception 78.846 79.052 21.154 20.948 94.284 94.392 5.716 5.608 126.89 22.86 224 299 0.875 0.897 bilinear bicubic
126 tf_efficientnet_b1 resnet50 78.832 79.038 21.168 20.962 94.196 94.390 5.804 5.610 7.79 25.56 240 224 0.882 0.875 bicubic
127 gluon_inception_v3 mixnet_l 78.804 78.976 21.196 21.024 94.38 94.182 5.62 5.818 23.83 7.33 299 224 0.875 bicubic
128 tf_mixnet_l hrnet_w40 78.77 78.920 21.23 21.080 94.004 94.470 5.996 5.530 7.33 57.56 224 0.875 bicubic bilinear
129 gluon_resnet50_v1s hrnet_w44 78.712 78.896 21.288 21.104 94.242 94.368 5.758 5.632 25.68 67.06 224 0.875 bicubic bilinear
130 dla169 regnety_032 78.71 78.886 21.29 21.114 94.338 94.412 5.662 5.588 53.99 19.44 224 0.875 bilinear bicubic
131 efficientnet_b1 wide_resnet101_2 78.698 78.856 21.302 21.144 94.152 94.282 5.848 5.718 7.79 126.89 240 224 0.875 bicubic bilinear
132 tf_efficientnet_em tf_efficientnet_b1 78.698 78.826 21.302 21.174 94.32 94.198 5.68 5.802 6.9 7.79 240 0.882 bicubic
133 seresnet152 gluon_inception_v3 78.658 78.806 21.342 21.194 94.374 94.370 5.626 5.630 66.82 23.83 224 299 0.875 bilinear bicubic
134 tf_efficientnet_b0_ns tf_mixnet_l 78.652 78.774 21.348 21.226 94.368 93.998 5.632 6.002 5.29 7.33 224 0.875 bicubic
135 res2net50_26w_6s gluon_resnet50_v1s 78.574 78.712 21.426 21.288 94.126 94.238 5.874 5.762 37.05 25.68 224 0.875 bilinear bicubic
136 dla102x tf_efficientnet_em 78.508 78.708 21.492 21.292 94.234 94.314 5.766 5.686 26.77 6.90 224 240 0.875 0.882 bilinear bicubic
137 regnetx_040 efficientnet_b1 78.486 78.698 21.514 21.302 94.242 94.144 5.758 5.856 22.12 7.79 224 240 0.875 bicubic
138 resnest26d dla169 78.482 78.688 21.518 21.312 94.29 94.336 5.71 5.664 17.07 53.39 224 0.875 bilinear
139 dla60_res2net tf_efficientnet_b0_ns 78.472 78.658 21.528 21.342 94.204 94.376 5.796 5.624 21.15 5.29 224 0.875 bilinear bicubic
140 wide_resnet50_2 res2net50_26w_6s 78.468 78.570 21.532 21.430 94.086 94.124 5.914 5.876 68.88 37.05 224 0.875 bilinear
141 dla60_res2next xception41 78.448 78.516 21.552 21.484 94.144 94.278 5.856 5.722 17.33 26.97 224 299 0.875 0.903 bilinear bicubic
142 hrnet_w32 dla102x 78.448 78.510 21.552 21.490 94.188 94.228 5.812 5.772 41.23 26.31 224 0.875 bilinear
143 selecsls60b regnetx_040 78.418 78.482 21.582 21.518 94.166 94.244 5.834 5.756 32.77 22.12 224 0.875 bicubic
144 seresnet101 resnest26d 78.396 78.478 21.604 21.522 94.258 94.298 5.742 5.702 49.33 17.07 224 0.875 bilinear
145 resnet152 wide_resnet50_2 78.312 78.478 21.688 21.522 94.046 94.094 5.954 5.906 60.19 68.88 224 0.875 bilinear
146 dla60x dla60_res2net 78.242 78.464 21.758 21.536 94.022 94.206 5.978 5.794 17.65 20.85 224 0.875 bilinear
147 efficientnet_b1_pruned hrnet_w32 78.242 78.450 21.758 21.550 93.832 94.186 6.168 5.814 6.33 41.23 240 224 0.882 0.875 bicubic bilinear
148 res2next50 dla60_res2next 78.242 78.440 21.758 21.560 93.892 94.152 6.108 5.848 24.67 17.03 224 0.875 bilinear
149 hrnet_w30 selecsls60b 78.196 78.412 21.804 21.588 94.22 94.174 5.78 5.826 37.71 32.77 224 0.875 bilinear bicubic
150 regnetx_032 resnet152 78.166 78.312 21.834 21.688 94.08 94.038 5.92 5.962 15.3 60.19 224 0.875 bicubic bilinear
151 res2net50_14w_8s dla60x 78.152 78.246 21.848 21.754 93.842 94.018 6.158 5.982 25.06 17.35 224 0.875 bilinear
152 efficientnet_es res2next50 78.054 78.246 21.946 21.754 93.93 93.892 6.07 6.108 5.44 24.67 224 0.875 bicubic bilinear
153 dla102 efficientnet_b1_pruned 78.026 78.236 21.974 21.764 93.95 93.834 6.05 6.166 33.73 6.33 224 240 0.875 0.882 bilinear bicubic
154 gluon_resnet50_v1c hrnet_w30 78.01 78.206 21.99 21.794 93.988 94.222 6.012 5.778 25.58 37.71 224 0.875 bicubic bilinear
155 seresnext26tn_32x4d regnetx_032 77.99 78.172 22.01 21.828 93.748 94.088 6.252 5.912 16.81 15.30 224 0.875 bicubic
156 seresnext26t_32x4d res2net50_14w_8s 77.988 78.150 22.012 21.850 93.706 93.848 6.294 6.152 16.82 25.06 224 0.875 bicubic bilinear
157 selecsls60 efficientnet_es 77.982 78.066 22.018 21.934 93.832 93.926 6.168 6.074 30.67 5.44 224 0.875 bicubic
158 res2net50_26w_4s dla102 77.946 78.032 22.054 21.968 93.852 93.946 6.148 6.054 25.7 33.27 224 0.875 bilinear
159 tf_efficientnet_cc_b0_8e gluon_resnet50_v1c 77.908 78.012 22.092 21.988 93.656 93.988 6.344 6.012 24.01 25.58 224 0.875 bicubic
160 tf_inception_v3 seresnext26t_32x4d 77.856 77.998 22.144 22.002 93.644 93.708 6.356 6.292 23.83 16.82 299 224 0.875 bicubic
161 regnety_016 seresnext26tn_32x4d 77.852 77.986 22.148 22.014 93.716 93.746 6.284 6.254 11.2 16.81 224 0.875 bicubic
162 efficientnet_b0 selecsls60 77.692 77.982 22.308 22.018 93.532 93.828 6.468 6.172 5.29 30.67 224 0.875 bicubic
163 seresnet50 res2net50_26w_4s 77.636 77.964 22.364 22.036 93.752 93.854 6.248 6.146 28.09 25.70 224 0.875 bilinear
164 tv_resnext50_32x4d tf_efficientnet_cc_b0_8e 77.618 77.908 22.382 22.092 93.698 93.654 6.302 6.346 25.03 24.01 224 0.875 bilinear bicubic
165 seresnext26d_32x4d regnety_016 77.604 77.862 22.396 22.138 93.612 93.720 6.388 6.280 16.81 11.20 224 0.875 bicubic
166 adv_inception_v3 rexnet_100 77.58 77.858 22.42 22.142 93.724 93.870 6.276 6.130 23.83 4.80 299 224 0.875 bicubic
167 gluon_resnet50_v1b tf_inception_v3 77.578 77.858 22.422 22.142 93.718 93.638 6.282 6.362 25.56 23.83 224 299 0.875 bicubic
168 dpn68b efficientnet_b0 77.514 77.698 22.486 22.302 93.822 93.532 6.178 6.468 12.61 5.29 224 0.875 bicubic
169 res2net50_48w_2s tv_resnext50_32x4d 77.514 77.620 22.486 22.380 93.548 93.696 6.452 6.304 25.29 25.03 224 0.875 bilinear
170 tf_efficientnet_lite2 seresnext26d_32x4d 77.46 77.602 22.54 22.398 93.746 93.608 6.254 6.392 6.09 16.81 260 224 0.89 0.875 bicubic
171 inception_v3 adv_inception_v3 77.436 77.582 22.564 22.418 93.476 93.736 6.524 6.264 23.83 299 0.875 bicubic
172 resnet101 gluon_resnet50_v1b 77.374 77.580 22.626 22.420 93.546 93.716 6.454 6.284 44.55 25.56 224 0.875 bilinear bicubic
173 densenet161 res2net50_48w_2s 77.348 77.522 22.652 22.478 93.648 93.554 6.352 6.446 28.68 25.29 224 0.875 bicubic bilinear
174 tf_efficientnet_cc_b0_4e tf_efficientnet_lite2 77.304 77.468 22.696 22.532 93.332 93.754 6.668 6.246 13.31 6.09 224 260 0.875 0.890 bicubic
175 mobilenetv2_120d inception_v3 77.294 77.440 22.706 22.560 93.502 93.476 6.498 6.524 5.83 23.83 224 299 0.875 bicubic
176 densenet201 resnet101 77.29 77.374 22.71 22.626 93.478 93.540 6.522 6.460 20.01 44.55 224 0.875 bicubic bilinear
177 tf_efficientnet_es densenet161 77.264 77.358 22.736 22.642 93.6 93.638 6.4 6.362 5.44 28.68 224 0.875 bicubic
178 mixnet_m tf_efficientnet_cc_b0_4e 77.256 77.306 22.744 22.694 93.418 93.334 6.582 6.666 5.01 13.31 224 0.875 bicubic
179 selecsls42b densenet201 77.176 77.286 22.824 22.714 93.392 93.478 6.608 6.522 32.46 20.01 224 0.875 bicubic
180 seresnext26_32x4d mobilenetv2_120d 77.1 77.284 22.9 22.716 93.31 93.492 6.69 6.508 16.79 5.83 224 0.875 bicubic
181 tf_efficientnet_b0_ap mixnet_m 77.084 77.260 22.916 22.740 93.254 93.424 6.746 6.576 5.29 5.01 224 0.875 bicubic
182 dla60 tf_efficientnet_es 77.024 77.258 22.976 22.742 93.308 93.594 6.692 6.406 22.33 5.44 224 0.875 bilinear bicubic
183 tf_mixnet_m selecsls42b 76.95 77.174 23.05 22.826 93.156 93.390 6.844 6.610 5.01 32.46 224 0.875 bicubic
184 regnetx_016 tf_efficientnet_b0_ap 76.93 77.086 23.07 22.914 93.418 93.256 6.582 6.744 9.19 5.29 224 0.875 bicubic
185 skresnet34 dla60 76.91 77.032 23.09 22.968 93.316 93.318 6.684 6.682 22.28 22.04 224 0.875 bicubic bilinear
186 tf_efficientnet_b0 regnetx_016 76.84 76.950 23.16 23.050 93.226 93.420 6.774 6.580 5.29 9.19 224 0.875 bicubic
187 hrnet_w18 tf_mixnet_m 76.756 76.942 23.244 23.058 93.442 93.152 6.558 6.848 21.3 5.01 224 0.875 bilinear bicubic
188 resnet26d skresnet34 76.68 76.912 23.32 23.088 93.166 93.322 6.834 6.678 16.01 22.28 224 0.875 bicubic
189 tf_efficientnet_lite1 tf_efficientnet_b0 76.638 76.848 23.362 23.152 93.232 93.228 6.768 6.772 5.42 5.29 240 224 0.882 0.875 bicubic
190 densenetblur121d ese_vovnet19b_dw 76.576 76.798 23.424 23.202 93.19 93.268 6.81 6.732 8.0 6.54 224 0.875 bicubic
191 mobilenetv2_140 hrnet_w18 76.524 76.758 23.476 23.242 92.99 93.444 7.01 6.556 6.11 21.30 224 0.875 bicubic bilinear
192 regnety_008 resnet26d 76.314 76.696 23.686 23.304 93.062 93.150 6.938 6.850 6.26 16.01 224 0.875 bicubic
193 dpn68 tf_efficientnet_lite1 76.306 76.642 23.694 23.358 92.97 93.226 7.03 6.774 12.61 5.42 224 240 0.875 0.882 bicubic
194 tv_resnet50 densenetblur121d 76.13 76.588 23.87 23.412 92.862 93.192 7.138 6.808 25.56 8.00 224 0.875 bilinear bicubic
195 mixnet_s mobilenetv2_140 75.988 76.516 24.012 23.484 92.794 92.996 7.206 7.004 4.13 6.11 224 0.875 bicubic
196 densenet169 dpn68 75.912 76.318 24.088 23.682 93.024 92.978 6.976 7.022 14.15 12.61 224 0.875 bicubic
197 mobilenetv3_large_100 regnety_008 75.768 76.316 24.232 23.684 92.54 93.066 7.46 6.934 5.48 6.26 224 0.875 bicubic
198 tf_mixnet_s tv_resnet50 75.648 76.138 24.352 23.862 92.636 92.864 7.364 7.136 4.13 25.56 224 0.875 bicubic bilinear
199 mobilenetv3_rw mixnet_s 75.628 75.992 24.372 24.008 92.71 92.796 7.29 7.204 5.48 4.13 224 0.875 bicubic
200 densenet121 densenet169 75.574 75.906 24.426 24.094 92.656 93.026 7.344 6.974 7.98 14.15 224 0.875 bicubic
201 tf_mobilenetv3_large_100 mobilenetv3_large_100 75.516 75.766 24.484 24.234 92.6 92.542 7.4 7.458 5.48 224 0.875 bilinear bicubic
202 resnest14d tf_mixnet_s 75.504 75.650 24.496 24.350 92.514 92.628 7.486 7.372 10.61 4.13 224 0.875 bilinear bicubic
203 semnasnet_100 mobilenetv3_rw 75.456 75.634 24.544 24.366 92.592 92.708 7.408 7.292 3.89 5.48 224 0.875 bicubic
204 resnet26 densenet121 75.292 75.578 24.708 24.422 92.57 92.652 7.43 7.348 16.0 7.98 224 0.875 bicubic
205 regnety_006 tf_mobilenetv3_large_100 75.26 75.518 24.74 24.482 92.528 92.606 7.472 7.394 6.06 5.48 224 0.875 bicubic bilinear
206 hrnet_w18_small_v2 resnest14d 75.126 75.506 24.874 24.494 92.416 92.518 7.584 7.482 15.6 10.61 224 0.875 bilinear
207 fbnetc_100 efficientnet_lite0 75.12 75.484 24.88 24.516 92.386 92.510 7.614 7.490 5.57 4.65 224 0.875 bilinear bicubic
208 resnet34 semnasnet_100 75.112 75.448 24.888 24.552 92.288 92.604 7.712 7.396 21.8 3.89 224 0.875 bilinear bicubic
209 mobilenetv2_110d resnet26 75.052 75.292 24.948 24.708 92.18 92.570 7.82 7.430 4.52 16.00 224 0.875 bicubic
210 regnetx_008 regnety_006 75.022 75.246 24.978 24.754 92.344 92.532 7.656 7.468 7.26 6.06 224 0.875 bicubic
211 tf_efficientnet_lite0 fbnetc_100 74.842 75.124 25.158 24.876 92.17 92.386 7.83 7.614 4.65 5.57 224 0.875 bicubic bilinear
212 seresnet34 hrnet_w18_small_v2 74.808 75.114 25.192 24.886 92.126 92.416 7.874 7.584 21.96 15.60 224 0.875 bilinear
213 tv_densenet121 resnet34 74.752 75.110 25.248 24.890 92.152 92.284 7.848 7.716 7.98 21.80 224 0.875 bicubic bilinear
214 mnasnet_100 regnetx_008 74.656 75.038 25.344 24.962 92.126 92.336 7.874 7.664 4.38 7.26 224 0.875 bicubic
215 dla34 mobilenetv2_110d 74.636 75.036 25.364 24.964 92.064 92.186 7.936 7.814 15.78 4.52 224 0.875 bilinear bicubic
216 gluon_resnet34_v1b tf_efficientnet_lite0 74.58 74.830 25.42 25.170 91.988 92.176 8.012 7.824 21.8 4.65 224 0.875 bicubic
217 spnasnet_100 tv_densenet121 74.08 74.738 25.92 25.262 91.832 92.150 8.168 7.850 4.42 7.98 224 0.875 bilinear bicubic
218 regnety_004 mnasnet_100 74.026 74.658 25.974 25.342 91.748 92.114 8.252 7.886 4.34 4.38 224 0.875 bicubic
219 regnetx_006 dla34 73.862 74.630 26.138 25.370 91.68 92.078 8.32 7.922 6.2 15.74 224 0.875 bicubic bilinear
220 tf_mobilenetv3_large_075 gluon_resnet34_v1b 73.442 74.588 26.558 25.412 91.352 91.990 8.648 8.010 3.99 21.80 224 0.875 bilinear bicubic
221 tv_resnet34 spnasnet_100 73.314 74.084 26.686 25.916 91.42 91.818 8.58 8.182 21.8 4.42 224 0.875 bilinear
222 swsl_resnet18 regnety_004 73.286 74.034 26.714 25.966 91.732 91.752 8.268 8.248 11.69 4.34 224 0.875 bilinear bicubic
223 skresnet18 regnetx_006 73.044 73.852 26.956 26.148 91.178 91.672 8.822 8.328 11.96 6.20 224 0.875 bicubic
224 mobilenetv2_100 tf_mobilenetv3_large_075 72.978 73.438 27.022 26.562 91.016 91.350 8.984 8.650 3.5 3.99 224 0.875 bicubic bilinear
225 ssl_resnet18 tv_resnet34 72.6 73.312 27.4 26.688 91.416 91.426 8.584 8.574 11.69 21.80 224 0.875 bilinear
226 regnetx_004 swsl_resnet18 72.406 73.276 27.594 26.724 90.83 91.734 9.17 8.266 5.16 11.69 224 0.875 bicubic bilinear
227 hrnet_w18_small skresnet18 72.342 73.038 27.658 26.962 90.672 91.168 9.328 8.832 13.19 11.96 224 0.875 bilinear bicubic
228 tf_mobilenetv3_large_minimal_100 mobilenetv2_100 72.244 72.970 27.756 27.030 90.636 91.016 9.364 8.984 3.92 3.50 224 0.875 bilinear bicubic
229 seresnet18 ssl_resnet18 71.758 72.610 28.242 27.390 90.334 91.416 9.666 8.584 11.78 11.69 224 0.875 bicubic bilinear
230 gluon_resnet18_v1b regnetx_004 70.83 72.396 29.17 27.604 89.756 90.830 10.244 9.170 11.69 5.16 224 0.875 bicubic
231 regnety_002 hrnet_w18_small 70.282 72.342 29.718 27.658 89.54 90.678 10.46 9.322 3.16 13.19 224 0.875 bicubic bilinear
232 resnet18 tf_mobilenetv3_large_minimal_100 69.758 72.248 30.242 27.752 89.078 90.630 10.922 9.370 11.69 3.92 224 0.875 bilinear
233 regnetx_002 gluon_resnet18_v1b 68.754 70.836 31.246 29.164 88.548 89.762 11.452 10.238 2.68 11.69 224 0.875 bicubic
234 tf_mobilenetv3_small_100 regnety_002 67.918 70.252 32.082 29.748 87.662 89.540 12.338 10.460 2.54 3.16 224 0.875 bilinear bicubic
235 dla60x_c resnet18 67.908 69.748 32.092 30.252 88.434 89.078 11.566 10.922 1.34 11.69 224 0.875 bilinear
236 dla46x_c regnetx_002 65.98 68.762 34.02 31.238 86.98 88.556 13.02 11.444 1.08 2.68 224 0.875 bilinear bicubic
237 tf_mobilenetv3_small_075 tf_mobilenetv3_small_100 65.718 67.922 34.282 32.078 86.136 87.664 13.864 12.336 2.04 2.54 224 0.875 bilinear
238 dla46_c dla60x_c 64.878 67.892 35.122 32.108 86.286 88.426 13.714 11.574 1.31 1.32 224 0.875 bilinear
239 tf_mobilenetv3_small_minimal_100 dla46x_c 62.898 65.970 37.102 34.030 84.23 86.980 15.77 13.020 2.04 1.07 224 0.875 bilinear
240 tf_mobilenetv3_small_075 65.716 34.284 86.130 13.870 2.04 224 0.875 bilinear
241 dla46_c 64.866 35.134 86.292 13.708 1.30 224 0.875 bilinear
242 tf_mobilenetv3_small_minimal_100 62.906 37.094 84.230 15.770 2.04 224 0.875 bilinear

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results/results-imagenetv2-matched-frequency.csv
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@ -1,215 +1,242 @@
model,rank_diff,top1,top1_diff,top1_err,top5,top5_diff,top5_err,param_count,img_size,cropt_pct,interpolation
tf_efficientnet_l2_ns_475,+1,80.470,-7.764,19.530,95.730,-2.816,4.270,480.31,475,0.936,bicubic
tf_efficientnet_l2_ns,-1,80.250,-8.102,19.750,95.850,-2.798,4.150,480.31,800,0.960,bicubic
tf_efficientnet_b7_ns,=,78.520,-8.318,21.480,94.370,-3.724,5.630,66.35,600,0.949,bicubic
tf_efficientnet_b6_ns,=,77.280,-9.182,22.720,93.890,-3.994,6.110,43.04,528,0.942,bicubic
ig_resnext101_32x48d,+1,76.870,-8.572,23.130,93.320,-4.252,6.680,828.41,224,0.875,bilinear
ig_resnext101_32x32d,+5,76.840,-8.252,23.160,93.190,-4.246,6.810,468.53,224,0.875,bilinear
tf_efficientnet_b5_ns,-2,76.820,-9.260,23.180,93.580,-4.174,6.420,30.39,456,0.934,bicubic
tf_efficientnet_b7_ap,+2,76.090,-9.028,23.910,92.970,-4.282,7.030,66.35,600,0.949,bicubic
tf_efficientnet_b8_ap,-1,76.090,-9.278,23.910,92.730,-4.564,7.270,87.41,672,0.954,bicubic
ig_resnext101_32x16d,+7,75.710,-8.466,24.290,92.900,-4.296,7.100,194.03,224,0.875,bilinear
tf_efficientnet_b4_ns,-2,75.690,-9.468,24.310,93.040,-4.428,6.960,19.34,380,0.922,bicubic
swsl_resnext101_32x8d,+2,75.450,-8.844,24.550,92.750,-4.424,7.250,88.79,224,0.875,bilinear
tf_efficientnet_b6_ap,=,75.380,-9.406,24.620,92.440,-4.698,7.560,43.04,528,0.942,bicubic
tf_efficientnet_b8,-7,74.930,-10.440,25.070,92.320,-5.072,7.680,87.41,672,0.954,bicubic
tf_efficientnet_b7,-3,74.720,-10.212,25.280,92.220,-4.988,7.780,66.35,600,0.949,bicubic
tf_efficientnet_b5_ap,-1,74.590,-9.664,25.410,91.990,-4.986,8.010,30.39,456,0.934,bicubic
swsl_resnext101_32x4d,+7,74.150,-9.084,25.850,91.990,-4.766,8.010,44.18,224,0.875,bilinear
swsl_resnext101_32x16d,+4,74.010,-9.328,25.990,92.170,-4.682,7.830,194.03,224,0.875,bilinear
resnest200e,+1,73.930,-9.904,26.070,91.580,-5.258,8.420,70.20,320,0.875,bilinear
tf_efficientnet_b6,-2,73.900,-10.212,26.100,91.750,-5.134,8.250,43.04,528,0.942,bicubic
tf_efficientnet_b3_ns,-2,73.870,-10.184,26.130,91.860,-5.052,8.140,12.23,300,0.904,bicubic
ig_resnext101_32x8d,+7,73.660,-9.028,26.340,92.150,-4.482,7.850,88.79,224,0.875,bilinear
tf_efficientnet_b5,-2,73.540,-10.276,26.460,91.460,-5.290,8.540,30.39,456,0.934,bicubic
resnest269e,-8,73.460,-10.726,26.540,91.680,-5.242,8.320,110.93,416,0.875,bilinear
tf_efficientnet_b4_ap,-2,72.890,-10.358,27.110,90.980,-5.408,9.020,19.34,380,0.922,bicubic
swsl_resnext50_32x4d,+7,72.580,-9.600,27.420,90.840,-5.388,9.160,25.03,224,0.875,bilinear
resnest101e,=,72.550,-10.340,27.450,90.810,-5.514,9.190,48.28,256,0.875,bilinear
tresnet_xl_448,-3,72.550,-10.498,27.450,90.310,-5.864,9.690,78.44,448,0.875,bilinear
pnasnet5large,-1,72.370,-10.370,27.630,90.260,-5.780,9.740,86.06,331,0.875,bicubic
nasnetalarge,=,72.310,-10.248,27.690,90.510,-5.526,9.490,88.75,331,0.875,bicubic
tf_efficientnet_b4,-5,72.280,-10.736,27.720,90.600,-5.698,9.400,19.34,380,0.922,bicubic
tf_efficientnet_b2_ns,-1,72.270,-10.110,27.730,91.090,-5.162,8.910,9.11,260,0.890,bicubic
swsl_resnet50,+15,71.690,-9.490,28.310,90.510,-5.476,9.490,25.56,224,0.875,bilinear
tresnet_xl,+1,71.650,-10.420,28.350,89.630,-6.298,10.370,78.44,224,0.875,bilinear
tresnet_l_448,-3,71.600,-10.668,28.400,90.060,-5.918,9.940,55.99,448,0.875,bilinear
ecaresnet101d,-2,71.500,-10.666,28.500,90.310,-5.742,9.690,44.57,224,0.875,bicubic
ssl_resnext101_32x8d,+4,71.490,-10.136,28.510,90.470,-5.568,9.530,88.79,224,0.875,bilinear
ssl_resnext101_32x16d,-1,71.400,-10.436,28.600,90.550,-5.544,9.450,194.03,224,0.875,bilinear
tresnet_m_448,=,71.000,-10.712,29.000,88.680,-6.890,11.320,31.39,448,0.875,bilinear
resnest50d_4s2x40d,+9,70.940,-10.174,29.060,89.710,-5.858,10.290,30.42,224,0.875,bicubic
tf_efficientnet_b3_ap,-3,70.920,-10.908,29.080,89.430,-6.194,10.570,12.23,300,0.904,bicubic
efficientnet_b3a,-6,70.870,-11.004,29.130,89.720,-6.120,10.280,12.23,320,1.000,bicubic
tf_efficientnet_b1_ns,+2,70.850,-10.536,29.150,90.110,-5.628,9.890,7.79,240,0.882,bicubic
tresnet_l,=,70.830,-10.658,29.170,89.610,-6.018,10.390,55.99,224,0.875,bilinear
efficientnet_b3,-2,70.760,-10.738,29.240,89.840,-5.878,10.160,12.23,300,0.904,bicubic
tf_efficientnet_b3,-6,70.620,-11.020,29.380,89.440,-6.282,10.560,12.23,300,0.904,bicubic
gluon_senet154,=,70.600,-10.624,29.400,88.920,-6.436,11.080,115.09,224,0.875,bicubic
ssl_resnext101_32x4d,+5,70.500,-10.428,29.500,89.760,-5.968,10.240,44.18,224,0.875,bilinear
senet154,-3,70.480,-10.824,29.520,88.990,-6.508,11.010,115.09,224,0.875,bilinear
gluon_seresnext101_64x4d,+5,70.440,-10.450,29.560,89.350,-5.954,10.650,88.23,224,0.875,bicubic
resnest50d_1s4x24d,=,70.430,-10.560,29.570,89.240,-6.082,10.760,25.68,224,0.875,bicubic
tf_efficientnet_lite4,-10,70.430,-11.098,29.570,89.120,-6.548,10.880,13.01,380,0.920,bilinear
resnest50d,-1,70.420,-10.538,29.580,88.760,-6.622,11.240,27.48,224,0.875,bilinear
gluon_resnet152_v1s,-4,70.320,-10.692,29.680,88.870,-6.546,11.130,60.32,224,0.875,bicubic
ecaresnet101d_pruned,+3,70.120,-10.688,29.880,89.580,-6.048,10.420,24.88,224,0.875,bicubic
inception_resnet_v2,+9,70.120,-10.340,29.880,88.680,-6.630,11.320,55.84,299,0.897,bicubic
gluon_seresnext101_32x4d,-3,70.010,-10.892,29.990,88.910,-6.384,11.090,48.96,224,0.875,bicubic
gluon_resnet152_v1d,+6,69.950,-10.520,30.050,88.470,-6.736,11.530,60.21,224,0.875,bicubic
ecaresnet50d,+2,69.830,-10.774,30.170,89.370,-5.952,10.630,25.58,224,0.875,bicubic
gluon_resnext101_64x4d,+2,69.690,-10.912,30.310,88.260,-6.734,11.740,83.46,224,0.875,bicubic
ssl_resnext50_32x4d,+11,69.690,-10.638,30.310,89.420,-5.984,10.580,25.03,224,0.875,bilinear
tresnet_m,-3,69.650,-11.146,30.350,88.000,-6.856,12.000,31.39,224,0.875,bilinear
efficientnet_b3_pruned,-7,69.580,-11.276,30.420,88.970,-6.270,11.030,9.86,300,0.904,bicubic
ens_adv_inception_resnet_v2,+19,69.520,-10.456,30.480,88.500,-6.446,11.500,55.84,299,0.897,bicubic
efficientnet_b2a,-5,69.490,-11.118,30.510,88.680,-6.630,11.320,9.11,288,1.000,bicubic
inception_v4,+13,69.350,-10.806,30.650,88.780,-6.194,11.220,42.68,299,0.875,bicubic
seresnext101_32x4d,+10,69.340,-10.896,30.660,88.050,-6.978,11.950,48.96,224,0.875,bilinear
ecaresnetlight,-2,69.330,-11.124,30.670,89.220,-6.036,10.780,30.16,224,0.875,bicubic
gluon_resnet152_v1c,+16,69.130,-10.786,30.870,87.890,-6.952,12.110,60.21,224,0.875,bicubic
mixnet_xl,-7,69.080,-11.398,30.920,88.310,-6.622,11.690,11.90,224,0.875,bicubic
efficientnet_b2,-2,69.000,-11.402,31.000,88.620,-6.456,11.380,9.11,260,0.875,bicubic
gluon_resnet101_v1d,-4,68.990,-11.434,31.010,88.080,-6.940,11.920,44.57,224,0.875,bicubic
gluon_xception65,+24,68.980,-10.624,31.020,88.320,-6.428,11.680,39.92,299,0.875,bicubic
gluon_resnext101_32x4d,-3,68.960,-11.374,31.040,88.340,-6.586,11.660,44.18,224,0.875,bicubic
tf_efficientnet_b2_ap,-2,68.930,-11.376,31.070,88.340,-6.688,11.660,9.11,260,0.890,bicubic
gluon_resnet152_v1b,+18,68.810,-10.882,31.190,87.710,-7.028,12.290,60.19,224,0.875,bicubic
dpn131,+12,68.760,-11.068,31.240,87.480,-7.224,12.520,79.25,224,0.875,bicubic
resnext50d_32x4d,+17,68.750,-10.924,31.250,88.310,-6.558,11.690,25.05,224,0.875,bicubic
tf_efficientnet_b2,+2,68.750,-11.340,31.250,87.950,-6.956,12.050,9.11,260,0.890,bicubic
gluon_resnet101_v1s,-6,68.720,-11.580,31.280,87.900,-7.250,12.100,44.67,224,0.875,bicubic
dpn107,-3,68.710,-11.454,31.290,88.130,-6.782,11.870,86.92,224,0.875,bicubic
gluon_seresnext50_32x4d,+4,68.670,-11.242,31.330,88.320,-6.498,11.680,27.56,224,0.875,bicubic
hrnet_w64,+17,68.630,-10.842,31.370,88.070,-6.580,11.930,128.06,224,0.875,bilinear
resnext50_32x4d,+7,68.610,-11.152,31.390,87.570,-7.030,12.430,25.03,224,0.875,bicubic
dpn98,+11,68.580,-11.056,31.420,87.660,-6.934,12.340,61.57,224,0.875,bicubic
ssl_resnet50,+24,68.420,-10.808,31.580,88.580,-6.252,11.420,25.56,224,0.875,bilinear
ecaresnet50d_pruned,+5,68.390,-11.328,31.610,88.370,-6.520,11.630,19.94,224,0.875,bicubic
skresnext50_32x4d,-8,68.390,-11.760,31.610,87.590,-7.054,12.410,27.48,224,0.875,bicubic
dla102x2,+12,68.340,-11.112,31.660,87.870,-6.774,12.130,41.75,224,0.875,bilinear
efficientnet_b2_pruned,-6,68.300,-11.618,31.700,88.100,-6.748,11.900,8.31,260,0.890,bicubic
gluon_resnext50_32x4d,+11,68.280,-11.076,31.720,87.320,-7.104,12.680,25.03,224,0.875,bicubic
tf_efficientnet_lite3,-2,68.230,-11.582,31.770,87.720,-7.194,12.280,8.20,300,0.904,bilinear
ese_vovnet39b,+10,68.190,-11.130,31.810,88.260,-6.450,11.740,24.57,224,0.875,bicubic
tf_efficientnet_el,-27,68.180,-12.268,31.820,88.350,-6.810,11.650,10.59,300,0.904,bicubic
dpn92,-13,68.010,-12.006,31.990,87.590,-7.248,12.410,37.67,224,0.875,bicubic
gluon_resnet50_v1d,+20,67.910,-11.164,32.090,87.120,-7.356,12.880,25.58,224,0.875,bicubic
seresnext50_32x4d,+18,67.870,-11.206,32.130,87.620,-6.814,12.380,27.56,224,0.875,bilinear
resnext101_32x8d,+6,67.850,-11.462,32.150,87.480,-7.046,12.520,88.79,224,0.875,bilinear
hrnet_w44,+23,67.770,-11.124,32.230,87.530,-6.840,12.470,67.06,224,0.875,bilinear
hrnet_w48,+5,67.770,-11.540,32.230,87.420,-7.098,12.580,77.47,224,0.875,bilinear
tf_efficientnet_b0_ns,+32,67.720,-10.932,32.280,88.080,-6.288,11.920,5.29,224,0.875,bicubic
xception,+16,67.670,-11.378,32.330,87.570,-6.822,12.430,22.86,299,0.897,bicubic
dla169,+26,67.610,-11.100,32.390,87.560,-6.778,12.440,53.99,224,0.875,bilinear
gluon_inception_v3,+22,67.590,-11.214,32.410,87.460,-6.920,12.540,23.83,299,0.875,bicubic
hrnet_w40,+16,67.590,-11.344,32.410,87.130,-7.336,12.870,57.56,224,0.875,bilinear
gluon_resnet101_v1c,-7,67.560,-11.984,32.440,87.160,-7.426,12.840,44.57,224,0.875,bicubic
seresnet152,+25,67.550,-11.108,32.450,87.390,-6.984,12.610,66.82,224,0.875,bilinear
res2net50_26w_8s,+4,67.530,-11.680,32.470,87.270,-7.092,12.730,48.40,224,0.875,bilinear
tf_efficientnet_b1_ap,=,67.520,-11.758,32.480,87.770,-6.538,12.230,7.79,240,0.882,bicubic
tf_efficientnet_cc_b1_8e,-3,67.480,-11.818,32.520,87.310,-7.054,12.690,39.72,240,0.882,bicubic
gluon_resnet101_v1b,-5,67.450,-11.854,32.550,87.230,-7.294,12.770,44.55,224,0.875,bicubic
res2net101_26w_4s,+2,67.450,-11.746,32.550,87.010,-7.430,12.990,45.21,224,0.875,bilinear
resnet50,+6,67.440,-11.592,32.560,87.420,-6.964,12.580,25.56,224,0.875,bicubic
resnetblur50,-6,67.440,-11.850,32.560,87.430,-7.202,12.570,25.56,224,0.875,bicubic
resnest26d,+22,67.210,-11.272,32.790,87.180,-7.110,12.820,17.07,224,0.875,bilinear
efficientnet_b1,+14,67.160,-11.538,32.840,87.150,-7.002,12.850,7.79,240,0.875,bicubic
seresnet101,+26,67.150,-11.246,32.850,87.050,-7.208,12.950,49.33,224,0.875,bilinear
gluon_resnet50_v1s,+10,67.100,-11.612,32.900,86.860,-7.382,13.140,25.68,224,0.875,bicubic
dla60x,+26,67.080,-11.162,32.920,87.170,-6.852,12.830,17.65,224,0.875,bilinear
dla60_res2net,+18,67.030,-11.442,32.970,87.140,-7.064,12.860,21.15,224,0.875,bilinear
resnet152,+23,67.020,-11.292,32.980,87.570,-6.476,12.430,60.19,224,0.875,bilinear
dla102x,+13,67.000,-11.508,33.000,86.770,-7.464,13.230,26.77,224,0.875,bilinear
mixnet_l,-3,66.970,-12.006,33.030,86.940,-7.244,13.060,7.33,224,0.875,bicubic
res2net50_26w_6s,+10,66.910,-11.664,33.090,86.900,-7.226,13.100,37.05,224,0.875,bilinear
efficientnet_es,+26,66.890,-11.164,33.110,86.730,-7.200,13.270,5.44,224,0.875,bicubic
tf_efficientnet_b1,-1,66.890,-11.942,33.110,87.040,-7.156,12.960,7.79,240,0.882,bicubic
tf_efficientnet_em,+4,66.870,-11.828,33.130,86.980,-7.340,13.020,6.90,240,0.882,bicubic
hrnet_w32,+13,66.790,-11.658,33.210,87.290,-6.898,12.710,41.23,224,0.875,bilinear
tf_mixnet_l,-2,66.780,-11.990,33.220,86.460,-7.544,13.540,7.33,224,0.875,bicubic
hrnet_w30,+18,66.760,-11.436,33.240,86.790,-7.430,13.210,37.71,224,0.875,bilinear
selecsls60b,+11,66.720,-11.698,33.280,86.540,-7.626,13.460,32.77,224,0.875,bicubic
wide_resnet101_2,-8,66.680,-12.166,33.320,87.040,-7.244,12.960,126.89,224,0.875,bilinear
wide_resnet50_2,+6,66.650,-11.818,33.350,86.810,-7.276,13.190,68.88,224,0.875,bilinear
dla60_res2next,+6,66.640,-11.808,33.360,87.020,-7.124,12.980,17.33,224,0.875,bilinear
adv_inception_v3,+30,66.600,-10.980,33.400,86.560,-7.164,13.440,23.83,299,0.875,bicubic
dla102,+16,66.550,-11.476,33.450,86.910,-7.040,13.090,33.73,224,0.875,bilinear
gluon_resnet50_v1c,+16,66.540,-11.470,33.460,86.160,-7.828,13.840,25.58,224,0.875,bicubic
tf_inception_v3,+21,66.420,-11.436,33.580,86.680,-6.964,13.320,23.83,299,0.875,bicubic
efficientnet_b0,+22,66.250,-11.442,33.750,85.950,-7.582,14.050,5.29,224,0.875,bicubic
seresnet50,+22,66.240,-11.396,33.760,86.330,-7.422,13.670,28.09,224,0.875,bilinear
selecsls60,+15,66.220,-11.762,33.780,86.330,-7.502,13.670,30.67,224,0.875,bicubic
tf_efficientnet_cc_b0_8e,+16,66.210,-11.698,33.790,86.220,-7.436,13.780,24.01,224,0.875,bicubic
tv_resnext50_32x4d,+20,66.180,-11.438,33.820,86.040,-7.658,13.960,25.03,224,0.875,bilinear
res2net50_26w_4s,+13,66.170,-11.776,33.830,86.600,-7.252,13.400,25.70,224,0.875,bilinear
inception_v3,+25,66.120,-11.316,33.880,86.340,-7.136,13.660,23.83,299,0.875,bicubic
efficientnet_b1_pruned,=,66.080,-12.162,33.920,86.580,-7.252,13.420,6.33,240,0.882,bicubic
gluon_resnet50_v1b,+19,66.040,-11.538,33.960,86.270,-7.448,13.730,25.56,224,0.875,bicubic
res2net50_14w_8s,+2,66.020,-12.132,33.980,86.240,-7.602,13.760,25.06,224,0.875,bilinear
densenet161,+23,65.850,-11.498,34.150,86.460,-7.188,13.540,28.68,224,0.875,bicubic
res2next50,-3,65.850,-12.392,34.150,85.830,-8.062,14.170,24.67,224,0.875,bilinear
seresnext26tn_32x4d,+3,65.850,-12.140,34.150,85.680,-8.068,14.320,16.81,224,0.875,bicubic
skresnet34,+32,65.770,-11.140,34.230,85.960,-7.356,14.040,22.28,224,0.875,bicubic
resnet101,+18,65.680,-11.694,34.320,85.980,-7.566,14.020,44.55,224,0.875,bilinear
dpn68b,+13,65.600,-11.914,34.400,85.940,-7.882,14.060,12.61,224,0.875,bicubic
seresnext26t_32x4d,=,65.600,-12.388,34.400,86.090,-7.616,13.910,16.82,224,0.875,bicubic
selecsls42b,+22,65.590,-11.586,34.410,85.830,-7.562,14.170,32.46,224,0.875,bicubic
tf_efficientnet_b0_ap,+23,65.490,-11.594,34.510,85.550,-7.704,14.450,5.29,224,0.875,bicubic
seresnext26d_32x4d,+6,65.420,-12.184,34.580,85.970,-7.642,14.030,16.81,224,0.875,bicubic
tf_efficientnet_lite2,+10,65.390,-12.070,34.610,86.030,-7.716,13.970,6.09,260,0.890,bicubic
res2net50_48w_2s,+8,65.320,-12.194,34.680,85.960,-7.588,14.040,25.29,224,0.875,bilinear
densenetblur121d,+28,65.300,-11.276,34.700,85.710,-7.480,14.290,8.00,224,0.875,bicubic
densenet201,+13,65.280,-12.010,34.720,85.670,-7.808,14.330,20.01,224,0.875,bicubic
tf_efficientnet_es,+13,65.240,-12.024,34.760,85.540,-8.060,14.460,5.44,224,0.875,bicubic
dla60,+17,65.220,-11.804,34.780,85.750,-7.558,14.250,22.33,224,0.875,bilinear
tf_efficientnet_cc_b0_4e,+8,65.130,-12.174,34.870,85.130,-8.202,14.870,13.31,224,0.875,bicubic
mobilenetv2_120d,+8,65.040,-12.254,34.960,85.990,-7.512,14.010,5.83,224,0.875,bicubic
seresnext26_32x4d,+12,65.040,-12.060,34.960,85.650,-7.660,14.350,16.79,224,0.875,bicubic
hrnet_w18,+18,64.910,-11.846,35.090,85.750,-7.692,14.250,21.30,224,0.875,bilinear
densenet169,+26,64.780,-11.132,35.220,85.250,-7.774,14.750,14.15,224,0.875,bicubic
mixnet_m,+7,64.690,-12.566,35.310,85.470,-7.948,14.530,5.01,224,0.875,bicubic
resnet26d,+16,64.630,-12.050,35.370,85.120,-8.046,14.880,16.01,224,0.875,bicubic
tf_efficientnet_lite1,+16,64.370,-12.268,35.630,85.490,-7.742,14.510,5.42,240,0.882,bicubic
tf_efficientnet_b0,+12,64.290,-12.550,35.710,85.250,-7.976,14.750,5.29,224,0.875,bicubic
tf_mixnet_m,+8,64.270,-12.680,35.730,85.090,-8.066,14.910,5.01,224,0.875,bicubic
dpn68,+17,64.220,-12.086,35.780,85.180,-7.790,14.820,12.61,224,0.875,bicubic
mobilenetv2_140,+14,64.050,-12.474,35.950,85.020,-7.970,14.980,6.11,224,0.875,bicubic
densenet121,+22,63.740,-11.834,36.260,84.630,-8.026,15.370,7.98,224,0.875,bicubic
resnest14d,+23,63.600,-11.904,36.400,84.220,-8.294,15.780,10.61,224,0.875,bilinear
tf_mixnet_s,+18,63.590,-12.058,36.410,84.270,-8.366,15.730,4.13,224,0.875,bicubic
resnet26,+23,63.450,-11.842,36.550,84.270,-8.300,15.730,16.00,224,0.875,bicubic
mixnet_s,+13,63.380,-12.608,36.620,84.710,-8.084,15.290,4.13,224,0.875,bicubic
mobilenetv3_large_100,+14,63.360,-12.408,36.640,84.080,-8.460,15.920,5.48,224,0.875,bicubic
tv_resnet50,+10,63.330,-12.800,36.670,84.650,-8.212,15.350,25.56,224,0.875,bilinear
mobilenetv3_rw,+14,63.230,-12.398,36.770,84.520,-8.190,15.480,5.48,224,0.875,bicubic
semnasnet_100,+17,63.120,-12.336,36.880,84.530,-8.062,15.470,3.89,224,0.875,bicubic
tv_densenet121,+26,62.940,-11.812,37.060,84.260,-7.892,15.740,7.98,224,0.875,bicubic
seresnet34,+24,62.890,-11.918,37.110,84.220,-7.906,15.780,21.96,224,0.875,bilinear
hrnet_w18_small_v2,+17,62.830,-12.296,37.170,83.970,-8.446,16.030,15.60,224,0.875,bilinear
mobilenetv2_110d,+19,62.820,-12.232,37.180,84.480,-7.700,15.520,4.52,224,0.875,bicubic
resnet34,+17,62.820,-12.292,37.180,84.120,-8.168,15.880,21.80,224,0.875,bilinear
swsl_resnet18,+30,62.730,-10.556,37.270,84.300,-7.432,15.700,11.69,224,0.875,bilinear
tf_efficientnet_lite0,+18,62.580,-12.262,37.420,84.250,-7.920,15.750,4.65,224,0.875,bicubic
gluon_resnet34_v1b,+22,62.560,-12.020,37.440,84.000,-7.988,16.000,21.80,224,0.875,bicubic
dla34,+20,62.510,-12.126,37.490,83.920,-8.144,16.080,15.78,224,0.875,bilinear
tf_mobilenetv3_large_100,+5,62.470,-13.046,37.530,83.960,-8.640,16.040,5.48,224,0.875,bilinear
fbnetc_100,+10,62.430,-12.690,37.570,83.390,-8.996,16.610,5.57,224,0.875,bilinear
mnasnet_100,+16,61.910,-12.746,38.090,83.710,-8.416,16.290,4.38,224,0.875,bicubic
ssl_resnet18,+26,61.490,-11.110,38.510,83.330,-8.086,16.670,11.69,224,0.875,bilinear
spnasnet_100,+17,61.210,-12.870,38.790,82.770,-9.062,17.230,4.42,224,0.875,bilinear
tv_resnet34,+20,61.200,-12.114,38.800,82.720,-8.700,17.280,21.80,224,0.875,bilinear
skresnet18,+21,60.850,-12.194,39.150,82.880,-8.298,17.120,11.96,224,0.875,bicubic
tf_mobilenetv3_large_075,+17,60.380,-13.062,39.620,81.960,-9.392,18.040,3.99,224,0.875,bilinear
mobilenetv2_100,+20,60.160,-12.818,39.840,82.240,-8.776,17.760,3.50,224,0.875,bicubic
seresnet18,+24,59.810,-11.948,40.190,81.680,-8.654,18.320,11.78,224,0.875,bicubic
tf_mobilenetv3_large_minimal_100,+22,59.070,-13.174,40.930,81.140,-9.496,18.860,3.92,224,0.875,bilinear
hrnet_w18_small,+20,58.970,-13.372,41.030,81.340,-9.332,18.660,13.19,224,0.875,bilinear
gluon_resnet18_v1b,+22,58.320,-12.510,41.680,80.960,-8.796,19.040,11.69,224,0.875,bicubic
resnet18,+23,57.180,-12.578,42.820,80.190,-8.888,19.810,11.69,224,0.875,bilinear
dla60x_c,+25,56.020,-11.888,43.980,78.960,-9.474,21.040,1.34,224,0.875,bilinear
tf_mobilenetv3_small_100,+23,54.510,-13.408,45.490,77.080,-10.582,22.920,2.54,224,0.875,bilinear
dla46x_c,+24,53.080,-12.900,46.920,76.840,-10.140,23.160,1.08,224,0.875,bilinear
dla46_c,+25,52.200,-12.678,47.800,75.680,-10.606,24.320,1.31,224,0.875,bilinear
tf_mobilenetv3_small_075,+23,52.150,-13.568,47.850,75.460,-10.676,24.540,2.04,224,0.875,bilinear
tf_mobilenetv3_small_minimal_100,+24,49.530,-13.368,50.470,73.050,-11.180,26.950,2.04,224,0.875,bilinear
model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff
tf_efficientnet_l2_ns_475,80.460,19.540,95.730,4.270,480.31,475,0.936,bicubic,-7.774,-2.816,+1
tf_efficientnet_l2_ns,80.250,19.750,95.840,4.160,480.31,800,0.960,bicubic,-8.102,-2.810,-1
tf_efficientnet_b7_ns,78.510,21.490,94.380,5.620,66.35,600,0.949,bicubic,-8.330,-3.714,0
tf_efficientnet_b6_ns,77.280,22.720,93.890,6.110,43.04,528,0.942,bicubic,-9.172,-3.992,0
ig_resnext101_32x48d,76.870,23.130,93.310,6.690,828.41,224,0.875,bilinear,-8.558,-4.262,+1
ig_resnext101_32x32d,76.840,23.160,93.200,6.800,468.53,224,0.875,bilinear,-8.254,-4.238,+5
tf_efficientnet_b5_ns,76.810,23.190,93.580,6.420,30.39,456,0.934,bicubic,-9.278,-4.172,-2
tf_efficientnet_b7_ap,76.090,23.910,92.970,7.030,66.35,600,0.949,bicubic,-9.030,-4.282,+2
tf_efficientnet_b8_ap,76.090,23.910,92.730,7.270,87.41,672,0.954,bicubic,-9.280,-4.564,-1
ig_resnext101_32x16d,75.720,24.280,92.910,7.090,194.03,224,0.875,bilinear,-8.450,-4.286,+7
tf_efficientnet_b4_ns,75.670,24.330,93.050,6.950,19.34,380,0.922,bicubic,-9.492,-4.420,-2
swsl_resnext101_32x8d,75.430,24.570,92.760,7.240,88.79,224,0.875,bilinear,-8.854,-4.416,+3
tf_efficientnet_b6_ap,75.380,24.620,92.440,7.560,43.04,528,0.942,bicubic,-9.408,-4.698,0
tf_efficientnet_b8,74.940,25.060,92.310,7.690,87.41,672,0.954,bicubic,-10.430,-5.080,-7
tf_efficientnet_b7,74.720,25.280,92.220,7.780,66.35,600,0.949,bicubic,-10.216,-4.984,-3
tf_efficientnet_b5_ap,74.600,25.400,91.990,8.010,30.39,456,0.934,bicubic,-9.652,-4.984,0
resnest200e,74.480,25.520,91.860,8.140,70.20,320,0.909,bicubic,-9.352,-5.034,+3
resnest269e,74.170,25.830,91.950,8.050,110.93,416,0.928,bicubic,-10.348,-5.036,-4
swsl_resnext101_32x4d,74.140,25.860,91.990,8.010,44.18,224,0.875,bilinear,-9.090,-4.770,+5
swsl_resnext101_32x16d,74.020,25.980,92.160,7.840,194.03,224,0.875,bilinear,-9.326,-4.686,+2
tf_efficientnet_b6,73.900,26.100,91.750,8.250,43.04,528,0.942,bicubic,-10.210,-5.136,-3
tf_efficientnet_b3_ns,73.890,26.110,91.870,8.130,12.23,300,0.904,bicubic,-10.158,-5.040,-3
ig_resnext101_32x8d,73.650,26.350,92.190,7.810,88.79,224,0.875,bilinear,-9.038,-4.446,+6
tf_efficientnet_b5,73.550,26.450,91.460,8.540,30.39,456,0.934,bicubic,-10.262,-5.288,-3
tf_efficientnet_b4_ap,72.890,27.110,90.980,9.020,19.34,380,0.922,bicubic,-10.358,-5.412,-2
pnasnet5large,72.610,27.390,90.510,9.490,86.06,331,0.911,bicubic,-10.172,-5.530,+2
resnest101e,72.570,27.430,90.820,9.180,48.28,256,0.875,bilinear,-10.320,-5.500,0
swsl_resnext50_32x4d,72.560,27.440,90.870,9.130,25.03,224,0.875,bilinear,-9.622,-5.360,+5
tresnet_xl_448,72.550,27.450,90.310,9.690,78.44,448,0.875,bilinear,-10.500,-5.864,-4
tf_efficientnet_b4,72.290,27.710,90.590,9.410,19.34,380,0.922,bicubic,-10.732,-5.710,-4
tf_efficientnet_b2_ns,72.280,27.720,91.090,8.910,9.11,260,0.890,bicubic,-10.100,-5.158,0
nasnetalarge,72.230,27.770,90.470,9.530,88.75,331,0.911,bicubic,-10.390,-5.576,-2
swsl_resnet50,71.700,28.300,90.500,9.500,25.56,224,0.875,bilinear,-9.466,-5.472,+15
tresnet_xl,71.660,28.340,89.630,10.370,78.44,224,0.875,bilinear,-10.394,-6.306,+1
tresnet_l_448,71.600,28.400,90.050,9.950,55.99,448,0.875,bilinear,-10.668,-5.926,-3
ssl_resnext101_32x8d,71.500,28.500,90.460,9.540,88.79,224,0.875,bilinear,-10.116,-5.578,+6
ecaresnet101d,71.490,28.510,90.330,9.670,44.57,224,0.875,bicubic,-10.682,-5.716,-3
ssl_resnext101_32x16d,71.410,28.590,90.560,9.440,194.03,224,0.875,bilinear,-10.434,-5.536,-1
tresnet_m_448,70.990,29.010,88.680,11.320,31.39,448,0.875,bilinear,-10.724,-6.892,0
resnest50d_4s2x40d,70.950,29.050,89.710,10.290,30.42,224,0.875,bicubic,-10.158,-5.848,+9
tf_efficientnet_b3_ap,70.920,29.080,89.430,10.570,12.23,300,0.904,bicubic,-10.902,-6.194,-3
efficientnet_b3a,70.870,29.130,89.720,10.280,12.23,320,1.000,bicubic,-10.996,-6.116,-6
tf_efficientnet_b1_ns,70.870,29.130,90.120,9.880,7.79,240,0.882,bicubic,-10.518,-5.618,+3
rexnet_200,70.840,29.160,89.700,10.300,16.37,224,0.875,bicubic,-10.792,-5.968,-3
tresnet_l,70.840,29.160,89.630,10.370,55.99,224,0.875,bilinear,-10.648,-5.994,0
efficientnet_b3,70.760,29.240,89.850,10.150,12.23,300,0.904,bicubic,-10.734,-5.866,-2
tf_efficientnet_b3,70.640,29.360,89.440,10.560,12.23,300,0.904,bicubic,-10.996,-6.278,-7
gluon_senet154,70.600,29.400,88.920,11.080,115.09,224,0.875,bicubic,-10.634,-6.428,-1
ssl_resnext101_32x4d,70.530,29.470,89.760,10.240,44.18,224,0.875,bilinear,-10.394,-5.968,+4
gluon_seresnext101_64x4d,70.430,29.570,89.350,10.650,88.23,224,0.875,bicubic,-10.464,-5.958,+5
tf_efficientnet_lite4,70.430,29.570,89.110,10.890,13.01,380,0.920,bilinear,-11.106,-6.558,-8
resnest50d,70.410,29.590,88.760,11.240,27.48,224,0.875,bilinear,-10.564,-6.618,0
resnest50d_1s4x24d,70.400,29.600,89.220,10.780,25.68,224,0.875,bicubic,-10.588,-6.102,-2
gluon_resnet152_v1s,70.290,29.710,88.850,11.150,60.32,224,0.875,bicubic,-10.726,-6.562,-4
ecaresnet101d_pruned,70.130,29.870,89.590,10.410,24.88,224,0.875,bicubic,-10.688,-6.038,+2
inception_resnet_v2,70.120,29.880,88.700,11.300,55.84,299,0.897,bicubic,-10.338,-6.606,+10
gluon_seresnext101_32x4d,70.010,29.990,88.900,11.100,48.96,224,0.875,bicubic,-10.894,-6.394,-3
regnety_320,70.000,30.000,88.890,11.110,145.05,224,0.875,bicubic,-10.812,-6.354,0
gluon_resnet152_v1d,69.960,30.040,88.490,11.510,60.21,224,0.875,bicubic,-10.514,-6.716,+5
ecaresnet50d,69.840,30.160,89.400,10.600,25.58,224,0.875,bicubic,-10.752,-5.920,+2
ssl_resnext50_32x4d,69.710,30.290,89.440,10.560,25.03,224,0.875,bilinear,-10.608,-5.966,+11
gluon_resnext101_64x4d,69.680,30.320,88.270,11.730,83.46,224,0.875,bicubic,-10.924,-6.718,-1
tresnet_m,69.660,30.340,87.990,12.010,31.39,224,0.875,bilinear,-11.142,-6.870,-4
efficientnet_b3_pruned,69.580,30.420,88.980,11.020,9.86,300,0.904,bicubic,-11.278,-6.262,-8
ens_adv_inception_resnet_v2,69.520,30.480,88.510,11.490,55.84,299,0.897,bicubic,-10.462,-6.426,+21
efficientnet_b2a,69.500,30.500,88.680,11.320,9.11,288,1.000,bicubic,-11.112,-6.638,-6
rexnet_150,69.470,30.530,88.980,11.020,9.73,224,0.875,bicubic,-10.840,-6.186,+6
regnetx_320,69.440,30.560,88.270,11.730,107.81,224,0.875,bicubic,-10.806,-6.756,+10
inception_v4,69.360,30.640,88.780,11.220,42.68,299,0.875,bicubic,-10.808,-6.188,+10
ecaresnetlight,69.340,30.660,89.220,10.780,30.16,224,0.875,bicubic,-11.122,-6.030,-5
xception71,69.320,30.680,88.260,11.740,42.34,299,0.903,bicubic,-10.554,-6.662,+20
gluon_xception65,69.160,30.840,88.090,11.910,39.92,299,0.903,bicubic,-10.556,-6.770,+26
gluon_resnet152_v1c,69.140,30.860,87.870,12.130,60.21,224,0.875,bicubic,-10.770,-6.970,+16
mixnet_xl,69.100,30.900,88.310,11.690,11.90,224,0.875,bicubic,-11.376,-6.626,-11
gluon_resnet101_v1d,69.010,30.990,88.100,11.900,44.57,224,0.875,bicubic,-11.404,-6.914,-7
xception65,68.980,31.020,88.480,11.520,39.92,299,0.903,bicubic,-10.572,-6.174,+26
seresnet50,68.980,31.020,88.710,11.290,28.09,224,0.875,bicubic,-11.294,-6.360,+1
efficientnet_b2,68.970,31.030,88.630,11.370,9.11,260,0.875,bicubic,-11.422,-6.446,-9
regnety_160,68.970,31.030,88.270,11.730,83.59,224,0.875,bicubic,-11.326,-6.692,-3
gluon_resnext101_32x4d,68.960,31.040,88.360,11.640,44.18,224,0.875,bicubic,-11.374,-6.566,-9
tf_efficientnet_b2_ap,68.920,31.080,88.350,11.650,9.11,260,0.890,bicubic,-11.380,-6.678,-6
cspdarknet53,68.890,31.110,88.600,11.400,27.64,256,0.887,bilinear,-11.168,-6.484,+1
regnety_120,68.850,31.150,88.330,11.670,51.82,224,0.875,bicubic,-11.516,-6.796,-13
gluon_resnet152_v1b,68.820,31.180,87.710,12.290,60.19,224,0.875,bicubic,-10.866,-7.026,+15
dpn131,68.770,31.230,87.470,12.530,79.25,224,0.875,bicubic,-11.052,-7.240,+8
cspresnext50,68.760,31.240,87.950,12.050,20.57,224,0.875,bilinear,-11.280,-6.994,-2
tf_efficientnet_b2,68.750,31.250,87.990,12.010,9.11,260,0.890,bicubic,-11.336,-6.918,-5
resnext50d_32x4d,68.740,31.260,88.300,11.700,25.05,224,0.875,bicubic,-10.936,-6.566,+12
gluon_resnet101_v1s,68.710,31.290,87.910,12.090,44.67,224,0.875,bicubic,-11.592,-7.250,-15
regnety_080,68.700,31.300,87.970,12.030,39.18,224,0.875,bicubic,-11.176,-6.860,0
dpn107,68.690,31.310,88.130,11.870,86.92,224,0.875,bicubic,-11.466,-6.780,-11
gluon_seresnext50_32x4d,68.670,31.330,88.310,11.690,27.56,224,0.875,bicubic,-11.248,-6.512,-5
hrnet_w64,68.640,31.360,88.050,11.950,128.06,224,0.875,bilinear,-10.834,-6.602,+13
resnext50_32x4d,68.640,31.360,87.570,12.430,25.03,224,0.875,bicubic,-11.128,-7.028,+1
dpn98,68.590,31.410,87.680,12.320,61.57,224,0.875,bicubic,-11.052,-6.918,+6
regnetx_160,68.530,31.470,88.450,11.550,54.28,224,0.875,bicubic,-11.326,-6.380,-4
rexnet_130,68.450,31.550,88.040,11.960,7.56,224,0.875,bicubic,-11.050,-6.642,+8
ecaresnet50d_pruned,68.420,31.580,88.370,11.630,19.94,224,0.875,bicubic,-11.296,-6.510,-1
regnety_064,68.420,31.580,88.080,11.920,30.58,224,0.875,bicubic,-11.302,-6.688,-3
ssl_resnet50,68.410,31.590,88.560,11.440,25.56,224,0.875,bilinear,-10.812,-6.272,+16
skresnext50_32x4d,68.350,31.650,87.570,12.430,27.48,224,0.875,bicubic,-11.806,-7.072,-20
dla102x2,68.330,31.670,87.890,12.110,41.28,224,0.875,bilinear,-11.118,-6.750,+5
efficientnet_b2_pruned,68.320,31.680,88.100,11.900,8.31,260,0.890,bicubic,-11.596,-6.756,-15
gluon_resnext50_32x4d,68.310,31.690,87.300,12.700,25.03,224,0.875,bicubic,-11.044,-7.126,+4
tf_efficientnet_lite3,68.230,31.770,87.740,12.260,8.20,300,0.904,bilinear,-11.590,-7.174,-11
ese_vovnet39b,68.210,31.790,88.240,11.760,24.57,224,0.875,bicubic,-11.110,-6.472,+3
tf_efficientnet_el,68.180,31.820,88.350,11.650,10.59,300,0.904,bicubic,-12.260,-6.814,-40
regnetx_120,68.150,31.850,87.660,12.340,46.11,224,0.875,bicubic,-11.446,-7.078,-6
dpn92,67.990,32.010,87.580,12.420,37.67,224,0.875,bicubic,-12.018,-7.256,-24
gluon_resnet50_v1d,67.940,32.060,87.130,12.870,25.58,224,0.875,bicubic,-11.134,-7.340,+12
regnetx_080,67.880,32.120,86.990,13.010,39.57,224,0.875,bicubic,-11.314,-7.570,+10
resnext101_32x8d,67.860,32.140,87.490,12.510,88.79,224,0.875,bilinear,-11.448,-7.028,-2
hrnet_w48,67.770,32.230,87.420,12.580,77.47,224,0.875,bilinear,-11.530,-7.092,0
hrnet_w44,67.740,32.260,87.560,12.440,67.06,224,0.875,bilinear,-11.156,-6.808,+14
tf_efficientnet_b0_ns,67.710,32.290,88.070,11.930,5.29,224,0.875,bicubic,-10.948,-6.306,+23
regnetx_064,67.680,32.320,87.520,12.480,26.21,224,0.875,bicubic,-11.392,-6.938,+7
xception,67.650,32.350,87.570,12.430,22.86,299,0.897,bicubic,-11.402,-6.822,+7
dpn68b,67.630,32.370,87.660,12.340,12.61,224,0.875,bicubic,-11.586,-6.754,0
dla169,67.610,32.390,87.590,12.410,53.39,224,0.875,bilinear,-11.078,-6.746,+18
gluon_inception_v3,67.590,32.410,87.470,12.530,23.83,299,0.875,bicubic,-11.216,-6.900,+12
regnety_040,67.580,32.420,87.510,12.490,20.65,224,0.875,bicubic,-11.640,-7.146,-5
gluon_resnet101_v1c,67.580,32.420,87.180,12.820,44.57,224,0.875,bicubic,-11.954,-7.398,-17
res2net50_26w_8s,67.570,32.430,87.280,12.720,48.40,224,0.875,bilinear,-11.628,-7.088,-4
hrnet_w40,67.560,32.440,87.140,12.860,57.56,224,0.875,bilinear,-11.360,-7.330,+3
tf_efficientnet_b1_ap,67.520,32.480,87.760,12.240,7.79,240,0.882,bicubic,-11.760,-6.546,-10
gluon_resnet101_v1b,67.460,32.540,87.240,12.760,44.55,224,0.875,bicubic,-11.846,-7.284,-14
tf_efficientnet_cc_b1_8e,67.450,32.550,87.310,12.690,39.72,240,0.882,bicubic,-11.858,-7.060,-16
res2net101_26w_4s,67.440,32.560,87.010,12.990,45.21,224,0.875,bilinear,-11.758,-7.422,-8
resnet50,67.440,32.560,87.420,12.580,25.56,224,0.875,bicubic,-11.598,-6.970,-4
resnetblur50,67.430,32.570,87.440,12.560,25.56,224,0.875,bicubic,-11.856,-7.198,-16
regnety_032,67.400,32.600,87.270,12.730,19.44,224,0.875,bicubic,-11.486,-7.142,-2
regnetx_032,67.290,32.710,87.000,13.000,15.30,224,0.875,bicubic,-10.882,-7.088,+22
xception41,67.250,32.750,87.200,12.800,26.97,299,0.903,bicubic,-11.266,-7.078,+7
resnest26d,67.200,32.800,87.170,12.830,17.07,224,0.875,bilinear,-11.278,-7.128,+9
efficientnet_b1,67.170,32.830,87.150,12.850,7.79,240,0.875,bicubic,-11.528,-6.994,+1
dla60x,67.100,32.900,87.190,12.810,17.35,224,0.875,bilinear,-11.146,-6.828,+14
gluon_resnet50_v1s,67.060,32.940,86.860,13.140,25.68,224,0.875,bicubic,-11.652,-7.378,-3
resnet152,67.050,32.950,87.550,12.450,60.19,224,0.875,bilinear,-11.262,-6.488,+11
dla60_res2net,67.020,32.980,87.160,12.840,20.85,224,0.875,bilinear,-11.444,-7.046,+6
dla102x,67.010,32.990,86.770,13.230,26.31,224,0.875,bilinear,-11.500,-7.458,+1
mixnet_l,66.940,33.060,86.910,13.090,7.33,224,0.875,bicubic,-12.036,-7.272,-15
res2net50_26w_6s,66.910,33.090,86.860,13.140,37.05,224,0.875,bilinear,-11.660,-7.264,-3
efficientnet_es,66.880,33.120,86.730,13.270,5.44,224,0.875,bicubic,-11.186,-7.196,+13
tf_efficientnet_b1,66.880,33.120,87.010,12.990,7.79,240,0.882,bicubic,-11.946,-7.188,-13
tf_efficientnet_em,66.880,33.120,86.970,13.030,6.90,240,0.882,bicubic,-11.828,-7.344,-10
regnetx_040,66.840,33.160,86.730,13.270,22.12,224,0.875,bicubic,-11.642,-7.514,-4
hrnet_w30,66.780,33.220,86.800,13.200,37.71,224,0.875,bilinear,-11.426,-7.422,+6
tf_mixnet_l,66.780,33.220,86.470,13.530,7.33,224,0.875,bicubic,-11.994,-7.528,-15
selecsls60b,66.760,33.240,86.530,13.470,32.77,224,0.875,bicubic,-11.652,-7.644,-1
hrnet_w32,66.750,33.250,87.300,12.700,41.23,224,0.875,bilinear,-11.700,-6.886,-4
wide_resnet101_2,66.730,33.270,87.030,12.970,126.89,224,0.875,bilinear,-12.126,-7.252,-21
wide_resnet50_2,66.650,33.350,86.800,13.200,68.88,224,0.875,bilinear,-11.828,-7.294,-9
adv_inception_v3,66.650,33.350,86.540,13.460,23.83,299,0.875,bicubic,-10.932,-7.196,+18
dla60_res2next,66.640,33.360,87.030,12.970,17.03,224,0.875,bilinear,-11.800,-7.122,-7
gluon_resnet50_v1c,66.560,33.440,86.180,13.820,25.58,224,0.875,bicubic,-11.452,-7.808,+3
dla102,66.540,33.460,86.910,13.090,33.27,224,0.875,bilinear,-11.492,-7.036,+1
tf_inception_v3,66.410,33.590,86.660,13.340,23.83,299,0.875,bicubic,-11.448,-6.978,+9
efficientnet_b0,66.290,33.710,85.960,14.040,5.29,224,0.875,bicubic,-11.408,-7.572,+9
selecsls60,66.210,33.790,86.340,13.660,30.67,224,0.875,bicubic,-11.772,-7.488,+2
tv_resnext50_32x4d,66.180,33.820,86.040,13.960,25.03,224,0.875,bilinear,-11.440,-7.656,+8
tf_efficientnet_cc_b0_8e,66.170,33.830,86.240,13.760,24.01,224,0.875,bicubic,-11.738,-7.414,+2
inception_v3,66.160,33.840,86.320,13.680,23.83,299,0.875,bicubic,-11.280,-7.156,+12
res2net50_26w_4s,66.140,33.860,86.600,13.400,25.70,224,0.875,bilinear,-11.824,-7.254,-1
efficientnet_b1_pruned,66.090,33.910,86.570,13.430,6.33,240,0.882,bicubic,-12.146,-7.264,-12
gluon_resnet50_v1b,66.070,33.930,86.260,13.740,25.56,224,0.875,bicubic,-11.510,-7.456,+6
rexnet_100,66.070,33.930,86.490,13.510,4.80,224,0.875,bicubic,-11.788,-7.380,-1
regnety_016,66.060,33.940,86.380,13.620,11.20,224,0.875,bicubic,-11.802,-7.340,-3
res2net50_14w_8s,66.020,33.980,86.250,13.750,25.06,224,0.875,bilinear,-12.130,-7.598,-13
seresnext26tn_32x4d,65.880,34.120,85.680,14.320,16.81,224,0.875,bicubic,-12.106,-8.066,-9
res2next50,65.850,34.150,85.840,14.160,24.67,224,0.875,bilinear,-12.396,-8.052,-19
densenet161,65.840,34.160,86.450,13.550,28.68,224,0.875,bicubic,-11.518,-7.188,+5
skresnet34,65.750,34.250,85.960,14.040,22.28,224,0.875,bicubic,-11.162,-7.362,+15
resnet101,65.690,34.310,85.980,14.020,44.55,224,0.875,bilinear,-11.684,-7.560,+2
selecsls42b,65.610,34.390,85.810,14.190,32.46,224,0.875,bicubic,-11.564,-7.580,+8
seresnext26t_32x4d,65.600,34.400,86.080,13.920,16.82,224,0.875,bicubic,-12.398,-7.628,-16
tf_efficientnet_b0_ap,65.490,34.510,85.580,14.420,5.29,224,0.875,bicubic,-11.596,-7.676,+7
seresnext26d_32x4d,65.410,34.590,85.970,14.030,16.81,224,0.875,bicubic,-12.192,-7.638,-8
tf_efficientnet_lite2,65.380,34.620,85.990,14.010,6.09,260,0.890,bicubic,-12.088,-7.764,-5
res2net50_48w_2s,65.350,34.650,85.960,14.040,25.29,224,0.875,bilinear,-12.172,-7.594,-7
densenet201,65.290,34.710,85.690,14.310,20.01,224,0.875,bicubic,-11.996,-7.788,-2
densenetblur121d,65.280,34.720,85.710,14.290,8.00,224,0.875,bicubic,-11.308,-7.482,+12
tf_efficientnet_es,65.220,34.780,85.550,14.450,5.44,224,0.875,bicubic,-12.038,-8.044,-1
dla60,65.200,34.800,85.760,14.240,22.04,224,0.875,bilinear,-11.832,-7.558,+1
ese_vovnet19b_dw,65.190,34.810,85.470,14.530,6.54,224,0.875,bicubic,-11.608,-7.798,+5
tf_efficientnet_cc_b0_4e,65.150,34.850,85.160,14.840,13.31,224,0.875,bicubic,-12.156,-8.174,-8
mobilenetv2_120d,65.030,34.970,85.960,14.040,5.83,224,0.875,bicubic,-12.254,-7.532,-7
hrnet_w18,64.920,35.080,85.740,14.260,21.30,224,0.875,bilinear,-11.838,-7.704,+3
densenet169,64.760,35.240,85.240,14.760,14.15,224,0.875,bicubic,-11.146,-7.786,+11
mixnet_m,64.700,35.300,85.450,14.550,5.01,224,0.875,bicubic,-12.560,-7.974,-9
resnet26d,64.680,35.320,85.120,14.880,16.01,224,0.875,bicubic,-12.016,-8.030,+1
regnetx_016,64.380,35.620,85.470,14.530,9.19,224,0.875,bicubic,-12.570,-7.950,-6
tf_efficientnet_lite1,64.380,35.620,85.470,14.530,5.42,240,0.882,bicubic,-12.262,-7.756,0
tf_efficientnet_b0,64.310,35.690,85.280,14.720,5.29,224,0.875,bicubic,-12.538,-7.948,-5
tf_mixnet_m,64.270,35.730,85.090,14.910,5.01,224,0.875,bicubic,-12.672,-8.062,-8
dpn68,64.230,35.770,85.180,14.820,12.61,224,0.875,bicubic,-12.088,-7.798,0
regnety_008,64.160,35.840,85.270,14.730,6.26,224,0.875,bicubic,-12.156,-7.796,0
mobilenetv2_140,64.060,35.940,85.040,14.960,6.11,224,0.875,bicubic,-12.456,-7.956,-3
densenet121,63.750,36.250,84.590,15.410,7.98,224,0.875,bicubic,-11.828,-8.062,+5
resnest14d,63.590,36.410,84.250,15.750,10.61,224,0.875,bilinear,-11.916,-8.268,+6
tf_mixnet_s,63.560,36.440,84.270,15.730,4.13,224,0.875,bicubic,-12.090,-8.358,+1
resnet26,63.470,36.530,84.260,15.740,16.00,224,0.875,bicubic,-11.822,-8.310,+7
mixnet_s,63.390,36.610,84.740,15.260,4.13,224,0.875,bicubic,-12.602,-8.056,-4
mobilenetv3_large_100,63.360,36.640,84.090,15.910,5.48,224,0.875,bicubic,-12.406,-8.452,-3
tv_resnet50,63.330,36.670,84.640,15.360,25.56,224,0.875,bilinear,-12.808,-8.224,-7
efficientnet_lite0,63.240,36.760,84.440,15.560,4.65,224,0.875,bicubic,-12.244,-8.070,+1
mobilenetv3_rw,63.220,36.780,84.510,15.490,5.48,224,0.875,bicubic,-12.414,-8.198,-4
semnasnet_100,63.150,36.850,84.520,15.480,3.89,224,0.875,bicubic,-12.298,-8.084,0
regnety_006,63.110,36.890,84.250,15.750,6.06,224,0.875,bicubic,-12.136,-8.282,+1
tv_densenet121,62.940,37.060,84.250,15.750,7.98,224,0.875,bicubic,-11.798,-7.900,+7
resnet34,62.870,37.130,84.140,15.860,21.80,224,0.875,bilinear,-12.240,-8.144,+2
mobilenetv2_110d,62.830,37.170,84.500,15.500,4.52,224,0.875,bicubic,-12.206,-7.686,+3
hrnet_w18_small_v2,62.800,37.200,83.980,16.020,15.60,224,0.875,bilinear,-12.314,-8.436,-1
swsl_resnet18,62.760,37.240,84.300,15.700,11.69,224,0.875,bilinear,-10.516,-7.434,+12
gluon_resnet34_v1b,62.570,37.430,83.990,16.010,21.80,224,0.875,bicubic,-12.018,-8.000,+5
tf_efficientnet_lite0,62.550,37.450,84.220,15.780,4.65,224,0.875,bicubic,-12.280,-7.956,0
regnetx_008,62.490,37.510,84.020,15.980,7.26,224,0.875,bicubic,-12.548,-8.316,-3
dla34,62.480,37.520,83.910,16.090,15.74,224,0.875,bilinear,-12.150,-8.168,+1
tf_mobilenetv3_large_100,62.460,37.540,83.970,16.030,5.48,224,0.875,bilinear,-13.058,-8.636,-14
fbnetc_100,62.440,37.560,83.380,16.620,5.57,224,0.875,bilinear,-12.684,-9.006,-9
mnasnet_100,61.900,38.100,83.710,16.290,4.38,224,0.875,bicubic,-12.758,-8.404,-3
regnety_004,61.870,38.130,83.430,16.570,4.34,224,0.875,bicubic,-12.164,-8.322,0
ssl_resnet18,61.480,38.520,83.300,16.700,11.69,224,0.875,bilinear,-11.130,-8.116,+6
regnetx_006,61.350,38.650,83.450,16.550,6.20,224,0.875,bicubic,-12.502,-8.222,-1
spnasnet_100,61.220,38.780,82.790,17.210,4.42,224,0.875,bilinear,-12.864,-9.028,-4
tv_resnet34,61.190,38.810,82.710,17.290,21.80,224,0.875,bilinear,-12.122,-8.716,-1
skresnet18,60.860,39.140,82.880,17.120,11.96,224,0.875,bicubic,-12.178,-8.288,0
tf_mobilenetv3_large_075,60.400,39.600,81.950,18.050,3.99,224,0.875,bilinear,-13.038,-9.400,-4
mobilenetv2_100,60.190,39.810,82.240,17.760,3.50,224,0.875,bicubic,-12.780,-8.776,-1
regnetx_004,59.410,40.590,81.690,18.310,5.16,224,0.875,bicubic,-12.986,-9.140,0
tf_mobilenetv3_large_minimal_100,59.070,40.930,81.150,18.850,3.92,224,0.875,bilinear,-13.178,-9.480,+1
hrnet_w18_small,58.950,41.050,81.340,18.660,13.19,224,0.875,bilinear,-13.392,-9.338,-1
gluon_resnet18_v1b,58.340,41.660,80.970,19.030,11.69,224,0.875,bicubic,-12.496,-8.792,0
resnet18,57.170,42.830,80.200,19.800,11.69,224,0.875,bilinear,-12.578,-8.878,+1
regnety_002,57.000,43.000,79.840,20.160,3.16,224,0.875,bicubic,-13.252,-9.700,-1
regnetx_002,56.050,43.950,79.210,20.790,2.68,224,0.875,bicubic,-12.712,-9.346,0
dla60x_c,56.000,44.000,78.930,21.070,1.32,224,0.875,bilinear,-11.892,-9.496,+1
tf_mobilenetv3_small_100,54.530,45.470,77.060,22.940,2.54,224,0.875,bilinear,-13.392,-10.604,-1
dla46x_c,53.050,46.950,76.870,23.130,1.07,224,0.875,bilinear,-12.920,-10.110,0
tf_mobilenetv3_small_075,52.160,47.840,75.470,24.530,2.04,224,0.875,bilinear,-13.556,-10.660,0
dla46_c,52.130,47.870,75.690,24.310,1.30,224,0.875,bilinear,-12.736,-10.602,0
tf_mobilenetv3_small_minimal_100,49.500,50.500,73.050,26.950,2.04,224,0.875,bilinear,-13.406,-11.180,0

1 model top1 top1_err top5 top5_err param_count img_size cropt_pct interpolation top1_diff top5_diff rank_diff
2 tf_efficientnet_l2_ns_475 80.470 80.460 19.530 19.540 95.730 4.270 480.31 475 0.936 bicubic -7.764 -7.774 -2.816 +1
3 tf_efficientnet_l2_ns 80.250 19.750 95.850 95.840 4.150 4.160 480.31 800 0.960 bicubic -8.102 -2.798 -2.810 -1
4 tf_efficientnet_b7_ns 78.520 78.510 21.480 21.490 94.370 94.380 5.630 5.620 66.35 600 0.949 bicubic -8.318 -8.330 -3.724 -3.714 = 0
5 tf_efficientnet_b6_ns 77.280 22.720 93.890 6.110 43.04 528 0.942 bicubic -9.182 -9.172 -3.994 -3.992 = 0
6 ig_resnext101_32x48d 76.870 23.130 93.320 93.310 6.680 6.690 828.41 224 0.875 bilinear -8.572 -8.558 -4.252 -4.262 +1
7 ig_resnext101_32x32d 76.840 23.160 93.190 93.200 6.810 6.800 468.53 224 0.875 bilinear -8.252 -8.254 -4.246 -4.238 +5
8 tf_efficientnet_b5_ns 76.820 76.810 23.180 23.190 93.580 6.420 30.39 456 0.934 bicubic -9.260 -9.278 -4.174 -4.172 -2
9 tf_efficientnet_b7_ap 76.090 23.910 92.970 7.030 66.35 600 0.949 bicubic -9.028 -9.030 -4.282 +2
10 tf_efficientnet_b8_ap 76.090 23.910 92.730 7.270 87.41 672 0.954 bicubic -9.278 -9.280 -4.564 -1
11 ig_resnext101_32x16d 75.710 75.720 24.290 24.280 92.900 92.910 7.100 7.090 194.03 224 0.875 bilinear -8.466 -8.450 -4.296 -4.286 +7
12 tf_efficientnet_b4_ns 75.690 75.670 24.310 24.330 93.040 93.050 6.960 6.950 19.34 380 0.922 bicubic -9.468 -9.492 -4.428 -4.420 -2
13 swsl_resnext101_32x8d 75.450 75.430 24.550 24.570 92.750 92.760 7.250 7.240 88.79 224 0.875 bilinear -8.844 -8.854 -4.424 -4.416 +2 +3
14 tf_efficientnet_b6_ap 75.380 24.620 92.440 7.560 43.04 528 0.942 bicubic -9.406 -9.408 -4.698 = 0
15 tf_efficientnet_b8 74.930 74.940 25.070 25.060 92.320 92.310 7.680 7.690 87.41 672 0.954 bicubic -10.440 -10.430 -5.072 -5.080 -7
16 tf_efficientnet_b7 74.720 25.280 92.220 7.780 66.35 600 0.949 bicubic -10.212 -10.216 -4.988 -4.984 -3
17 tf_efficientnet_b5_ap 74.590 74.600 25.410 25.400 91.990 8.010 30.39 456 0.934 bicubic -9.664 -9.652 -4.986 -4.984 -1 0
18 swsl_resnext101_32x4d resnest200e 74.150 74.480 25.850 25.520 91.990 91.860 8.010 8.140 44.18 70.20 224 320 0.875 0.909 bilinear bicubic -9.084 -9.352 -4.766 -5.034 +7 +3
19 swsl_resnext101_32x16d resnest269e 74.010 74.170 25.990 25.830 92.170 91.950 7.830 8.050 194.03 110.93 224 416 0.875 0.928 bilinear bicubic -9.328 -10.348 -4.682 -5.036 +4 -4
20 resnest200e swsl_resnext101_32x4d 73.930 74.140 26.070 25.860 91.580 91.990 8.420 8.010 70.20 44.18 320 224 0.875 bilinear -9.904 -9.090 -5.258 -4.770 +1 +5
21 tf_efficientnet_b6 swsl_resnext101_32x16d 73.900 74.020 26.100 25.980 91.750 92.160 8.250 7.840 43.04 194.03 528 224 0.942 0.875 bicubic bilinear -10.212 -9.326 -5.134 -4.686 -2 +2
22 tf_efficientnet_b3_ns tf_efficientnet_b6 73.870 73.900 26.130 26.100 91.860 91.750 8.140 8.250 12.23 43.04 300 528 0.904 0.942 bicubic -10.184 -10.210 -5.052 -5.136 -2 -3
23 ig_resnext101_32x8d tf_efficientnet_b3_ns 73.660 73.890 26.340 26.110 92.150 91.870 7.850 8.130 88.79 12.23 224 300 0.875 0.904 bilinear bicubic -9.028 -10.158 -4.482 -5.040 +7 -3
24 tf_efficientnet_b5 ig_resnext101_32x8d 73.540 73.650 26.460 26.350 91.460 92.190 8.540 7.810 30.39 88.79 456 224 0.934 0.875 bicubic bilinear -10.276 -9.038 -5.290 -4.446 -2 +6
25 resnest269e tf_efficientnet_b5 73.460 73.550 26.540 26.450 91.680 91.460 8.320 8.540 110.93 30.39 416 456 0.875 0.934 bilinear bicubic -10.726 -10.262 -5.242 -5.288 -8 -3
26 tf_efficientnet_b4_ap 72.890 27.110 90.980 9.020 19.34 380 0.922 bicubic -10.358 -5.408 -5.412 -2
27 swsl_resnext50_32x4d pnasnet5large 72.580 72.610 27.420 27.390 90.840 90.510 9.160 9.490 25.03 86.06 224 331 0.875 0.911 bilinear bicubic -9.600 -10.172 -5.388 -5.530 +7 +2
28 resnest101e 72.550 72.570 27.450 27.430 90.810 90.820 9.190 9.180 48.28 256 0.875 bilinear -10.340 -10.320 -5.514 -5.500 = 0
29 tresnet_xl_448 swsl_resnext50_32x4d 72.550 72.560 27.450 27.440 90.310 90.870 9.690 9.130 78.44 25.03 448 224 0.875 bilinear -10.498 -9.622 -5.864 -5.360 -3 +5
30 pnasnet5large tresnet_xl_448 72.370 72.550 27.630 27.450 90.260 90.310 9.740 9.690 86.06 78.44 331 448 0.875 bicubic bilinear -10.370 -10.500 -5.780 -5.864 -1 -4
31 nasnetalarge tf_efficientnet_b4 72.310 72.290 27.690 27.710 90.510 90.590 9.490 9.410 88.75 19.34 331 380 0.875 0.922 bicubic -10.248 -10.732 -5.526 -5.710 = -4
32 tf_efficientnet_b4 tf_efficientnet_b2_ns 72.280 27.720 90.600 91.090 9.400 8.910 19.34 9.11 380 260 0.922 0.890 bicubic -10.736 -10.100 -5.698 -5.158 -5 0
33 tf_efficientnet_b2_ns nasnetalarge 72.270 72.230 27.730 27.770 91.090 90.470 8.910 9.530 9.11 88.75 260 331 0.890 0.911 bicubic -10.110 -10.390 -5.162 -5.576 -1 -2
34 swsl_resnet50 71.690 71.700 28.310 28.300 90.510 90.500 9.490 9.500 25.56 224 0.875 bilinear -9.490 -9.466 -5.476 -5.472 +15
35 tresnet_xl 71.650 71.660 28.350 28.340 89.630 10.370 78.44 224 0.875 bilinear -10.420 -10.394 -6.298 -6.306 +1
36 tresnet_l_448 71.600 28.400 90.060 90.050 9.940 9.950 55.99 448 0.875 bilinear -10.668 -5.918 -5.926 -3
37 ecaresnet101d ssl_resnext101_32x8d 71.500 28.500 90.310 90.460 9.690 9.540 44.57 88.79 224 0.875 bicubic bilinear -10.666 -10.116 -5.742 -5.578 -2 +6
38 ssl_resnext101_32x8d ecaresnet101d 71.490 28.510 90.470 90.330 9.530 9.670 88.79 44.57 224 0.875 bilinear bicubic -10.136 -10.682 -5.568 -5.716 +4 -3
39 ssl_resnext101_32x16d 71.400 71.410 28.600 28.590 90.550 90.560 9.450 9.440 194.03 224 0.875 bilinear -10.436 -10.434 -5.544 -5.536 -1
40 tresnet_m_448 71.000 70.990 29.000 29.010 88.680 11.320 31.39 448 0.875 bilinear -10.712 -10.724 -6.890 -6.892 = 0
41 resnest50d_4s2x40d 70.940 70.950 29.060 29.050 89.710 10.290 30.42 224 0.875 bicubic -10.174 -10.158 -5.858 -5.848 +9
42 tf_efficientnet_b3_ap 70.920 29.080 89.430 10.570 12.23 300 0.904 bicubic -10.908 -10.902 -6.194 -3
43 efficientnet_b3a 70.870 29.130 89.720 10.280 12.23 320 1.000 bicubic -11.004 -10.996 -6.120 -6.116 -6
44 tf_efficientnet_b1_ns 70.850 70.870 29.150 29.130 90.110 90.120 9.890 9.880 7.79 240 0.882 bicubic -10.536 -10.518 -5.628 -5.618 +2 +3
45 tresnet_l rexnet_200 70.830 70.840 29.170 29.160 89.610 89.700 10.390 10.300 55.99 16.37 224 0.875 bilinear bicubic -10.658 -10.792 -6.018 -5.968 = -3
46 efficientnet_b3 tresnet_l 70.760 70.840 29.240 29.160 89.840 89.630 10.160 10.370 12.23 55.99 300 224 0.904 0.875 bicubic bilinear -10.738 -10.648 -5.878 -5.994 -2 0
47 tf_efficientnet_b3 efficientnet_b3 70.620 70.760 29.380 29.240 89.440 89.850 10.560 10.150 12.23 300 0.904 bicubic -11.020 -10.734 -6.282 -5.866 -6 -2
48 gluon_senet154 tf_efficientnet_b3 70.600 70.640 29.400 29.360 88.920 89.440 11.080 10.560 115.09 12.23 224 300 0.875 0.904 bicubic -10.624 -10.996 -6.436 -6.278 = -7
49 ssl_resnext101_32x4d gluon_senet154 70.500 70.600 29.500 29.400 89.760 88.920 10.240 11.080 44.18 115.09 224 0.875 bilinear bicubic -10.428 -10.634 -5.968 -6.428 +5 -1
50 senet154 ssl_resnext101_32x4d 70.480 70.530 29.520 29.470 88.990 89.760 11.010 10.240 115.09 44.18 224 0.875 bilinear -10.824 -10.394 -6.508 -5.968 -3 +4
51 gluon_seresnext101_64x4d 70.440 70.430 29.560 29.570 89.350 10.650 88.23 224 0.875 bicubic -10.450 -10.464 -5.954 -5.958 +5
52 resnest50d_1s4x24d tf_efficientnet_lite4 70.430 29.570 89.240 89.110 10.760 10.890 25.68 13.01 224 380 0.875 0.920 bicubic bilinear -10.560 -11.106 -6.082 -6.558 = -8
53 tf_efficientnet_lite4 resnest50d 70.430 70.410 29.570 29.590 89.120 88.760 10.880 11.240 13.01 27.48 380 224 0.920 0.875 bilinear -11.098 -10.564 -6.548 -6.618 -10 0
54 resnest50d resnest50d_1s4x24d 70.420 70.400 29.580 29.600 88.760 89.220 11.240 10.780 27.48 25.68 224 0.875 bilinear bicubic -10.538 -10.588 -6.622 -6.102 -1 -2
55 gluon_resnet152_v1s 70.320 70.290 29.680 29.710 88.870 88.850 11.130 11.150 60.32 224 0.875 bicubic -10.692 -10.726 -6.546 -6.562 -4
56 ecaresnet101d_pruned 70.120 70.130 29.880 29.870 89.580 89.590 10.420 10.410 24.88 224 0.875 bicubic -10.688 -6.048 -6.038 +3 +2
57 inception_resnet_v2 70.120 29.880 88.680 88.700 11.320 11.300 55.84 299 0.897 bicubic -10.340 -10.338 -6.630 -6.606 +9 +10
58 gluon_seresnext101_32x4d 70.010 29.990 88.910 88.900 11.090 11.100 48.96 224 0.875 bicubic -10.892 -10.894 -6.384 -6.394 -3
59 gluon_resnet152_v1d regnety_320 69.950 70.000 30.050 30.000 88.470 88.890 11.530 11.110 60.21 145.05 224 0.875 bicubic -10.520 -10.812 -6.736 -6.354 +6 0
60 ecaresnet50d gluon_resnet152_v1d 69.830 69.960 30.170 30.040 89.370 88.490 10.630 11.510 25.58 60.21 224 0.875 bicubic -10.774 -10.514 -5.952 -6.716 +2 +5
61 gluon_resnext101_64x4d ecaresnet50d 69.690 69.840 30.310 30.160 88.260 89.400 11.740 10.600 83.46 25.58 224 0.875 bicubic -10.912 -10.752 -6.734 -5.920 +2
62 ssl_resnext50_32x4d 69.690 69.710 30.310 30.290 89.420 89.440 10.580 10.560 25.03 224 0.875 bilinear -10.638 -10.608 -5.984 -5.966 +11
63 tresnet_m gluon_resnext101_64x4d 69.650 69.680 30.350 30.320 88.000 88.270 12.000 11.730 31.39 83.46 224 0.875 bilinear bicubic -11.146 -10.924 -6.856 -6.718 -3 -1
64 efficientnet_b3_pruned tresnet_m 69.580 69.660 30.420 30.340 88.970 87.990 11.030 12.010 9.86 31.39 300 224 0.904 0.875 bicubic bilinear -11.276 -11.142 -6.270 -6.870 -7 -4
65 ens_adv_inception_resnet_v2 efficientnet_b3_pruned 69.520 69.580 30.480 30.420 88.500 88.980 11.500 11.020 55.84 9.86 299 300 0.897 0.904 bicubic -10.456 -11.278 -6.446 -6.262 +19 -8
66 efficientnet_b2a ens_adv_inception_resnet_v2 69.490 69.520 30.510 30.480 88.680 88.510 11.320 11.490 9.11 55.84 288 299 1.000 0.897 bicubic -11.118 -10.462 -6.630 -6.426 -5 +21
67 inception_v4 efficientnet_b2a 69.350 69.500 30.650 30.500 88.780 88.680 11.220 11.320 42.68 9.11 299 288 0.875 1.000 bicubic -10.806 -11.112 -6.194 -6.638 +13 -6
68 seresnext101_32x4d rexnet_150 69.340 69.470 30.660 30.530 88.050 88.980 11.950 11.020 48.96 9.73 224 0.875 bilinear bicubic -10.896 -10.840 -6.978 -6.186 +10 +6
69 ecaresnetlight regnetx_320 69.330 69.440 30.670 30.560 89.220 88.270 10.780 11.730 30.16 107.81 224 0.875 bicubic -11.124 -10.806 -6.036 -6.756 -2 +10
70 gluon_resnet152_v1c inception_v4 69.130 69.360 30.870 30.640 87.890 88.780 12.110 11.220 60.21 42.68 224 299 0.875 bicubic -10.786 -10.808 -6.952 -6.188 +16 +10
71 mixnet_xl ecaresnetlight 69.080 69.340 30.920 30.660 88.310 89.220 11.690 10.780 11.90 30.16 224 0.875 bicubic -11.398 -11.122 -6.622 -6.030 -7 -5
72 efficientnet_b2 xception71 69.000 69.320 31.000 30.680 88.620 88.260 11.380 11.740 9.11 42.34 260 299 0.875 0.903 bicubic -11.402 -10.554 -6.456 -6.662 -2 +20
73 gluon_resnet101_v1d gluon_xception65 68.990 69.160 31.010 30.840 88.080 88.090 11.920 11.910 44.57 39.92 224 299 0.875 0.903 bicubic -11.434 -10.556 -6.940 -6.770 -4 +26
74 gluon_xception65 gluon_resnet152_v1c 68.980 69.140 31.020 30.860 88.320 87.870 11.680 12.130 39.92 60.21 299 224 0.875 bicubic -10.624 -10.770 -6.428 -6.970 +24 +16
75 gluon_resnext101_32x4d mixnet_xl 68.960 69.100 31.040 30.900 88.340 88.310 11.660 11.690 44.18 11.90 224 0.875 bicubic -11.374 -11.376 -6.586 -6.626 -3 -11
76 tf_efficientnet_b2_ap gluon_resnet101_v1d 68.930 69.010 31.070 30.990 88.340 88.100 11.660 11.900 9.11 44.57 260 224 0.890 0.875 bicubic -11.376 -11.404 -6.688 -6.914 -2 -7
77 gluon_resnet152_v1b xception65 68.810 68.980 31.190 31.020 87.710 88.480 12.290 11.520 60.19 39.92 224 299 0.875 0.903 bicubic -10.882 -10.572 -7.028 -6.174 +18 +26
78 dpn131 seresnet50 68.760 68.980 31.240 31.020 87.480 88.710 12.520 11.290 79.25 28.09 224 0.875 bicubic -11.068 -11.294 -7.224 -6.360 +12 +1
79 resnext50d_32x4d efficientnet_b2 68.750 68.970 31.250 31.030 88.310 88.630 11.690 11.370 25.05 9.11 224 260 0.875 bicubic -10.924 -11.422 -6.558 -6.446 +17 -9
80 tf_efficientnet_b2 regnety_160 68.750 68.970 31.250 31.030 87.950 88.270 12.050 11.730 9.11 83.59 260 224 0.890 0.875 bicubic -11.340 -11.326 -6.956 -6.692 +2 -3
81 gluon_resnet101_v1s gluon_resnext101_32x4d 68.720 68.960 31.280 31.040 87.900 88.360 12.100 11.640 44.67 44.18 224 0.875 bicubic -11.580 -11.374 -7.250 -6.566 -6 -9
82 dpn107 tf_efficientnet_b2_ap 68.710 68.920 31.290 31.080 88.130 88.350 11.870 11.650 86.92 9.11 224 260 0.875 0.890 bicubic -11.454 -11.380 -6.782 -6.678 -3 -6
83 gluon_seresnext50_32x4d cspdarknet53 68.670 68.890 31.330 31.110 88.320 88.600 11.680 11.400 27.56 27.64 224 256 0.875 0.887 bicubic bilinear -11.242 -11.168 -6.498 -6.484 +4 +1
84 hrnet_w64 regnety_120 68.630 68.850 31.370 31.150 88.070 88.330 11.930 11.670 128.06 51.82 224 0.875 bilinear bicubic -10.842 -11.516 -6.580 -6.796 +17 -13
85 resnext50_32x4d gluon_resnet152_v1b 68.610 68.820 31.390 31.180 87.570 87.710 12.430 12.290 25.03 60.19 224 0.875 bicubic -11.152 -10.866 -7.030 -7.026 +7 +15
86 dpn98 dpn131 68.580 68.770 31.420 31.230 87.660 87.470 12.340 12.530 61.57 79.25 224 0.875 bicubic -11.056 -11.052 -6.934 -7.240 +11 +8
87 ssl_resnet50 cspresnext50 68.420 68.760 31.580 31.240 88.580 87.950 11.420 12.050 25.56 20.57 224 0.875 bilinear -10.808 -11.280 -6.252 -6.994 +24 -2
88 ecaresnet50d_pruned tf_efficientnet_b2 68.390 68.750 31.610 31.250 88.370 87.990 11.630 12.010 19.94 9.11 224 260 0.875 0.890 bicubic -11.328 -11.336 -6.520 -6.918 +5 -5
89 skresnext50_32x4d resnext50d_32x4d 68.390 68.740 31.610 31.260 87.590 88.300 12.410 11.700 27.48 25.05 224 0.875 bicubic -11.760 -10.936 -7.054 -6.566 -8 +12
90 dla102x2 gluon_resnet101_v1s 68.340 68.710 31.660 31.290 87.870 87.910 12.130 12.090 41.75 44.67 224 0.875 bilinear bicubic -11.112 -11.592 -6.774 -7.250 +12 -15
91 efficientnet_b2_pruned regnety_080 68.300 68.700 31.700 31.300 88.100 87.970 11.900 12.030 8.31 39.18 260 224 0.890 0.875 bicubic -11.618 -11.176 -6.748 -6.860 -6 0
92 gluon_resnext50_32x4d dpn107 68.280 68.690 31.720 31.310 87.320 88.130 12.680 11.870 25.03 86.92 224 0.875 bicubic -11.076 -11.466 -7.104 -6.780 +11 -11
93 tf_efficientnet_lite3 gluon_seresnext50_32x4d 68.230 68.670 31.770 31.330 87.720 88.310 12.280 11.690 8.20 27.56 300 224 0.904 0.875 bilinear bicubic -11.582 -11.248 -7.194 -6.512 -2 -5
94 ese_vovnet39b hrnet_w64 68.190 68.640 31.810 31.360 88.260 88.050 11.740 11.950 24.57 128.06 224 0.875 bicubic bilinear -11.130 -10.834 -6.450 -6.602 +10 +13
95 tf_efficientnet_el resnext50_32x4d 68.180 68.640 31.820 31.360 88.350 87.570 11.650 12.430 10.59 25.03 300 224 0.904 0.875 bicubic -12.268 -11.128 -6.810 -7.028 -27 +1
96 dpn92 dpn98 68.010 68.590 31.990 31.410 87.590 87.680 12.410 12.320 37.67 61.57 224 0.875 bicubic -12.006 -11.052 -7.248 -6.918 -13 +6
97 gluon_resnet50_v1d regnetx_160 67.910 68.530 32.090 31.470 87.120 88.450 12.880 11.550 25.58 54.28 224 0.875 bicubic -11.164 -11.326 -7.356 -6.380 +20 -4
98 seresnext50_32x4d rexnet_130 67.870 68.450 32.130 31.550 87.620 88.040 12.380 11.960 27.56 7.56 224 0.875 bilinear bicubic -11.206 -11.050 -6.814 -6.642 +18 +8
99 resnext101_32x8d ecaresnet50d_pruned 67.850 68.420 32.150 31.580 87.480 88.370 12.520 11.630 88.79 19.94 224 0.875 bilinear bicubic -11.462 -11.296 -7.046 -6.510 +6 -1
100 hrnet_w44 regnety_064 67.770 68.420 32.230 31.580 87.530 88.080 12.470 11.920 67.06 30.58 224 0.875 bilinear bicubic -11.124 -11.302 -6.840 -6.688 +23 -3
101 hrnet_w48 ssl_resnet50 67.770 68.410 32.230 31.590 87.420 88.560 12.580 11.440 77.47 25.56 224 0.875 bilinear -11.540 -10.812 -7.098 -6.272 +5 +16
102 tf_efficientnet_b0_ns skresnext50_32x4d 67.720 68.350 32.280 31.650 88.080 87.570 11.920 12.430 5.29 27.48 224 0.875 bicubic -10.932 -11.806 -6.288 -7.072 +32 -20
103 xception dla102x2 67.670 68.330 32.330 31.670 87.570 87.890 12.430 12.110 22.86 41.28 299 224 0.897 0.875 bicubic bilinear -11.378 -11.118 -6.822 -6.750 +16 +5
104 dla169 efficientnet_b2_pruned 67.610 68.320 32.390 31.680 87.560 88.100 12.440 11.900 53.99 8.31 224 260 0.875 0.890 bilinear bicubic -11.100 -11.596 -6.778 -6.756 +26 -15
105 gluon_inception_v3 gluon_resnext50_32x4d 67.590 68.310 32.410 31.690 87.460 87.300 12.540 12.700 23.83 25.03 299 224 0.875 bicubic -11.214 -11.044 -6.920 -7.126 +22 +4
106 hrnet_w40 tf_efficientnet_lite3 67.590 68.230 32.410 31.770 87.130 87.740 12.870 12.260 57.56 8.20 224 300 0.875 0.904 bilinear -11.344 -11.590 -7.336 -7.174 +16 -11
107 gluon_resnet101_v1c ese_vovnet39b 67.560 68.210 32.440 31.790 87.160 88.240 12.840 11.760 44.57 24.57 224 0.875 bicubic -11.984 -11.110 -7.426 -6.472 -7 +3
108 seresnet152 tf_efficientnet_el 67.550 68.180 32.450 31.820 87.390 88.350 12.610 11.650 66.82 10.59 224 300 0.875 0.904 bilinear bicubic -11.108 -12.260 -6.984 -6.814 +25 -40
109 res2net50_26w_8s regnetx_120 67.530 68.150 32.470 31.850 87.270 87.660 12.730 12.340 48.40 46.11 224 0.875 bilinear bicubic -11.680 -11.446 -7.092 -7.078 +4 -6
110 tf_efficientnet_b1_ap dpn92 67.520 67.990 32.480 32.010 87.770 87.580 12.230 12.420 7.79 37.67 240 224 0.882 0.875 bicubic -11.758 -12.018 -6.538 -7.256 = -24
111 tf_efficientnet_cc_b1_8e gluon_resnet50_v1d 67.480 67.940 32.520 32.060 87.310 87.130 12.690 12.870 39.72 25.58 240 224 0.882 0.875 bicubic -11.818 -11.134 -7.054 -7.340 -3 +12
112 gluon_resnet101_v1b regnetx_080 67.450 67.880 32.550 32.120 87.230 86.990 12.770 13.010 44.55 39.57 224 0.875 bicubic -11.854 -11.314 -7.294 -7.570 -5 +10
113 res2net101_26w_4s resnext101_32x8d 67.450 67.860 32.550 32.140 87.010 87.490 12.990 12.510 45.21 88.79 224 0.875 bilinear -11.746 -11.448 -7.430 -7.028 +2 -2
114 resnet50 hrnet_w48 67.440 67.770 32.560 32.230 87.420 12.580 25.56 77.47 224 0.875 bicubic bilinear -11.592 -11.530 -6.964 -7.092 +6 0
115 resnetblur50 hrnet_w44 67.440 67.740 32.560 32.260 87.430 87.560 12.570 12.440 25.56 67.06 224 0.875 bicubic bilinear -11.850 -11.156 -7.202 -6.808 -6 +14
116 resnest26d tf_efficientnet_b0_ns 67.210 67.710 32.790 32.290 87.180 88.070 12.820 11.930 17.07 5.29 224 0.875 bilinear bicubic -11.272 -10.948 -7.110 -6.306 +22 +23
117 efficientnet_b1 regnetx_064 67.160 67.680 32.840 32.320 87.150 87.520 12.850 12.480 7.79 26.21 240 224 0.875 bicubic -11.538 -11.392 -7.002 -6.938 +14 +7
118 seresnet101 xception 67.150 67.650 32.850 32.350 87.050 87.570 12.950 12.430 49.33 22.86 224 299 0.875 0.897 bilinear bicubic -11.246 -11.402 -7.208 -6.822 +26 +7
119 gluon_resnet50_v1s dpn68b 67.100 67.630 32.900 32.370 86.860 87.660 13.140 12.340 25.68 12.61 224 0.875 bicubic -11.612 -11.586 -7.382 -6.754 +10 0
120 dla60x dla169 67.080 67.610 32.920 32.390 87.170 87.590 12.830 12.410 17.65 53.39 224 0.875 bilinear -11.162 -11.078 -6.852 -6.746 +26 +18
121 dla60_res2net gluon_inception_v3 67.030 67.590 32.970 32.410 87.140 87.470 12.860 12.530 21.15 23.83 224 299 0.875 bilinear bicubic -11.442 -11.216 -7.064 -6.900 +18 +12
122 resnet152 regnety_040 67.020 67.580 32.980 32.420 87.570 87.510 12.430 12.490 60.19 20.65 224 0.875 bilinear bicubic -11.292 -11.640 -6.476 -7.146 +23 -5
123 dla102x gluon_resnet101_v1c 67.000 67.580 33.000 32.420 86.770 87.180 13.230 12.820 26.77 44.57 224 0.875 bilinear bicubic -11.508 -11.954 -7.464 -7.398 +13 -17
124 mixnet_l res2net50_26w_8s 66.970 67.570 33.030 32.430 86.940 87.280 13.060 12.720 7.33 48.40 224 0.875 bicubic bilinear -12.006 -11.628 -7.244 -7.088 -3 -4
125 res2net50_26w_6s hrnet_w40 66.910 67.560 33.090 32.440 86.900 87.140 13.100 12.860 37.05 57.56 224 0.875 bilinear -11.664 -11.360 -7.226 -7.330 +10 +3
126 efficientnet_es tf_efficientnet_b1_ap 66.890 67.520 33.110 32.480 86.730 87.760 13.270 12.240 5.44 7.79 224 240 0.875 0.882 bicubic -11.164 -11.760 -7.200 -6.546 +26 -10
127 tf_efficientnet_b1 gluon_resnet101_v1b 66.890 67.460 33.110 32.540 87.040 87.240 12.960 12.760 7.79 44.55 240 224 0.882 0.875 bicubic -11.942 -11.846 -7.156 -7.284 -1 -14
128 tf_efficientnet_em tf_efficientnet_cc_b1_8e 66.870 67.450 33.130 32.550 86.980 87.310 13.020 12.690 6.90 39.72 240 0.882 bicubic -11.828 -11.858 -7.340 -7.060 +4 -16
129 hrnet_w32 res2net101_26w_4s 66.790 67.440 33.210 32.560 87.290 87.010 12.710 12.990 41.23 45.21 224 0.875 bilinear -11.658 -11.758 -6.898 -7.422 +13 -8
130 tf_mixnet_l resnet50 66.780 67.440 33.220 32.560 86.460 87.420 13.540 12.580 7.33 25.56 224 0.875 bicubic -11.990 -11.598 -7.544 -6.970 -2 -4
131 hrnet_w30 resnetblur50 66.760 67.430 33.240 32.570 86.790 87.440 13.210 12.560 37.71 25.56 224 0.875 bilinear bicubic -11.436 -11.856 -7.430 -7.198 +18 -16
132 selecsls60b regnety_032 66.720 67.400 33.280 32.600 86.540 87.270 13.460 12.730 32.77 19.44 224 0.875 bicubic -11.698 -11.486 -7.626 -7.142 +11 -2
133 wide_resnet101_2 regnetx_032 66.680 67.290 33.320 32.710 87.040 87.000 12.960 13.000 126.89 15.30 224 0.875 bilinear bicubic -12.166 -10.882 -7.244 -7.088 -8 +22
134 wide_resnet50_2 xception41 66.650 67.250 33.350 32.750 86.810 87.200 13.190 12.800 68.88 26.97 224 299 0.875 0.903 bilinear bicubic -11.818 -11.266 -7.276 -7.078 +6 +7
135 dla60_res2next resnest26d 66.640 67.200 33.360 32.800 87.020 87.170 12.980 12.830 17.33 17.07 224 0.875 bilinear -11.808 -11.278 -7.124 -7.128 +6 +9
136 adv_inception_v3 efficientnet_b1 66.600 67.170 33.400 32.830 86.560 87.150 13.440 12.850 23.83 7.79 299 240 0.875 bicubic -10.980 -11.528 -7.164 -6.994 +30 +1
137 dla102 dla60x 66.550 67.100 33.450 32.900 86.910 87.190 13.090 12.810 33.73 17.35 224 0.875 bilinear -11.476 -11.146 -7.040 -6.828 +16 +14
138 gluon_resnet50_v1c gluon_resnet50_v1s 66.540 67.060 33.460 32.940 86.160 86.860 13.840 13.140 25.58 25.68 224 0.875 bicubic -11.470 -11.652 -7.828 -7.378 +16 -3
139 tf_inception_v3 resnet152 66.420 67.050 33.580 32.950 86.680 87.550 13.320 12.450 23.83 60.19 299 224 0.875 bicubic bilinear -11.436 -11.262 -6.964 -6.488 +21 +11
140 efficientnet_b0 dla60_res2net 66.250 67.020 33.750 32.980 85.950 87.160 14.050 12.840 5.29 20.85 224 0.875 bicubic bilinear -11.442 -11.444 -7.582 -7.046 +22 +6
141 seresnet50 dla102x 66.240 67.010 33.760 32.990 86.330 86.770 13.670 13.230 28.09 26.31 224 0.875 bilinear -11.396 -11.500 -7.422 -7.458 +22 +1
142 selecsls60 mixnet_l 66.220 66.940 33.780 33.060 86.330 86.910 13.670 13.090 30.67 7.33 224 0.875 bicubic -11.762 -12.036 -7.502 -7.272 +15 -15
143 tf_efficientnet_cc_b0_8e res2net50_26w_6s 66.210 66.910 33.790 33.090 86.220 86.860 13.780 13.140 24.01 37.05 224 0.875 bicubic bilinear -11.698 -11.660 -7.436 -7.264 +16 -3
144 tv_resnext50_32x4d efficientnet_es 66.180 66.880 33.820 33.120 86.040 86.730 13.960 13.270 25.03 5.44 224 0.875 bilinear bicubic -11.438 -11.186 -7.658 -7.196 +20 +13
145 res2net50_26w_4s tf_efficientnet_b1 66.170 66.880 33.830 33.120 86.600 87.010 13.400 12.990 25.70 7.79 224 240 0.875 0.882 bilinear bicubic -11.776 -11.946 -7.252 -7.188 +13 -13
146 inception_v3 tf_efficientnet_em 66.120 66.880 33.880 33.120 86.340 86.970 13.660 13.030 23.83 6.90 299 240 0.875 0.882 bicubic -11.316 -11.828 -7.136 -7.344 +25 -10
147 efficientnet_b1_pruned regnetx_040 66.080 66.840 33.920 33.160 86.580 86.730 13.420 13.270 6.33 22.12 240 224 0.882 0.875 bicubic -12.162 -11.642 -7.252 -7.514 = -4
148 gluon_resnet50_v1b hrnet_w30 66.040 66.780 33.960 33.220 86.270 86.800 13.730 13.200 25.56 37.71 224 0.875 bicubic bilinear -11.538 -11.426 -7.448 -7.422 +19 +6
149 res2net50_14w_8s tf_mixnet_l 66.020 66.780 33.980 33.220 86.240 86.470 13.760 13.530 25.06 7.33 224 0.875 bilinear bicubic -12.132 -11.994 -7.602 -7.528 +2 -15
150 densenet161 selecsls60b 65.850 66.760 34.150 33.240 86.460 86.530 13.540 13.470 28.68 32.77 224 0.875 bicubic -11.498 -11.652 -7.188 -7.644 +23 -1
151 res2next50 hrnet_w32 65.850 66.750 34.150 33.250 85.830 87.300 14.170 12.700 24.67 41.23 224 0.875 bilinear -12.392 -11.700 -8.062 -6.886 -3 -4
152 seresnext26tn_32x4d wide_resnet101_2 65.850 66.730 34.150 33.270 85.680 87.030 14.320 12.970 16.81 126.89 224 0.875 bicubic bilinear -12.140 -12.126 -8.068 -7.252 +3 -21
153 skresnet34 wide_resnet50_2 65.770 66.650 34.230 33.350 85.960 86.800 14.040 13.200 22.28 68.88 224 0.875 bicubic bilinear -11.140 -11.828 -7.356 -7.294 +32 -9
154 resnet101 adv_inception_v3 65.680 66.650 34.320 33.350 85.980 86.540 14.020 13.460 44.55 23.83 224 299 0.875 bilinear bicubic -11.694 -10.932 -7.566 -7.196 +18
155 dpn68b dla60_res2next 65.600 66.640 34.400 33.360 85.940 87.030 14.060 12.970 12.61 17.03 224 0.875 bicubic bilinear -11.914 -11.800 -7.882 -7.122 +13 -7
156 seresnext26t_32x4d gluon_resnet50_v1c 65.600 66.560 34.400 33.440 86.090 86.180 13.910 13.820 16.82 25.58 224 0.875 bicubic -12.388 -11.452 -7.616 -7.808 = +3
157 selecsls42b dla102 65.590 66.540 34.410 33.460 85.830 86.910 14.170 13.090 32.46 33.27 224 0.875 bicubic bilinear -11.586 -11.492 -7.562 -7.036 +22 +1
158 tf_efficientnet_b0_ap tf_inception_v3 65.490 66.410 34.510 33.590 85.550 86.660 14.450 13.340 5.29 23.83 224 299 0.875 bicubic -11.594 -11.448 -7.704 -6.978 +23 +9
159 seresnext26d_32x4d efficientnet_b0 65.420 66.290 34.580 33.710 85.970 85.960 14.030 14.040 16.81 5.29 224 0.875 bicubic -12.184 -11.408 -7.642 -7.572 +6 +9
160 tf_efficientnet_lite2 selecsls60 65.390 66.210 34.610 33.790 86.030 86.340 13.970 13.660 6.09 30.67 260 224 0.890 0.875 bicubic -12.070 -11.772 -7.716 -7.488 +10 +2
161 res2net50_48w_2s tv_resnext50_32x4d 65.320 66.180 34.680 33.820 85.960 86.040 14.040 13.960 25.29 25.03 224 0.875 bilinear -12.194 -11.440 -7.588 -7.656 +8
162 densenetblur121d tf_efficientnet_cc_b0_8e 65.300 66.170 34.700 33.830 85.710 86.240 14.290 13.760 8.00 24.01 224 0.875 bicubic -11.276 -11.738 -7.480 -7.414 +28 +2
163 densenet201 inception_v3 65.280 66.160 34.720 33.840 85.670 86.320 14.330 13.680 20.01 23.83 224 299 0.875 bicubic -12.010 -11.280 -7.808 -7.156 +13 +12
164 tf_efficientnet_es res2net50_26w_4s 65.240 66.140 34.760 33.860 85.540 86.600 14.460 13.400 5.44 25.70 224 0.875 bicubic bilinear -12.024 -11.824 -8.060 -7.254 +13 -1
165 dla60 efficientnet_b1_pruned 65.220 66.090 34.780 33.910 85.750 86.570 14.250 13.430 22.33 6.33 224 240 0.875 0.882 bilinear bicubic -11.804 -12.146 -7.558 -7.264 +17 -12
166 tf_efficientnet_cc_b0_4e gluon_resnet50_v1b 65.130 66.070 34.870 33.930 85.130 86.260 14.870 13.740 13.31 25.56 224 0.875 bicubic -12.174 -11.510 -8.202 -7.456 +8 +6
167 mobilenetv2_120d rexnet_100 65.040 66.070 34.960 33.930 85.990 86.490 14.010 13.510 5.83 4.80 224 0.875 bicubic -12.254 -11.788 -7.512 -7.380 +8 -1
168 seresnext26_32x4d regnety_016 65.040 66.060 34.960 33.940 85.650 86.380 14.350 13.620 16.79 11.20 224 0.875 bicubic -12.060 -11.802 -7.660 -7.340 +12 -3
169 hrnet_w18 res2net50_14w_8s 64.910 66.020 35.090 33.980 85.750 86.250 14.250 13.750 21.30 25.06 224 0.875 bilinear -11.846 -12.130 -7.692 -7.598 +18 -13
170 densenet169 seresnext26tn_32x4d 64.780 65.880 35.220 34.120 85.250 85.680 14.750 14.320 14.15 16.81 224 0.875 bicubic -11.132 -12.106 -7.774 -8.066 +26 -9
171 mixnet_m res2next50 64.690 65.850 35.310 34.150 85.470 85.840 14.530 14.160 5.01 24.67 224 0.875 bicubic bilinear -12.566 -12.396 -7.948 -8.052 +7 -19
172 resnet26d densenet161 64.630 65.840 35.370 34.160 85.120 86.450 14.880 13.550 16.01 28.68 224 0.875 bicubic -12.050 -11.518 -8.046 -7.188 +16 +5
173 tf_efficientnet_lite1 skresnet34 64.370 65.750 35.630 34.250 85.490 85.960 14.510 14.040 5.42 22.28 240 224 0.882 0.875 bicubic -12.268 -11.162 -7.742 -7.362 +16 +15
174 tf_efficientnet_b0 resnet101 64.290 65.690 35.710 34.310 85.250 85.980 14.750 14.020 5.29 44.55 224 0.875 bicubic bilinear -12.550 -11.684 -7.976 -7.560 +12 +2
175 tf_mixnet_m selecsls42b 64.270 65.610 35.730 34.390 85.090 85.810 14.910 14.190 5.01 32.46 224 0.875 bicubic -12.680 -11.564 -8.066 -7.580 +8
176 dpn68 seresnext26t_32x4d 64.220 65.600 35.780 34.400 85.180 86.080 14.820 13.920 12.61 16.82 224 0.875 bicubic -12.086 -12.398 -7.790 -7.628 +17 -16
177 mobilenetv2_140 tf_efficientnet_b0_ap 64.050 65.490 35.950 34.510 85.020 85.580 14.980 14.420 6.11 5.29 224 0.875 bicubic -12.474 -11.596 -7.970 -7.676 +14 +7
178 densenet121 seresnext26d_32x4d 63.740 65.410 36.260 34.590 84.630 85.970 15.370 14.030 7.98 16.81 224 0.875 bicubic -11.834 -12.192 -8.026 -7.638 +22 -8
179 resnest14d tf_efficientnet_lite2 63.600 65.380 36.400 34.620 84.220 85.990 15.780 14.010 10.61 6.09 224 260 0.875 0.890 bilinear bicubic -11.904 -12.088 -8.294 -7.764 +23 -5
180 tf_mixnet_s res2net50_48w_2s 63.590 65.350 36.410 34.650 84.270 85.960 15.730 14.040 4.13 25.29 224 0.875 bicubic bilinear -12.058 -12.172 -8.366 -7.594 +18 -7
181 resnet26 densenet201 63.450 65.290 36.550 34.710 84.270 85.690 15.730 14.310 16.00 20.01 224 0.875 bicubic -11.842 -11.996 -8.300 -7.788 +23 -2
182 mixnet_s densenetblur121d 63.380 65.280 36.620 34.720 84.710 85.710 15.290 14.290 4.13 8.00 224 0.875 bicubic -12.608 -11.308 -8.084 -7.482 +13 +12
183 mobilenetv3_large_100 tf_efficientnet_es 63.360 65.220 36.640 34.780 84.080 85.550 15.920 14.450 5.48 5.44 224 0.875 bicubic -12.408 -12.038 -8.460 -8.044 +14 -1
184 tv_resnet50 dla60 63.330 65.200 36.670 34.800 84.650 85.760 15.350 14.240 25.56 22.04 224 0.875 bilinear -12.800 -11.832 -8.212 -7.558 +10 +1
185 mobilenetv3_rw ese_vovnet19b_dw 63.230 65.190 36.770 34.810 84.520 85.470 15.480 14.530 5.48 6.54 224 0.875 bicubic -12.398 -11.608 -8.190 -7.798 +14 +5
186 semnasnet_100 tf_efficientnet_cc_b0_4e 63.120 65.150 36.880 34.850 84.530 85.160 15.470 14.840 3.89 13.31 224 0.875 bicubic -12.336 -12.156 -8.062 -8.174 +17 -8
187 tv_densenet121 mobilenetv2_120d 62.940 65.030 37.060 34.970 84.260 85.960 15.740 14.040 7.98 5.83 224 0.875 bicubic -11.812 -12.254 -7.892 -7.532 +26 -7
188 seresnet34 hrnet_w18 62.890 64.920 37.110 35.080 84.220 85.740 15.780 14.260 21.96 21.30 224 0.875 bilinear -11.918 -11.838 -7.906 -7.704 +24 +3
189 hrnet_w18_small_v2 densenet169 62.830 64.760 37.170 35.240 83.970 85.240 16.030 14.760 15.60 14.15 224 0.875 bilinear bicubic -12.296 -11.146 -8.446 -7.786 +17 +11
190 mobilenetv2_110d mixnet_m 62.820 64.700 37.180 35.300 84.480 85.450 15.520 14.550 4.52 5.01 224 0.875 bicubic -12.232 -12.560 -7.700 -7.974 +19 -9
191 resnet34 resnet26d 62.820 64.680 37.180 35.320 84.120 85.120 15.880 14.880 21.80 16.01 224 0.875 bilinear bicubic -12.292 -12.016 -8.168 -8.030 +17 +1
192 swsl_resnet18 regnetx_016 62.730 64.380 37.270 35.620 84.300 85.470 15.700 14.530 11.69 9.19 224 0.875 bilinear bicubic -10.556 -12.570 -7.432 -7.950 +30 -6
193 tf_efficientnet_lite0 tf_efficientnet_lite1 62.580 64.380 37.420 35.620 84.250 85.470 15.750 14.530 4.65 5.42 224 240 0.875 0.882 bicubic -12.262 -7.920 -7.756 +18 0
194 gluon_resnet34_v1b tf_efficientnet_b0 62.560 64.310 37.440 35.690 84.000 85.280 16.000 14.720 21.80 5.29 224 0.875 bicubic -12.020 -12.538 -7.988 -7.948 +22 -5
195 dla34 tf_mixnet_m 62.510 64.270 37.490 35.730 83.920 85.090 16.080 14.910 15.78 5.01 224 0.875 bilinear bicubic -12.126 -12.672 -8.144 -8.062 +20 -8
196 tf_mobilenetv3_large_100 dpn68 62.470 64.230 37.530 35.770 83.960 85.180 16.040 14.820 5.48 12.61 224 0.875 bilinear bicubic -13.046 -12.088 -8.640 -7.798 +5 0
197 fbnetc_100 regnety_008 62.430 64.160 37.570 35.840 83.390 85.270 16.610 14.730 5.57 6.26 224 0.875 bilinear bicubic -12.690 -12.156 -8.996 -7.796 +10 0
198 mnasnet_100 mobilenetv2_140 61.910 64.060 38.090 35.940 83.710 85.040 16.290 14.960 4.38 6.11 224 0.875 bicubic -12.746 -12.456 -8.416 -7.956 +16 -3
199 ssl_resnet18 densenet121 61.490 63.750 38.510 36.250 83.330 84.590 16.670 15.410 11.69 7.98 224 0.875 bilinear bicubic -11.110 -11.828 -8.086 -8.062 +26 +5
200 spnasnet_100 resnest14d 61.210 63.590 38.790 36.410 82.770 84.250 17.230 15.750 4.42 10.61 224 0.875 bilinear -12.870 -11.916 -9.062 -8.268 +17 +6
201 tv_resnet34 tf_mixnet_s 61.200 63.560 38.800 36.440 82.720 84.270 17.280 15.730 21.80 4.13 224 0.875 bilinear bicubic -12.114 -12.090 -8.700 -8.358 +20 +1
202 skresnet18 resnet26 60.850 63.470 39.150 36.530 82.880 84.260 17.120 15.740 11.96 16.00 224 0.875 bicubic -12.194 -11.822 -8.298 -8.310 +21 +7
203 tf_mobilenetv3_large_075 mixnet_s 60.380 63.390 39.620 36.610 81.960 84.740 18.040 15.260 3.99 4.13 224 0.875 bilinear bicubic -13.062 -12.602 -9.392 -8.056 +17 -4
204 mobilenetv2_100 mobilenetv3_large_100 60.160 63.360 39.840 36.640 82.240 84.090 17.760 15.910 3.50 5.48 224 0.875 bicubic -12.818 -12.406 -8.776 -8.452 +20 -3
205 seresnet18 tv_resnet50 59.810 63.330 40.190 36.670 81.680 84.640 18.320 15.360 11.78 25.56 224 0.875 bicubic bilinear -11.948 -12.808 -8.654 -8.224 +24 -7
206 tf_mobilenetv3_large_minimal_100 efficientnet_lite0 59.070 63.240 40.930 36.760 81.140 84.440 18.860 15.560 3.92 4.65 224 0.875 bilinear bicubic -13.174 -12.244 -9.496 -8.070 +22 +1
207 hrnet_w18_small mobilenetv3_rw 58.970 63.220 41.030 36.780 81.340 84.510 18.660 15.490 13.19 5.48 224 0.875 bilinear bicubic -13.372 -12.414 -9.332 -8.198 +20 -4
208 gluon_resnet18_v1b semnasnet_100 58.320 63.150 41.680 36.850 80.960 84.520 19.040 15.480 11.69 3.89 224 0.875 bicubic -12.510 -12.298 -8.796 -8.084 +22 0
209 resnet18 regnety_006 57.180 63.110 42.820 36.890 80.190 84.250 19.810 15.750 11.69 6.06 224 0.875 bilinear bicubic -12.578 -12.136 -8.888 -8.282 +23 +1
210 dla60x_c tv_densenet121 56.020 62.940 43.980 37.060 78.960 84.250 21.040 15.750 1.34 7.98 224 0.875 bilinear bicubic -11.888 -11.798 -9.474 -7.900 +25 +7
211 tf_mobilenetv3_small_100 resnet34 54.510 62.870 45.490 37.130 77.080 84.140 22.920 15.860 2.54 21.80 224 0.875 bilinear -13.408 -12.240 -10.582 -8.144 +23 +2
212 dla46x_c mobilenetv2_110d 53.080 62.830 46.920 37.170 76.840 84.500 23.160 15.500 1.08 4.52 224 0.875 bilinear bicubic -12.900 -12.206 -10.140 -7.686 +24 +3
213 dla46_c hrnet_w18_small_v2 52.200 62.800 47.800 37.200 75.680 83.980 24.320 16.020 1.31 15.60 224 0.875 bilinear -12.678 -12.314 -10.606 -8.436 +25 -1
214 tf_mobilenetv3_small_075 swsl_resnet18 52.150 62.760 47.850 37.240 75.460 84.300 24.540 15.700 2.04 11.69 224 0.875 bilinear -13.568 -10.516 -10.676 -7.434 +23 +12
215 tf_mobilenetv3_small_minimal_100 gluon_resnet34_v1b 49.530 62.570 50.470 37.430 73.050 83.990 26.950 16.010 2.04 21.80 224 0.875 bilinear bicubic -13.368 -12.018 -11.180 -8.000 +24 +5
216 tf_efficientnet_lite0 62.550 37.450 84.220 15.780 4.65 224 0.875 bicubic -12.280 -7.956 0
217 regnetx_008 62.490 37.510 84.020 15.980 7.26 224 0.875 bicubic -12.548 -8.316 -3
218 dla34 62.480 37.520 83.910 16.090 15.74 224 0.875 bilinear -12.150 -8.168 +1
219 tf_mobilenetv3_large_100 62.460 37.540 83.970 16.030 5.48 224 0.875 bilinear -13.058 -8.636 -14
220 fbnetc_100 62.440 37.560 83.380 16.620 5.57 224 0.875 bilinear -12.684 -9.006 -9
221 mnasnet_100 61.900 38.100 83.710 16.290 4.38 224 0.875 bicubic -12.758 -8.404 -3
222 regnety_004 61.870 38.130 83.430 16.570 4.34 224 0.875 bicubic -12.164 -8.322 0
223 ssl_resnet18 61.480 38.520 83.300 16.700 11.69 224 0.875 bilinear -11.130 -8.116 +6
224 regnetx_006 61.350 38.650 83.450 16.550 6.20 224 0.875 bicubic -12.502 -8.222 -1
225 spnasnet_100 61.220 38.780 82.790 17.210 4.42 224 0.875 bilinear -12.864 -9.028 -4
226 tv_resnet34 61.190 38.810 82.710 17.290 21.80 224 0.875 bilinear -12.122 -8.716 -1
227 skresnet18 60.860 39.140 82.880 17.120 11.96 224 0.875 bicubic -12.178 -8.288 0
228 tf_mobilenetv3_large_075 60.400 39.600 81.950 18.050 3.99 224 0.875 bilinear -13.038 -9.400 -4
229 mobilenetv2_100 60.190 39.810 82.240 17.760 3.50 224 0.875 bicubic -12.780 -8.776 -1
230 regnetx_004 59.410 40.590 81.690 18.310 5.16 224 0.875 bicubic -12.986 -9.140 0
231 tf_mobilenetv3_large_minimal_100 59.070 40.930 81.150 18.850 3.92 224 0.875 bilinear -13.178 -9.480 +1
232 hrnet_w18_small 58.950 41.050 81.340 18.660 13.19 224 0.875 bilinear -13.392 -9.338 -1
233 gluon_resnet18_v1b 58.340 41.660 80.970 19.030 11.69 224 0.875 bicubic -12.496 -8.792 0
234 resnet18 57.170 42.830 80.200 19.800 11.69 224 0.875 bilinear -12.578 -8.878 +1
235 regnety_002 57.000 43.000 79.840 20.160 3.16 224 0.875 bicubic -13.252 -9.700 -1
236 regnetx_002 56.050 43.950 79.210 20.790 2.68 224 0.875 bicubic -12.712 -9.346 0
237 dla60x_c 56.000 44.000 78.930 21.070 1.32 224 0.875 bilinear -11.892 -9.496 +1
238 tf_mobilenetv3_small_100 54.530 45.470 77.060 22.940 2.54 224 0.875 bilinear -13.392 -10.604 -1
239 dla46x_c 53.050 46.950 76.870 23.130 1.07 224 0.875 bilinear -12.920 -10.110 0
240 tf_mobilenetv3_small_075 52.160 47.840 75.470 24.530 2.04 224 0.875 bilinear -13.556 -10.660 0
241 dla46_c 52.130 47.870 75.690 24.310 1.30 224 0.875 bilinear -12.736 -10.602 0
242 tf_mobilenetv3_small_minimal_100 49.500 50.500 73.050 26.950 2.04 224 0.875 bilinear -13.406 -11.180 0

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results/results-sketch.csv
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@ -1,239 +1,242 @@
model,rank_diff,top1,top1_diff,top1_err,top5,top5_diff,top5_err,param_count,img_size,cropt_pct,interpolation
ig_resnext101_32x48d,+5,58.814,-26.628,41.186,81.086,-16.486,18.914,828.41,224,0.875,bilinear
ig_resnext101_32x32d,+9,58.380,-26.712,41.620,80.379,-17.057,19.621,468.53,224,0.875,bilinear
ig_resnext101_32x16d,+14,57.700,-26.476,42.300,79.913,-17.283,20.087,194.03,224,0.875,bilinear
swsl_resnext101_32x16d,+18,57.466,-25.872,42.534,80.381,-16.471,19.619,194.03,224,0.875,bilinear
swsl_resnext101_32x8d,+9,56.435,-27.859,43.565,78.934,-18.240,21.066,88.79,224,0.875,bilinear
ig_resnext101_32x8d,+23,54.918,-27.770,45.082,77.545,-19.087,22.455,88.79,224,0.875,bilinear
swsl_resnext101_32x4d,+17,53.591,-29.643,46.409,76.339,-20.417,23.661,44.18,224,0.875,bilinear
tf_efficientnet_l2_ns_475,-6,51.487,-36.747,48.513,73.930,-24.616,26.070,480.31,475,0.936,bicubic
swsl_resnext50_32x4d,+24,50.449,-31.731,49.551,73.358,-22.870,26.642,25.03,224,0.875,bilinear
swsl_resnet50,+38,49.551,-31.629,50.449,72.332,-23.654,27.668,25.56,224,0.875,bilinear
tf_efficientnet_b7_ns,-8,47.800,-39.038,52.200,69.638,-28.456,30.362,66.35,600,0.949,bicubic
tf_efficientnet_b6_ns,-8,47.751,-38.711,52.249,69.962,-27.922,30.038,43.04,528,0.942,bicubic
tf_efficientnet_l2_ns,-12,47.570,-40.782,52.430,70.017,-28.631,29.983,480.31,800,0.960,bicubic
tf_efficientnet_b8_ap,-6,45.778,-39.590,54.222,67.905,-29.389,32.095,87.41,672,0.954,bicubic
tf_efficientnet_b5_ns,-10,45.607,-40.473,54.393,67.852,-29.902,32.148,30.39,456,0.934,bicubic
tf_efficientnet_b4_ns,-7,43.455,-41.703,56.545,65.513,-31.955,34.487,19.34,380,0.922,bicubic
tf_efficientnet_b8,-10,42.502,-42.868,57.498,64.874,-32.518,35.126,87.41,672,0.954,bicubic
tf_efficientnet_b7,-6,41.437,-43.495,58.563,63.027,-34.181,36.973,66.35,600,0.949,bicubic
tf_efficientnet_b7_ap,-9,41.433,-43.685,58.567,62.876,-34.376,37.124,66.35,600,0.949,bicubic
tf_efficientnet_b5_ap,-5,41.420,-42.834,58.580,62.082,-34.894,37.918,30.39,456,0.934,bicubic
tf_efficientnet_b6_ap,-8,41.091,-43.695,58.909,62.359,-34.779,37.641,43.04,528,0.942,bicubic
tf_efficientnet_b4_ap,+1,40.476,-42.772,59.524,61.713,-34.675,38.287,19.34,380,0.922,bicubic
tf_efficientnet_b3_ns,-4,39.582,-44.472,60.418,61.463,-35.449,38.537,12.23,300,0.904,bicubic
tf_efficientnet_b5,-3,38.328,-45.488,61.672,59.928,-36.822,40.072,30.39,456,0.934,bicubic
tf_efficientnet_b3_ap,+13,37.061,-44.767,62.939,57.236,-38.388,42.764,12.23,300,0.904,bicubic
resnest269e,-10,36.670,-47.516,63.330,56.810,-40.112,43.190,110.93,416,0.875,bilinear
tf_efficientnet_b2_ns,+4,36.177,-46.203,63.823,57.555,-38.697,42.445,9.11,260,0.890,bicubic
ecaresnet101d,+6,36.006,-46.160,63.994,56.154,-39.898,43.846,44.57,224,0.875,bicubic
swsl_resnet18,+192,35.860,-37.426,64.140,58.437,-33.295,41.563,11.69,224,0.875,bilinear
resnest200e,-10,35.847,-47.987,64.153,55.890,-40.948,44.110,70.20,320,0.875,bilinear
resnest101e,-4,35.365,-47.525,64.635,55.786,-40.538,44.214,48.28,256,0.875,bilinear
ssl_resnext101_32x16d,+5,34.609,-47.227,65.391,55.914,-40.180,44.086,194.03,224,0.875,bilinear
resnest50d_4s2x40d,+16,34.361,-46.753,65.639,54.711,-40.857,45.289,30.42,224,0.875,bicubic
tf_efficientnet_b1_ns,+11,34.153,-47.233,65.847,55.489,-40.249,44.511,7.79,240,0.882,bicubic
tf_efficientnet_b4,-9,34.062,-48.954,65.938,54.216,-42.082,45.784,19.34,380,0.922,bicubic
ssl_resnext101_32x8d,+5,34.021,-47.605,65.979,55.593,-40.445,44.407,88.79,224,0.875,bilinear
tf_efficientnet_b6,-19,34.005,-50.107,65.995,54.540,-42.344,45.460,43.04,528,0.942,bicubic
efficientnet_b3_pruned,+18,33.996,-46.860,66.004,54.110,-41.130,45.890,9.86,300,0.904,bicubic
tresnet_xl,-4,33.259,-48.811,66.741,52.296,-43.632,47.704,78.44,224,0.875,bilinear
resnest50d_1s4x24d,+11,33.139,-47.851,66.861,52.831,-42.491,47.169,25.68,224,0.875,bicubic
resnest50d,+11,32.968,-47.990,67.032,52.701,-42.681,47.299,27.48,224,0.875,bilinear
tf_efficientnet_b3,-2,32.864,-48.776,67.136,52.962,-42.760,47.038,12.23,300,0.904,bicubic
inception_resnet_v2,+22,32.736,-47.724,67.264,50.640,-44.670,49.360,55.84,299,0.897,bicubic
gluon_resnet152_v1d,+20,32.730,-47.740,67.270,51.084,-44.122,48.916,60.21,224,0.875,bicubic
tf_efficientnet_b2_ap,+28,32.679,-47.627,67.321,52.233,-42.795,47.767,9.11,260,0.890,bicubic
nasnetalarge,-16,32.583,-49.975,67.417,49.787,-46.249,50.213,88.75,331,0.875,bicubic
tresnet_l,-3,32.567,-48.921,67.433,51.141,-44.487,48.859,55.99,224,0.875,bilinear
pnasnet5large,-20,32.532,-50.208,67.468,50.188,-45.852,49.812,86.06,331,0.875,bicubic
ens_adv_inception_resnet_v2,+34,32.370,-47.606,67.629,50.427,-44.519,49.573,55.84,299,0.897,bicubic
gluon_resnet152_v1s,=,32.331,-48.681,67.669,50.539,-44.877,49.461,60.32,224,0.875,bicubic
gluon_seresnext101_64x4d,+4,32.194,-48.696,67.806,50.327,-44.977,49.673,88.23,224,0.875,bicubic
gluon_seresnext101_32x4d,+2,32.115,-48.787,67.885,51.241,-44.053,48.759,48.96,224,0.875,bicubic
efficientnet_b3a,-17,31.728,-50.146,68.272,51.322,-44.518,48.678,12.23,320,1.000,bicubic
efficientnet_b3,-11,31.565,-49.933,68.435,51.272,-44.446,48.728,12.23,300,0.904,bicubic
resnet50,+64,31.545,-47.487,68.455,50.172,-44.212,49.828,25.56,224,0.875,bicubic
ssl_resnext101_32x4d,-3,31.433,-49.495,68.567,52.115,-43.613,47.885,44.18,224,0.875,bilinear
inception_v4,+22,31.382,-48.774,68.618,49.237,-45.737,50.763,42.68,299,0.875,bicubic
ecaresnetlight,+8,31.133,-49.321,68.868,50.252,-45.004,49.748,30.16,224,0.875,bicubic
gluon_resnet101_v1s,+15,31.113,-49.187,68.887,49.791,-45.359,50.209,44.67,224,0.875,bicubic
tf_efficientnet_cc_b0_8e,+98,31.081,-46.827,68.919,50.773,-42.883,49.227,24.01,224,0.875,bicubic
ecaresnet50d,=,31.064,-49.540,68.936,50.846,-44.476,49.154,25.58,224,0.875,bicubic
gluon_resnet152_v1c,+23,31.007,-48.909,68.993,48.936,-45.906,51.064,60.21,224,0.875,bicubic
tresnet_m,-4,30.993,-49.803,69.007,48.690,-46.166,51.310,31.39,224,0.875,bilinear
gluon_resnext101_64x4d,-2,30.981,-49.621,69.019,48.553,-46.441,51.447,83.46,224,0.875,bicubic
tf_efficientnet_cc_b1_8e,+42,30.901,-48.397,69.099,50.074,-44.290,49.926,39.72,240,0.882,bicubic
ecaresnet101d_pruned,-8,30.895,-49.913,69.105,50.001,-45.627,49.999,24.88,224,0.875,bicubic
gluon_resnext101_32x4d,+4,30.881,-49.453,69.119,48.537,-46.389,51.463,44.18,224,0.875,bicubic
tf_efficientnet_lite4,-26,30.840,-50.688,69.160,50.398,-45.270,49.602,13.01,380,0.920,bilinear
dpn107,+9,30.680,-49.484,69.320,48.806,-46.106,51.194,86.92,224,0.875,bicubic
ese_vovnet39b,+33,30.677,-48.643,69.323,49.893,-44.817,50.107,24.57,224,0.875,bicubic
tresnet_xl_448,-46,30.620,-52.428,69.380,49.072,-47.102,50.928,78.44,448,0.875,bilinear
gluon_resnet152_v1b,+22,30.618,-49.074,69.382,48.529,-46.209,51.471,60.19,224,0.875,bicubic
ssl_resnext50_32x4d,-1,30.594,-49.734,69.406,50.653,-44.751,49.347,25.03,224,0.875,bilinear
gluon_resnet101_v1d,-6,30.509,-49.915,69.490,47.975,-47.045,52.025,44.57,224,0.875,bicubic
resnest26d,+62,30.500,-47.982,69.500,50.677,-43.613,49.323,17.07,224,0.875,bilinear
efficientnet_b2a,-16,30.423,-50.185,69.577,49.675,-45.635,50.325,9.11,288,1.000,bicubic
tf_efficientnet_b1_ap,+32,30.419,-48.859,69.581,49.553,-44.755,50.447,7.79,240,0.882,bicubic
dpn98,+18,30.058,-49.578,69.942,48.240,-46.354,51.760,61.57,224,0.875,bicubic
tf_efficientnet_b2,+2,30.020,-50.070,69.980,49.590,-45.316,50.410,9.11,260,0.890,bicubic
dpn131,+9,30.014,-49.814,69.986,48.144,-46.560,51.856,79.25,224,0.875,bicubic
senet154,-35,30.001,-51.303,69.999,48.032,-47.466,51.968,115.09,224,0.875,bilinear
dpn92,=,29.969,-50.047,70.031,49.160,-45.678,50.840,37.67,224,0.875,bicubic
gluon_senet154,-36,29.887,-51.337,70.113,47.873,-47.483,52.127,115.09,224,0.875,bicubic
xception,+34,29.849,-49.199,70.151,48.690,-45.702,51.310,22.86,299,0.897,bicubic
adv_inception_v3,+80,29.824,-47.756,70.176,47.867,-45.857,52.133,23.83,299,0.875,bicubic
resnetblur50,+22,29.623,-49.667,70.377,48.250,-46.382,51.750,25.56,224,0.875,bicubic
efficientnet_b2,-18,29.617,-50.785,70.383,48.773,-46.303,51.227,9.11,260,0.875,bicubic
gluon_xception65,+9,29.555,-50.049,70.445,47.523,-47.225,52.477,39.92,299,0.875,bicubic
resnext101_32x8d,+15,29.435,-49.877,70.565,48.482,-46.044,51.518,88.79,224,0.875,bilinear
ssl_resnet50,+20,29.423,-49.805,70.577,49.773,-45.059,50.227,25.56,224,0.875,bilinear
resnext50_32x4d,=,29.328,-50.434,70.671,47.395,-47.205,52.605,25.03,224,0.875,bicubic
ecaresnet50d_pruned,=,29.216,-50.502,70.784,48.458,-46.432,51.542,19.94,224,0.875,bicubic
tresnet_l_448,-61,29.167,-53.101,70.833,47.234,-48.744,52.766,55.99,448,0.875,bilinear
gluon_inception_v3,+32,29.114,-49.690,70.886,46.943,-47.437,53.057,23.83,299,0.875,bicubic
hrnet_w64,+5,28.987,-50.485,71.013,47.140,-47.510,52.860,128.06,224,0.875,bilinear
tf_efficientnet_b0_ns,+37,28.914,-49.738,71.086,49.011,-45.357,50.989,5.29,224,0.875,bicubic
tf_efficientnet_b1,+28,28.892,-49.940,71.108,47.511,-46.685,52.489,7.79,240,0.882,bicubic
gluon_resnet101_v1b,+8,28.857,-50.447,71.143,46.371,-48.153,53.629,44.55,224,0.875,bicubic
skresnext50_32x4d,-19,28.818,-51.332,71.182,46.503,-48.141,53.497,27.48,224,0.875,bicubic
tf_efficientnet_lite3,-10,28.654,-51.158,71.346,47.358,-47.556,52.642,8.20,300,0.904,bilinear
hrnet_w40,+20,28.645,-50.289,71.355,47.443,-47.023,52.557,57.56,224,0.875,bilinear
gluon_seresnext50_32x4d,-16,28.641,-51.271,71.359,46.450,-48.368,53.550,27.56,224,0.875,bicubic
skresnet34,+81,28.629,-48.281,71.371,47.957,-45.359,52.043,22.28,224,0.875,bicubic
resnet152,+40,28.535,-49.777,71.465,47.114,-46.932,52.886,60.19,224,0.875,bilinear
hrnet_w48,=,28.407,-50.903,71.593,47.574,-46.944,52.426,77.47,224,0.875,bilinear
gluon_resnext50_32x4d,-4,28.383,-50.973,71.617,45.326,-49.098,54.674,25.03,224,0.875,bicubic
efficientnet_b2_pruned,-23,28.366,-51.552,71.634,47.059,-47.789,52.941,8.31,260,0.890,bicubic
tf_efficientnet_b0_ap,+72,28.350,-48.734,71.650,47.531,-45.723,52.469,5.29,224,0.875,bicubic
dla102x2,-8,28.319,-51.133,71.681,46.757,-47.887,53.243,41.75,224,0.875,bilinear
dla169,+19,28.311,-50.399,71.689,47.399,-46.939,52.601,53.99,224,0.875,bilinear
tf_efficientnet_cc_b0_4e,+62,28.311,-48.993,71.689,47.364,-45.968,52.636,13.31,224,0.875,bicubic
mixnet_xl,-49,28.293,-52.185,71.707,46.717,-48.215,53.283,11.90,224,0.875,bicubic
gluon_resnet50_v1d,+3,28.236,-50.838,71.764,45.876,-48.600,54.124,25.58,224,0.875,bicubic
wide_resnet101_2,+10,28.106,-50.740,71.894,46.425,-47.859,53.575,126.89,224,0.875,bilinear
gluon_resnet101_v1c,-16,28.102,-51.442,71.898,45.953,-48.633,54.047,44.57,224,0.875,bicubic
densenet161,+56,28.100,-49.248,71.900,46.651,-46.997,53.349,28.68,224,0.875,bicubic
regnetx_320,-41,28.079,-52.167,71.921,45.120,-49.902,54.880,107.81,224,0.875,bicubic
regnety_320,-61,28.071,-52.743,71.929,45.460,-49.780,54.540,145.05,224,0.875,bicubic
dpn68b,+48,27.884,-49.630,72.116,47.460,-46.362,52.540,12.61,224,0.875,bicubic
regnetx_160,-32,27.825,-52.041,72.175,45.631,-49.197,54.369,54.28,224,0.875,bicubic
tf_inception_v3,+38,27.786,-50.070,72.214,45.711,-47.933,54.289,23.83,299,0.875,bicubic
res2net101_26w_4s,-8,27.774,-51.422,72.226,45.171,-49.269,54.829,45.21,224,0.875,bilinear
regnety_160,-48,27.639,-52.661,72.361,45.534,-49.428,54.466,83.59,224,0.875,bicubic
hrnet_w44,-2,27.625,-51.269,72.375,45.831,-48.539,54.169,67.06,224,0.875,bilinear
inception_v3,+45,27.570,-49.866,72.430,45.261,-48.215,54.739,23.83,299,0.875,bicubic
regnetx_080,-13,27.411,-51.787,72.589,45.022,-49.536,54.978,39.57,224,0.875,bicubic
hrnet_w30,+21,27.385,-50.811,72.615,46.542,-47.678,53.458,37.71,224,0.875,bilinear
hrnet_w32,+13,27.377,-51.071,72.623,45.990,-48.198,54.010,41.23,224,0.875,bilinear
gluon_resnet50_v1s,-1,27.326,-51.386,72.674,45.214,-49.028,54.786,25.68,224,0.875,bicubic
densenet201,+45,27.261,-50.029,72.739,46.224,-47.254,53.776,20.01,224,0.875,bicubic
regnety_064,-38,27.228,-52.484,72.772,44.851,-49.923,55.149,30.58,224,0.875,bicubic
densenetblur121d,+57,27.224,-49.352,72.776,46.307,-46.883,53.693,8.00,224,0.875,bicubic
efficientnet_b1_pruned,+13,27.195,-51.047,72.805,45.872,-47.960,54.128,6.33,240,0.882,bicubic
res2net50_26w_8s,-22,27.073,-52.137,72.927,44.432,-49.930,55.568,48.40,224,0.875,bilinear
dla102x,=,27.023,-51.485,72.977,45.495,-48.739,54.505,26.77,224,0.875,bilinear
resnet101,+35,26.968,-50.406,73.031,45.236,-48.310,54.764,44.55,224,0.875,bilinear
resnext50d_32x4d,-42,26.874,-52.800,73.126,44.430,-50.438,55.570,25.05,224,0.875,bicubic
regnetx_120,-40,26.864,-52.726,73.136,44.682,-50.058,55.318,46.11,224,0.875,bicubic
seresnext101_32x4d,-62,26.819,-53.417,73.181,43.508,-51.520,56.492,48.96,224,0.875,bilinear
densenet169,+55,26.811,-49.101,73.189,45.375,-47.649,54.625,14.15,224,0.875,bicubic
regnetx_064,-24,26.802,-52.264,73.198,44.904,-49.552,55.096,26.21,224,0.875,bicubic
regnety_120,-72,26.782,-53.600,73.218,44.440,-50.688,55.560,51.82,224,0.875,bicubic
regnetx_032,+6,26.707,-51.459,73.293,45.226,-48.854,54.774,15.30,224,0.875,bicubic
densenet121,+55,26.676,-48.898,73.324,45.900,-46.756,54.100,7.98,224,0.875,bicubic
seresnet152,-13,26.672,-51.986,73.328,43.945,-50.429,56.055,66.82,224,0.875,bilinear
tf_efficientnet_el,-79,26.623,-53.825,73.377,44.636,-50.524,55.364,10.59,300,0.904,bicubic
efficientnet_es,+4,26.617,-51.437,73.383,45.106,-48.824,54.894,5.44,224,0.875,bicubic
res2net50_26w_6s,-14,26.587,-51.987,73.413,43.978,-50.148,56.022,37.05,224,0.875,bilinear
dla60x,-4,26.564,-51.678,73.436,45.039,-48.983,54.961,17.65,224,0.875,bilinear
regnety_080,-63,26.515,-53.353,73.485,44.355,-50.477,55.645,39.18,224,0.875,bicubic
tf_efficientnet_b0,+34,26.491,-50.349,73.509,45.656,-47.570,54.344,5.29,224,0.875,bicubic
res2net50_14w_8s,-2,26.471,-51.681,73.529,44.369,-49.473,55.631,25.06,224,0.875,bilinear
gluon_resnet50_v1b,+13,26.432,-51.146,73.568,44.033,-49.685,55.967,25.56,224,0.875,bicubic
regnetx_040,-18,26.239,-52.247,73.760,44.424,-49.818,55.576,22.12,224,0.875,bicubic
dpn68,+37,26.122,-50.184,73.878,44.233,-48.737,55.767,12.61,224,0.875,bicubic
hrnet_w18,+30,25.976,-50.780,74.024,44.809,-48.633,55.191,21.30,224,0.875,bilinear
regnety_040,-46,25.913,-53.309,74.087,43.854,-50.802,56.146,20.65,224,0.875,bicubic
resnet34,+49,25.884,-49.228,74.116,43.990,-48.298,56.010,21.80,224,0.875,bilinear
res2net50_26w_4s,-2,25.870,-52.076,74.130,43.161,-50.691,56.839,25.70,224,0.875,bilinear
tresnet_m_448,-121,25.850,-55.862,74.150,42.868,-52.702,57.132,31.39,448,0.875,bilinear
gluon_resnet50_v1c,-8,25.795,-52.215,74.205,43.017,-50.971,56.983,25.58,224,0.875,bicubic
selecsls60,-6,25.729,-52.253,74.272,44.069,-49.763,55.931,30.67,224,0.875,bicubic
dla60_res2net,-25,25.642,-52.830,74.358,43.589,-50.615,56.411,21.15,224,0.875,bilinear
dla60_res2next,-24,25.638,-52.810,74.362,43.670,-50.474,56.330,17.33,224,0.875,bilinear
tf_efficientnet_lite1,+23,25.506,-51.132,74.493,43.583,-49.649,56.417,5.42,240,0.882,bicubic
mixnet_l,-46,25.499,-53.477,74.501,43.463,-50.721,56.537,7.33,224,0.875,bicubic
efficientnet_b1,-37,25.483,-53.215,74.517,43.286,-50.866,56.714,7.79,240,0.875,bicubic
tv_resnext50_32x4d,-5,25.469,-52.149,74.531,42.791,-50.907,57.209,25.03,224,0.875,bilinear
tf_mixnet_l,-42,25.420,-53.350,74.580,42.544,-51.460,57.456,7.33,224,0.875,bicubic
res2next50,-23,25.395,-52.847,74.606,42.492,-51.400,57.508,24.67,224,0.875,bilinear
selecsls60b,-29,25.328,-53.090,74.672,43.554,-50.612,56.446,32.77,224,0.875,bicubic
seresnet101,-29,25.328,-53.068,74.672,42.828,-51.430,57.172,49.33,224,0.875,bilinear
regnety_032,-50,25.324,-53.546,74.676,42.907,-51.495,57.093,19.44,224,0.875,bicubic
dla102,-22,25.314,-52.712,74.686,43.837,-50.113,56.163,33.73,224,0.875,bilinear
wide_resnet50_2,-36,25.310,-53.158,74.690,42.178,-51.908,57.822,68.88,224,0.875,bilinear
resnest14d,+25,25.282,-50.222,74.718,44.121,-48.393,55.879,10.61,224,0.875,bilinear
seresnext50_32x4d,-62,25.218,-53.858,74.782,41.938,-52.496,58.062,27.56,224,0.875,bilinear
res2net50_48w_2s,-10,25.023,-52.491,74.977,42.202,-51.346,57.798,25.29,224,0.875,bilinear
efficientnet_b0,-18,25.015,-52.677,74.985,42.785,-50.747,57.215,5.29,224,0.875,bicubic
gluon_resnet34_v1b,+35,24.948,-49.632,75.052,42.237,-49.751,57.763,21.80,224,0.875,bicubic
mobilenetv2_120d,-7,24.933,-52.361,75.067,43.064,-50.438,56.936,5.83,224,0.875,bicubic
dla60,-1,24.927,-52.097,75.073,43.302,-50.006,56.698,22.33,224,0.875,bilinear
regnety_016,-23,24.819,-53.033,75.181,42.626,-51.090,57.374,11.20,224,0.875,bicubic
tf_efficientnet_em,-53,24.534,-54.164,75.466,42.410,-51.910,57.590,6.90,240,0.882,bicubic
tf_efficientnet_lite2,-16,24.530,-52.930,75.470,42.292,-51.454,57.708,6.09,260,0.890,bicubic
skresnet18,+36,24.494,-48.550,75.505,42.538,-48.640,57.462,11.96,224,0.875,bicubic
regnetx_016,-4,24.477,-52.453,75.523,42.502,-50.916,57.498,9.19,224,0.875,bicubic
tf_efficientnet_lite0,+22,24.371,-50.471,75.629,42.510,-49.660,57.490,4.65,224,0.875,bicubic
tv_resnet50,+4,24.092,-52.038,75.908,41.309,-51.553,58.691,25.56,224,0.875,bilinear
seresnet34,+21,24.037,-50.771,75.963,41.895,-50.231,58.105,21.96,224,0.875,bilinear
tv_densenet121,+21,23.846,-50.906,76.154,41.921,-50.231,58.079,7.98,224,0.875,bicubic
tf_efficientnet_es,-16,23.824,-53.440,76.176,41.319,-52.281,58.681,5.44,224,0.875,bicubic
mobilenetv2_140,-3,23.710,-52.814,76.290,41.469,-51.521,58.531,6.11,224,0.875,bicubic
mixnet_m,-17,23.709,-53.547,76.291,41.139,-52.279,58.861,5.01,224,0.875,bicubic
dla34,+19,23.677,-50.959,76.323,41.543,-50.521,58.457,15.78,224,0.875,bilinear
seresnet50,-34,23.644,-53.992,76.356,40.081,-53.671,59.919,28.09,224,0.875,bilinear
tf_mixnet_m,-15,23.479,-53.471,76.521,41.005,-52.151,58.995,5.01,224,0.875,bicubic
tv_resnet34,+22,23.473,-49.841,76.527,41.367,-50.053,58.633,21.80,224,0.875,bilinear
selecsls42b,-21,23.366,-53.810,76.633,40.677,-52.715,59.323,32.46,224,0.875,bicubic
mobilenetv2_110d,+8,23.070,-51.982,76.930,40.744,-51.436,59.256,4.52,224,0.875,bicubic
mobilenetv3_large_100,-5,22.665,-53.103,77.335,40.785,-51.755,59.215,5.48,224,0.875,bicubic
mobilenetv3_rw,-4,22.626,-53.002,77.374,40.370,-52.340,59.630,5.48,224,0.875,bicubic
tf_mobilenetv3_large_100,-3,22.571,-52.945,77.429,39.759,-52.841,60.241,5.48,224,0.875,bilinear
hrnet_w18_small_v2,+1,22.341,-52.785,77.659,39.847,-52.569,60.153,15.60,224,0.875,bilinear
regnety_008,-14,22.113,-54.201,77.887,38.896,-54.166,61.104,6.26,224,0.875,bicubic
seresnext26tn_32x4d,-52,22.003,-55.987,77.997,38.492,-55.256,61.508,16.81,224,0.875,bicubic
seresnext26t_32x4d,-52,21.987,-56.001,78.013,38.566,-55.140,61.434,16.82,224,0.875,bicubic
regnety_006,-4,21.973,-53.287,78.027,38.953,-53.575,61.047,6.06,224,0.875,bicubic
regnetx_008,=,21.952,-53.070,78.048,38.930,-53.414,61.070,7.26,224,0.875,bicubic
resnet26d,-23,21.914,-54.766,78.086,38.617,-54.549,61.383,16.01,224,0.875,bicubic
semnasnet_100,-9,21.897,-53.559,78.103,38.604,-53.988,61.396,3.89,224,0.875,bicubic
regnetx_006,+6,21.743,-52.119,78.257,38.904,-52.776,61.096,6.20,224,0.875,bicubic
gluon_resnet18_v1b,+16,21.545,-49.285,78.455,38.873,-50.883,61.127,11.69,224,0.875,bicubic
fbnetc_100,-8,21.492,-53.628,78.508,38.165,-54.221,61.835,5.57,224,0.875,bilinear
mnasnet_100,-2,21.350,-53.306,78.650,37.715,-54.411,62.285,4.38,224,0.875,bicubic
resnet26,-13,21.295,-53.997,78.705,38.016,-54.554,61.984,16.00,224,0.875,bicubic
ssl_resnet18,+7,21.278,-51.322,78.722,39.114,-52.302,60.886,11.69,224,0.875,bilinear
mixnet_s,-24,21.258,-54.730,78.742,38.193,-54.601,61.807,4.13,224,0.875,bicubic
seresnext26d_32x4d,-55,21.254,-56.350,78.746,37.285,-56.327,62.715,16.81,224,0.875,bicubic
seresnext26_32x4d,-41,21.093,-56.007,78.907,37.639,-55.671,62.361,16.79,224,0.875,bicubic
regnetx_004,+4,20.887,-51.519,79.113,37.548,-53.282,62.452,5.16,224,0.875,bicubic
spnasnet_100,-6,20.867,-53.213,79.133,37.892,-53.940,62.108,4.42,224,0.875,bilinear
seresnet18,+5,20.840,-50.918,79.160,37.645,-52.689,62.355,11.78,224,0.875,bicubic
mobilenetv2_100,-1,20.761,-52.217,79.239,37.751,-53.265,62.249,3.50,224,0.875,bicubic
tf_mixnet_s,-28,20.478,-55.170,79.522,36.627,-56.009,63.373,4.13,224,0.875,bicubic
regnety_004,-9,20.417,-53.609,79.583,37.030,-54.718,62.970,4.34,224,0.875,bicubic
tf_mobilenetv3_large_075,-8,20.372,-53.070,79.628,36.770,-54.582,63.230,3.99,224,0.875,bilinear
hrnet_w18_small,-2,20.366,-51.976,79.634,37.094,-53.578,62.906,13.19,224,0.875,bilinear
resnet18,+2,20.228,-49.530,79.772,37.260,-51.818,62.740,11.69,224,0.875,bilinear
tf_mobilenetv3_large_minimal_100,-3,20.116,-52.128,79.884,36.904,-53.732,63.096,3.92,224,0.875,bilinear
regnety_002,-1,17.460,-52.822,82.540,32.443,-57.097,67.557,3.16,224,0.875,bicubic
regnetx_002,=,16.951,-51.803,83.049,32.235,-56.313,67.765,2.68,224,0.875,bicubic
dla60x_c,+1,16.326,-51.582,83.674,31.775,-56.659,68.225,1.34,224,0.875,bilinear
tf_mobilenetv3_small_100,-1,16.233,-51.685,83.767,31.223,-56.439,68.777,2.54,224,0.875,bilinear
tf_mobilenetv3_small_075,+1,14.940,-50.778,85.060,29.572,-56.564,70.428,2.04,224,0.875,bilinear
dla46_c,+1,14.661,-50.217,85.339,29.374,-56.912,70.626,1.31,224,0.875,bilinear
dla46x_c,-2,14.380,-51.600,85.620,29.177,-57.803,70.823,1.08,224,0.875,bilinear
tf_mobilenetv3_small_minimal_100,=,13.968,-48.930,86.032,27.980,-56.250,72.019,2.04,224,0.875,bilinear
model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation,top1_diff,top5_diff,rank_diff
ig_resnext101_32x48d,58.810,41.190,81.076,18.924,828.41,224,0.875,bilinear,-26.618,-16.496,+5
ig_resnext101_32x32d,58.386,41.614,80.381,19.619,468.53,224,0.875,bilinear,-26.708,-17.057,+9
ig_resnext101_32x16d,57.690,42.310,79.905,20.095,194.03,224,0.875,bilinear,-26.480,-17.291,+14
swsl_resnext101_32x16d,57.458,42.542,80.385,19.615,194.03,224,0.875,bilinear,-25.888,-16.461,+18
swsl_resnext101_32x8d,56.438,43.562,78.944,21.056,88.79,224,0.875,bilinear,-27.845,-18.232,+10
ig_resnext101_32x8d,54.918,45.082,77.534,22.466,88.79,224,0.875,bilinear,-27.770,-19.103,+23
swsl_resnext101_32x4d,53.603,46.397,76.347,23.653,44.18,224,0.875,bilinear,-29.627,-20.413,+17
tf_efficientnet_l2_ns_475,51.494,48.506,73.928,26.072,480.31,475,0.936,bicubic,-36.740,-24.618,-6
swsl_resnext50_32x4d,50.437,49.563,73.368,26.633,25.03,224,0.875,bilinear,-31.745,-22.862,+24
swsl_resnet50,49.541,50.459,72.334,27.666,25.56,224,0.875,bilinear,-31.625,-23.638,+38
tf_efficientnet_b7_ns,47.800,52.200,69.640,30.360,66.35,600,0.949,bicubic,-39.040,-28.454,-8
tf_efficientnet_b6_ns,47.761,52.239,69.968,30.032,43.04,528,0.942,bicubic,-38.691,-27.914,-8
tf_efficientnet_l2_ns,47.570,52.430,70.019,29.981,480.31,800,0.960,bicubic,-40.782,-28.631,-12
tf_efficientnet_b8_ap,45.774,54.226,67.911,32.089,87.41,672,0.954,bicubic,-39.596,-29.383,-6
tf_efficientnet_b5_ns,45.615,54.385,67.842,32.158,30.39,456,0.934,bicubic,-40.473,-29.910,-10
tf_efficientnet_b4_ns,43.450,56.550,65.519,34.481,19.34,380,0.922,bicubic,-41.713,-31.951,-7
tf_efficientnet_b8,42.508,57.492,64.857,35.143,87.41,672,0.954,bicubic,-42.862,-32.533,-10
tf_efficientnet_b7,41.431,58.569,63.017,36.983,66.35,600,0.949,bicubic,-43.505,-34.186,-6
tf_efficientnet_b7_ap,41.429,58.571,62.874,37.126,66.35,600,0.949,bicubic,-43.691,-34.378,-9
tf_efficientnet_b5_ap,41.418,58.582,62.084,37.916,30.39,456,0.934,bicubic,-42.834,-34.890,-4
tf_efficientnet_b6_ap,41.099,58.901,62.355,37.645,43.04,528,0.942,bicubic,-43.689,-34.783,-8
tf_efficientnet_b4_ap,40.484,59.516,61.723,38.277,19.34,380,0.922,bicubic,-42.764,-34.669,+1
tf_efficientnet_b3_ns,39.584,60.416,61.453,38.547,12.23,300,0.904,bicubic,-44.464,-35.457,-4
tf_efficientnet_b5,38.356,61.644,59.913,40.087,30.39,456,0.934,bicubic,-45.456,-36.835,-3
resnest269e,37.315,62.685,57.468,42.532,110.93,416,0.928,bicubic,-47.203,-39.518,-11
tf_efficientnet_b3_ap,37.055,62.945,57.240,42.760,12.23,300,0.904,bicubic,-44.767,-38.384,+12
tf_efficientnet_b2_ns,36.183,63.817,57.551,42.449,9.11,260,0.890,bicubic,-46.197,-38.697,+4
ecaresnet101d,36.004,63.996,56.165,43.835,44.57,224,0.875,bicubic,-46.168,-39.881,+6
resnest200e,35.931,64.069,55.849,44.151,70.20,320,0.909,bicubic,-47.901,-41.045,-9
swsl_resnet18,35.858,64.142,58.455,41.545,11.69,224,0.875,bilinear,-37.418,-33.279,+195
resnest101e,35.373,64.627,55.780,44.220,48.28,256,0.875,bilinear,-47.517,-40.540,-4
ssl_resnext101_32x16d,34.603,65.397,55.931,44.069,194.03,224,0.875,bilinear,-47.241,-40.165,+5
resnest50d_4s2x40d,34.355,65.645,54.725,45.275,30.42,224,0.875,bicubic,-46.753,-40.833,+16
tf_efficientnet_b1_ns,34.157,65.843,55.489,44.511,7.79,240,0.882,bicubic,-47.231,-40.249,+12
tf_efficientnet_b4,34.064,65.936,54.198,45.802,19.34,380,0.922,bicubic,-48.958,-42.102,-9
ssl_resnext101_32x8d,34.017,65.983,55.601,44.399,88.79,224,0.875,bilinear,-47.599,-40.437,+6
tf_efficientnet_b6,33.998,66.002,54.544,45.456,43.04,528,0.942,bicubic,-50.112,-42.342,-19
efficientnet_b3_pruned,33.996,66.004,54.108,45.892,9.86,300,0.904,bicubic,-46.862,-41.134,+18
tresnet_xl,33.257,66.743,52.294,47.706,78.44,224,0.875,bilinear,-48.797,-43.642,-4
resnest50d_1s4x24d,33.147,66.853,52.839,47.161,25.68,224,0.875,bicubic,-47.841,-42.483,+11
rexnet_200,32.987,67.013,52.939,47.061,16.37,224,0.875,bicubic,-48.645,-42.729,0
resnest50d,32.972,67.028,52.713,47.287,27.48,224,0.875,bilinear,-48.002,-42.665,+10
tf_efficientnet_b3,32.860,67.140,52.950,47.050,12.23,300,0.904,bicubic,-48.776,-42.767,-3
pnasnet5large,32.848,67.152,50.500,49.500,86.06,331,0.911,bicubic,-49.934,-45.540,-16
nasnetalarge,32.775,67.225,50.141,49.859,88.75,331,0.911,bicubic,-49.845,-45.906,-15
inception_resnet_v2,32.738,67.262,50.648,49.352,55.84,299,0.897,bicubic,-47.720,-44.658,+20
gluon_resnet152_v1d,32.734,67.266,51.088,48.912,60.21,224,0.875,bicubic,-47.740,-44.118,+17
tf_efficientnet_b2_ap,32.681,67.319,52.239,47.761,9.11,260,0.890,bicubic,-47.619,-42.789,+27
tresnet_l,32.559,67.441,51.139,48.861,55.99,224,0.875,bilinear,-48.929,-44.485,-4
ens_adv_inception_resnet_v2,32.370,67.629,50.427,49.573,55.84,299,0.897,bicubic,-47.611,-44.509,+36
gluon_resnet152_v1s,32.331,67.669,50.526,49.474,60.32,224,0.875,bicubic,-48.685,-44.886,-1
gluon_seresnext101_64x4d,32.205,67.795,50.319,49.681,88.23,224,0.875,bicubic,-48.689,-44.989,+3
gluon_seresnext101_32x4d,32.107,67.893,51.237,48.763,48.96,224,0.875,bicubic,-48.797,-44.057,+1
cspresnext50,31.822,68.178,51.602,48.398,20.57,224,0.875,bilinear,-48.218,-43.342,+30
efficientnet_b3a,31.732,68.268,51.325,48.675,12.23,320,1.000,bicubic,-50.134,-44.511,-19
efficientnet_b3,31.555,68.445,51.276,48.724,12.23,300,0.904,bicubic,-49.939,-44.440,-12
resnet50,31.547,68.453,50.170,49.830,25.56,224,0.875,bicubic,-47.491,-44.220,+68
ssl_resnext101_32x4d,31.423,68.577,52.121,47.879,44.18,224,0.875,bilinear,-49.501,-43.607,-5
inception_v4,31.378,68.622,49.244,50.756,42.68,299,0.875,bicubic,-48.790,-45.724,+20
rexnet_150,31.366,68.634,51.288,48.712,9.73,224,0.875,bicubic,-48.944,-43.878,+13
ecaresnetlight,31.121,68.879,50.243,49.757,30.16,224,0.875,bicubic,-49.341,-45.007,+4
gluon_resnet101_v1s,31.115,68.885,49.793,50.207,44.67,224,0.875,bicubic,-49.187,-45.367,+12
tf_efficientnet_cc_b0_8e,31.087,68.913,50.761,49.239,24.01,224,0.875,bicubic,-46.821,-42.892,+100
ecaresnet50d,31.058,68.942,50.848,49.152,25.58,224,0.875,bicubic,-49.534,-44.472,-2
cspdarknet53,31.018,68.981,50.390,49.610,27.64,256,0.887,bilinear,-49.040,-44.694,+18
tresnet_m,30.997,69.003,48.682,51.318,31.39,224,0.875,bilinear,-49.805,-46.178,-7
gluon_resnet152_v1c,30.991,69.009,48.924,51.076,60.21,224,0.875,bicubic,-48.919,-45.916,+22
gluon_resnext101_64x4d,30.987,69.013,48.549,51.451,83.46,224,0.875,bicubic,-49.617,-46.439,-7
tf_efficientnet_cc_b1_8e,30.899,69.101,50.080,49.920,39.72,240,0.882,bicubic,-48.409,-44.290,+42
ecaresnet101d_pruned,30.897,69.103,50.013,49.987,24.88,224,0.875,bicubic,-49.921,-45.615,-13
gluon_resnext101_32x4d,30.877,69.123,48.537,51.463,44.18,224,0.875,bicubic,-49.457,-46.389,0
tf_efficientnet_lite4,30.830,69.170,50.386,49.614,13.01,380,0.920,bilinear,-50.706,-45.282,-29
dpn107,30.678,69.322,48.810,51.190,86.92,224,0.875,bicubic,-49.478,-46.100,+7
ese_vovnet39b,30.657,69.343,49.875,50.125,24.57,224,0.875,bicubic,-48.663,-44.837,+35
gluon_resnet152_v1b,30.623,69.376,48.521,51.479,60.19,224,0.875,bicubic,-49.063,-46.215,+24
tresnet_xl_448,30.614,69.386,49.069,50.931,78.44,448,0.875,bilinear,-52.436,-47.104,-51
ssl_resnext50_32x4d,30.594,69.406,50.657,49.343,25.03,224,0.875,bilinear,-49.724,-44.749,-5
gluon_resnet101_v1d,30.523,69.477,47.950,52.050,44.57,224,0.875,bicubic,-49.891,-47.064,-10
dpn68b,30.517,69.483,49.158,50.842,12.61,224,0.875,bicubic,-48.699,-45.256,+39
resnest26d,30.490,69.510,50.677,49.323,17.07,224,0.875,bilinear,-47.988,-43.621,+63
efficientnet_b2a,30.435,69.565,49.698,50.302,9.11,288,1.000,bicubic,-50.177,-45.620,-21
tf_efficientnet_b1_ap,30.421,69.579,49.553,50.447,7.79,240,0.882,bicubic,-48.859,-44.753,+33
seresnet50,30.077,69.923,49.292,50.708,28.09,224,0.875,bicubic,-50.197,-45.778,-6
dpn98,30.067,69.933,48.244,51.756,61.57,224,0.875,bicubic,-49.575,-46.354,+17
tf_efficientnet_b2,30.026,69.974,49.581,50.419,9.11,260,0.890,bicubic,-50.060,-45.327,-3
dpn131,30.024,69.976,48.146,51.854,79.25,224,0.875,bicubic,-49.798,-46.564,+7
dpn92,29.953,70.047,49.162,50.838,37.67,224,0.875,bicubic,-50.055,-45.674,-2
gluon_senet154,29.877,70.123,47.894,52.106,115.09,224,0.875,bicubic,-51.357,-47.454,-41
xception,29.865,70.135,48.686,51.314,22.86,299,0.897,bicubic,-49.187,-45.706,+35
adv_inception_v3,29.816,70.184,47.847,52.153,23.83,299,0.875,bicubic,-47.766,-45.889,+80
gluon_xception65,29.784,70.216,47.755,52.245,39.92,299,0.903,bicubic,-49.932,-47.105,+7
resnetblur50,29.625,70.375,48.248,51.752,25.56,224,0.875,bicubic,-49.661,-46.390,+22
efficientnet_b2,29.615,70.385,48.777,51.223,9.11,260,0.875,bicubic,-50.777,-46.299,-24
resnext101_32x8d,29.439,70.561,48.486,51.514,88.79,224,0.875,bilinear,-49.869,-46.032,+16
ssl_resnet50,29.423,70.577,49.781,50.219,25.56,224,0.875,bilinear,-49.799,-45.051,+21
resnext50_32x4d,29.331,70.669,47.397,52.603,25.03,224,0.875,bicubic,-50.438,-47.201,-1
ecaresnet50d_pruned,29.215,70.785,48.453,51.547,19.94,224,0.875,bicubic,-50.501,-46.427,0
tresnet_l_448,29.165,70.835,47.232,52.768,55.99,448,0.875,bilinear,-53.103,-48.744,-66
gluon_inception_v3,29.124,70.876,46.957,53.043,23.83,299,0.875,bicubic,-49.682,-47.413,+33
xception71,29.047,70.953,47.405,52.595,42.34,299,0.903,bicubic,-50.826,-47.517,-9
hrnet_w64,28.989,71.011,47.142,52.858,128.06,224,0.875,bilinear,-50.485,-47.510,+5
tf_efficientnet_b0_ns,28.902,71.098,49.011,50.989,5.29,224,0.875,bicubic,-49.756,-45.365,+36
xception65,28.896,71.104,47.167,52.833,39.92,299,0.903,bicubic,-50.656,-47.487,0
tf_efficientnet_b1,28.886,71.114,47.503,52.497,7.79,240,0.882,bicubic,-49.940,-46.695,+27
gluon_resnet101_v1b,28.878,71.121,46.389,53.611,44.55,224,0.875,bicubic,-50.427,-48.135,+7
skresnext50_32x4d,28.818,71.182,46.497,53.503,27.48,224,0.875,bicubic,-51.338,-48.145,-25
tf_efficientnet_lite3,28.660,71.340,47.354,52.646,8.20,300,0.904,bilinear,-51.160,-47.560,-13
gluon_seresnext50_32x4d,28.651,71.349,46.436,53.564,27.56,224,0.875,bicubic,-51.267,-48.386,-21
skresnet34,28.645,71.355,47.953,52.047,22.28,224,0.875,bicubic,-48.267,-45.369,+78
hrnet_w40,28.641,71.359,47.454,52.546,57.56,224,0.875,bilinear,-50.279,-47.016,+17
resnet152,28.533,71.467,47.118,52.882,60.19,224,0.875,bilinear,-49.779,-46.920,+38
hrnet_w48,28.413,71.587,47.586,52.414,77.47,224,0.875,bilinear,-50.887,-46.926,+1
gluon_resnext50_32x4d,28.375,71.624,45.328,54.672,25.03,224,0.875,bicubic,-50.978,-49.098,-5
efficientnet_b2_pruned,28.362,71.638,47.051,52.949,8.31,260,0.890,bicubic,-51.554,-47.805,-26
tf_efficientnet_b0_ap,28.346,71.654,47.531,52.469,5.29,224,0.875,bicubic,-48.740,-45.725,+68
tf_efficientnet_cc_b0_4e,28.315,71.685,47.364,52.636,13.31,224,0.875,bicubic,-48.991,-45.970,+61
dla102x2,28.313,71.687,46.761,53.239,41.28,224,0.875,bilinear,-51.135,-47.879,-10
dla169,28.313,71.687,47.391,52.609,53.39,224,0.875,bilinear,-50.375,-46.945,+19
mixnet_xl,28.287,71.713,46.702,53.298,11.90,224,0.875,bicubic,-52.189,-48.234,-56
gluon_resnet50_v1d,28.246,71.754,45.878,54.122,25.58,224,0.875,bicubic,-50.828,-48.592,+2
wide_resnet101_2,28.108,71.892,46.401,53.599,126.89,224,0.875,bilinear,-50.748,-47.881,+9
gluon_resnet101_v1c,28.104,71.896,45.961,54.039,44.57,224,0.875,bicubic,-51.430,-48.617,-18
regnetx_320,28.093,71.907,45.126,54.874,107.81,224,0.875,bicubic,-52.154,-49.900,-45
densenet161,28.081,71.919,46.641,53.359,28.68,224,0.875,bicubic,-49.277,-46.997,+52
regnety_320,28.059,71.941,45.444,54.556,145.05,224,0.875,bicubic,-52.753,-49.800,-67
xception41,27.888,72.112,45.890,54.110,26.97,299,0.903,bicubic,-50.628,-48.388,+14
regnetx_160,27.817,72.183,45.617,54.383,54.28,224,0.875,bicubic,-52.039,-49.213,-35
tf_inception_v3,27.780,72.220,45.721,54.279,23.83,299,0.875,bicubic,-50.078,-47.917,+38
res2net101_26w_4s,27.768,72.232,45.179,54.821,45.21,224,0.875,bilinear,-51.430,-49.253,-9
regnety_160,27.623,72.377,45.532,54.468,83.59,224,0.875,bicubic,-52.673,-49.430,-54
hrnet_w44,27.621,72.379,45.837,54.163,67.06,224,0.875,bilinear,-51.275,-48.531,-3
inception_v3,27.556,72.444,45.263,54.737,23.83,299,0.875,bicubic,-49.884,-48.213,+42
regnetx_080,27.405,72.595,45.002,54.998,39.57,224,0.875,bicubic,-51.789,-49.558,-12
hrnet_w30,27.381,72.619,46.554,53.446,37.71,224,0.875,bilinear,-50.825,-47.668,+19
hrnet_w32,27.369,72.631,45.994,54.006,41.23,224,0.875,bilinear,-51.081,-48.192,+11
gluon_resnet50_v1s,27.326,72.674,45.222,54.778,25.68,224,0.875,bicubic,-51.386,-49.016,-2
densenet201,27.265,72.735,46.222,53.778,20.01,224,0.875,bicubic,-50.021,-47.256,+41
densenetblur121d,27.228,72.772,46.299,53.701,8.00,224,0.875,bicubic,-49.360,-46.893,+55
regnety_064,27.220,72.780,44.847,55.153,30.58,224,0.875,bicubic,-52.502,-49.921,-43
efficientnet_b1_pruned,27.181,72.819,45.872,54.128,6.33,240,0.882,bicubic,-51.055,-47.962,+12
rexnet_130,27.094,72.906,45.933,54.067,7.56,224,0.875,bicubic,-52.406,-48.749,-36
res2net50_26w_8s,27.078,72.921,44.428,55.572,48.40,224,0.875,bilinear,-52.120,-49.940,-23
dla102x,27.061,72.939,45.475,54.525,26.31,224,0.875,bilinear,-51.449,-48.753,-2
resnet101,26.963,73.037,45.234,54.766,44.55,224,0.875,bilinear,-50.411,-48.306,+31
resnext50d_32x4d,26.876,73.124,44.436,55.564,25.05,224,0.875,bicubic,-52.800,-50.430,-45
regnetx_120,26.868,73.132,44.682,55.318,46.11,224,0.875,bicubic,-52.728,-50.056,-44
rexnet_100,26.831,73.169,45.369,54.631,4.80,224,0.875,bicubic,-51.027,-48.501,+18
densenet169,26.829,73.171,45.373,54.627,14.15,224,0.875,bicubic,-49.077,-47.653,+51
regnety_120,26.788,73.212,44.454,55.546,51.82,224,0.875,bicubic,-53.578,-50.672,-79
regnetx_064,26.784,73.216,44.927,55.073,26.21,224,0.875,bicubic,-52.288,-49.531,-27
regnetx_032,26.703,73.297,45.236,54.764,15.30,224,0.875,bicubic,-51.469,-48.852,+3
densenet121,26.664,73.336,45.900,54.100,7.98,224,0.875,bicubic,-48.914,-46.752,+51
tf_efficientnet_el,26.623,73.377,44.648,55.352,10.59,300,0.904,bicubic,-53.817,-50.516,-86
efficientnet_es,26.621,73.379,45.112,54.888,5.44,224,0.875,bicubic,-51.445,-48.814,+2
res2net50_26w_6s,26.595,73.405,43.990,56.010,37.05,224,0.875,bilinear,-51.975,-50.134,-16
dla60x,26.552,73.448,45.023,54.977,17.35,224,0.875,bilinear,-51.694,-48.994,-6
regnety_080,26.524,73.476,44.359,55.641,39.18,224,0.875,bicubic,-53.352,-50.471,-67
tf_efficientnet_b0,26.485,73.515,45.646,54.354,5.29,224,0.875,bicubic,-50.363,-47.582,+30
res2net50_14w_8s,26.483,73.517,44.371,55.629,25.06,224,0.875,bilinear,-51.667,-49.477,-4
gluon_resnet50_v1b,26.436,73.564,44.035,55.965,25.56,224,0.875,bicubic,-51.144,-49.681,+11
regnetx_040,26.243,73.757,44.438,55.562,22.12,224,0.875,bicubic,-52.239,-49.806,-19
dpn68,26.129,73.871,44.228,55.772,12.61,224,0.875,bicubic,-50.189,-48.750,+33
hrnet_w18,25.986,74.014,44.813,55.187,21.30,224,0.875,bilinear,-50.772,-48.631,+27
regnety_040,25.923,74.077,43.848,56.152,20.65,224,0.875,bicubic,-53.297,-50.808,-47
resnet34,25.888,74.112,43.982,56.018,21.80,224,0.875,bilinear,-49.222,-48.302,+47
res2net50_26w_4s,25.866,74.134,43.155,56.845,25.70,224,0.875,bilinear,-52.098,-50.699,-4
tresnet_m_448,25.852,74.148,42.874,57.126,31.39,448,0.875,bilinear,-55.862,-52.698,-128
gluon_resnet50_v1c,25.784,74.216,43.031,56.969,25.58,224,0.875,bicubic,-52.228,-50.957,-10
selecsls60,25.729,74.272,44.065,55.935,30.67,224,0.875,bicubic,-52.254,-49.763,-8
dla60_res2net,25.652,74.348,43.599,56.401,20.85,224,0.875,bilinear,-52.812,-50.607,-25
dla60_res2next,25.640,74.360,43.670,56.330,17.03,224,0.875,bilinear,-52.800,-50.482,-24
mixnet_l,25.512,74.488,43.455,56.545,7.33,224,0.875,bicubic,-53.464,-50.727,-46
tf_efficientnet_lite1,25.499,74.501,43.585,56.415,5.42,240,0.882,bicubic,-51.143,-49.641,+19
efficientnet_b1,25.469,74.531,43.284,56.716,7.79,240,0.875,bicubic,-53.229,-50.860,-38
tv_resnext50_32x4d,25.455,74.545,42.787,57.213,25.03,224,0.875,bilinear,-52.165,-50.909,-7
tf_mixnet_l,25.422,74.578,42.534,57.466,7.33,224,0.875,bicubic,-53.352,-51.464,-43
res2next50,25.389,74.611,42.508,57.492,24.67,224,0.875,bilinear,-52.857,-51.384,-26
regnety_032,25.332,74.668,42.911,57.089,19.44,224,0.875,bicubic,-53.554,-51.501,-49
selecsls60b,25.332,74.668,43.559,56.441,32.77,224,0.875,bicubic,-53.080,-50.614,-31
dla102,25.316,74.684,43.827,56.173,33.27,224,0.875,bilinear,-52.716,-50.119,-23
wide_resnet50_2,25.308,74.692,42.178,57.822,68.88,224,0.875,bilinear,-53.170,-51.916,-37
resnest14d,25.284,74.716,44.114,55.886,10.61,224,0.875,bilinear,-50.222,-48.404,+23
res2net50_48w_2s,25.027,74.973,42.208,57.792,25.29,224,0.875,bilinear,-52.495,-51.346,-11
efficientnet_b0,25.015,74.985,42.787,57.213,5.29,224,0.875,bicubic,-52.683,-50.745,-17
gluon_resnet34_v1b,24.939,75.061,42.243,57.757,21.80,224,0.875,bicubic,-49.649,-49.747,+34
mobilenetv2_120d,24.937,75.063,43.058,56.942,5.83,224,0.875,bicubic,-52.347,-50.434,-7
dla60,24.933,75.067,43.296,56.704,22.04,224,0.875,bilinear,-52.099,-50.022,-3
regnety_016,24.811,75.189,42.616,57.384,11.20,224,0.875,bicubic,-53.051,-51.104,-24
tf_efficientnet_em,24.542,75.458,42.412,57.588,6.90,240,0.882,bicubic,-54.166,-51.902,-54
tf_efficientnet_lite2,24.530,75.470,42.280,57.720,6.09,260,0.890,bicubic,-52.938,-51.474,-17
skresnet18,24.483,75.517,42.536,57.464,11.96,224,0.875,bicubic,-48.555,-48.632,+35
regnetx_016,24.473,75.527,42.514,57.486,9.19,224,0.875,bicubic,-52.477,-50.906,-7
tf_efficientnet_lite0,24.373,75.627,42.487,57.513,4.65,224,0.875,bicubic,-50.457,-49.689,+22
tv_resnet50,24.070,75.930,41.313,58.687,25.56,224,0.875,bilinear,-52.068,-51.551,+3
efficientnet_lite0,23.909,76.091,42.088,57.912,4.65,224,0.875,bicubic,-51.575,-50.422,+11
tv_densenet121,23.844,76.156,41.925,58.075,7.98,224,0.875,bicubic,-50.894,-50.225,+20
tf_efficientnet_es,23.819,76.181,41.331,58.669,5.44,224,0.875,bicubic,-53.439,-52.263,-16
mobilenetv2_140,23.712,76.288,41.477,58.523,6.11,224,0.875,bicubic,-52.804,-51.520,-4
mixnet_m,23.710,76.290,41.141,58.859,5.01,224,0.875,bicubic,-53.550,-52.283,-19
dla34,23.669,76.331,41.551,58.449,15.74,224,0.875,bilinear,-50.961,-50.527,+18
ese_vovnet19b_dw,23.535,76.465,41.288,58.712,6.54,224,0.875,bicubic,-53.263,-51.980,-12
tf_mixnet_m,23.484,76.516,40.989,59.011,5.01,224,0.875,bicubic,-53.458,-52.163,-16
tv_resnet34,23.473,76.527,41.367,58.633,21.80,224,0.875,bilinear,-49.839,-50.059,+21
selecsls42b,23.357,76.643,40.677,59.323,32.46,224,0.875,bicubic,-53.817,-52.713,-22
mobilenetv2_110d,23.066,76.934,40.716,59.284,4.52,224,0.875,bicubic,-51.970,-51.470,+9
mobilenetv3_large_100,22.655,77.345,40.781,59.219,5.48,224,0.875,bicubic,-53.111,-51.761,-6
mobilenetv3_rw,22.630,77.370,40.374,59.626,5.48,224,0.875,bicubic,-53.004,-52.334,-5
tf_mobilenetv3_large_100,22.569,77.431,39.767,60.233,5.48,224,0.875,bilinear,-52.949,-52.839,-4
hrnet_w18_small_v2,22.337,77.663,39.861,60.139,15.60,224,0.875,bilinear,-52.777,-52.555,+2
regnety_008,22.119,77.881,38.900,61.100,6.26,224,0.875,bicubic,-54.197,-54.166,-14
seresnext26tn_32x4d,21.991,78.009,38.482,61.518,16.81,224,0.875,bicubic,-55.995,-55.264,-51
seresnext26t_32x4d,21.985,78.015,38.570,61.430,16.82,224,0.875,bicubic,-56.013,-55.138,-53
regnety_006,21.971,78.029,38.955,61.045,6.06,224,0.875,bicubic,-53.275,-53.577,-4
regnetx_008,21.940,78.060,38.928,61.072,7.26,224,0.875,bicubic,-53.098,-53.408,-1
resnet26d,21.907,78.094,38.619,61.381,16.01,224,0.875,bicubic,-54.789,-54.531,-24
semnasnet_100,21.903,78.097,38.600,61.400,3.89,224,0.875,bicubic,-53.545,-54.004,-9
regnetx_006,21.738,78.263,38.904,61.096,6.20,224,0.875,bicubic,-52.115,-52.768,+5
gluon_resnet18_v1b,21.549,78.451,38.869,61.131,11.69,224,0.875,bicubic,-49.287,-50.893,+14
fbnetc_100,21.484,78.516,38.161,61.839,5.57,224,0.875,bilinear,-53.640,-54.225,-9
mnasnet_100,21.350,78.650,37.719,62.281,4.38,224,0.875,bicubic,-53.308,-54.395,-3
resnet26,21.295,78.705,38.018,61.982,16.00,224,0.875,bicubic,-53.997,-54.552,-13
ssl_resnet18,21.278,78.722,39.113,60.887,11.69,224,0.875,bilinear,-51.332,-52.303,+6
mixnet_s,21.254,78.746,38.187,61.813,4.13,224,0.875,bicubic,-54.738,-54.609,-25
seresnext26d_32x4d,21.252,78.748,37.311,62.689,16.81,224,0.875,bicubic,-56.350,-56.297,-55
regnetx_004,20.898,79.102,37.566,62.434,5.16,224,0.875,bicubic,-51.498,-53.264,+4
spnasnet_100,20.863,79.137,37.896,62.104,4.42,224,0.875,bilinear,-53.221,-53.922,-6
mobilenetv2_100,20.773,79.227,37.759,62.241,3.50,224,0.875,bicubic,-52.197,-53.257,0
tf_mixnet_s,20.470,79.530,36.607,63.393,4.13,224,0.875,bicubic,-55.180,-56.021,-27
regnety_004,20.415,79.585,37.002,62.998,4.34,224,0.875,bicubic,-53.619,-54.750,-8
hrnet_w18_small,20.368,79.632,37.093,62.907,13.19,224,0.875,bilinear,-51.974,-53.585,0
tf_mobilenetv3_large_075,20.366,79.634,36.764,63.236,3.99,224,0.875,bilinear,-53.072,-54.586,-8
resnet18,20.228,79.772,37.261,62.739,11.69,224,0.875,bilinear,-49.520,-51.816,+2
tf_mobilenetv3_large_minimal_100,20.122,79.878,36.908,63.092,3.92,224,0.875,bilinear,-52.126,-53.722,-2
regnety_002,17.450,82.550,32.431,67.569,3.16,224,0.875,bicubic,-52.802,-57.109,-1
regnetx_002,16.962,83.038,32.225,67.775,2.68,224,0.875,bicubic,-51.800,-56.331,0
dla60x_c,16.310,83.690,31.761,68.239,1.32,224,0.875,bilinear,-51.582,-56.665,+1
tf_mobilenetv3_small_100,16.226,83.775,31.223,68.777,2.54,224,0.875,bilinear,-51.697,-56.441,-1
tf_mobilenetv3_small_075,14.944,85.056,29.572,70.428,2.04,224,0.875,bilinear,-50.772,-56.558,+1
dla46_c,14.657,85.343,29.380,70.620,1.30,224,0.875,bilinear,-50.209,-56.912,+1
dla46x_c,14.382,85.618,29.191,70.809,1.07,224,0.875,bilinear,-51.588,-57.789,-2
tf_mobilenetv3_small_minimal_100,13.964,86.036,27.988,72.012,2.04,224,0.875,bilinear,-48.942,-56.242,0

1 model top1 top1_err top5 top5_err param_count img_size cropt_pct interpolation top1_diff top5_diff rank_diff
2 ig_resnext101_32x48d 58.814 58.810 41.186 41.190 81.086 81.076 18.914 18.924 828.41 224 0.875 bilinear -26.628 -26.618 -16.486 -16.496 +5
3 ig_resnext101_32x32d 58.380 58.386 41.620 41.614 80.379 80.381 19.621 19.619 468.53 224 0.875 bilinear -26.712 -26.708 -17.057 +9
4 ig_resnext101_32x16d 57.700 57.690 42.300 42.310 79.913 79.905 20.087 20.095 194.03 224 0.875 bilinear -26.476 -26.480 -17.283 -17.291 +14
5 swsl_resnext101_32x16d 57.466 57.458 42.534 42.542 80.381 80.385 19.619 19.615 194.03 224 0.875 bilinear -25.872 -25.888 -16.471 -16.461 +18
6 swsl_resnext101_32x8d 56.435 56.438 43.565 43.562 78.934 78.944 21.066 21.056 88.79 224 0.875 bilinear -27.859 -27.845 -18.240 -18.232 +9 +10
7 ig_resnext101_32x8d 54.918 45.082 77.545 77.534 22.455 22.466 88.79 224 0.875 bilinear -27.770 -19.087 -19.103 +23
8 swsl_resnext101_32x4d 53.591 53.603 46.409 46.397 76.339 76.347 23.661 23.653 44.18 224 0.875 bilinear -29.643 -29.627 -20.417 -20.413 +17
9 tf_efficientnet_l2_ns_475 51.487 51.494 48.513 48.506 73.930 73.928 26.070 26.072 480.31 475 0.936 bicubic -36.747 -36.740 -24.616 -24.618 -6
10 swsl_resnext50_32x4d 50.449 50.437 49.551 49.563 73.358 73.368 26.642 26.633 25.03 224 0.875 bilinear -31.731 -31.745 -22.870 -22.862 +24
11 swsl_resnet50 49.551 49.541 50.449 50.459 72.332 72.334 27.668 27.666 25.56 224 0.875 bilinear -31.629 -31.625 -23.654 -23.638 +38
12 tf_efficientnet_b7_ns 47.800 52.200 69.638 69.640 30.362 30.360 66.35 600 0.949 bicubic -39.038 -39.040 -28.456 -28.454 -8
13 tf_efficientnet_b6_ns 47.751 47.761 52.249 52.239 69.962 69.968 30.038 30.032 43.04 528 0.942 bicubic -38.711 -38.691 -27.922 -27.914 -8
14 tf_efficientnet_l2_ns 47.570 52.430 70.017 70.019 29.983 29.981 480.31 800 0.960 bicubic -40.782 -28.631 -12
15 tf_efficientnet_b8_ap 45.778 45.774 54.222 54.226 67.905 67.911 32.095 32.089 87.41 672 0.954 bicubic -39.590 -39.596 -29.389 -29.383 -6
16 tf_efficientnet_b5_ns 45.607 45.615 54.393 54.385 67.852 67.842 32.148 32.158 30.39 456 0.934 bicubic -40.473 -29.902 -29.910 -10
17 tf_efficientnet_b4_ns 43.455 43.450 56.545 56.550 65.513 65.519 34.487 34.481 19.34 380 0.922 bicubic -41.703 -41.713 -31.955 -31.951 -7
18 tf_efficientnet_b8 42.502 42.508 57.498 57.492 64.874 64.857 35.126 35.143 87.41 672 0.954 bicubic -42.868 -42.862 -32.518 -32.533 -10
19 tf_efficientnet_b7 41.437 41.431 58.563 58.569 63.027 63.017 36.973 36.983 66.35 600 0.949 bicubic -43.495 -43.505 -34.181 -34.186 -6
20 tf_efficientnet_b7_ap 41.433 41.429 58.567 58.571 62.876 62.874 37.124 37.126 66.35 600 0.949 bicubic -43.685 -43.691 -34.376 -34.378 -9
21 tf_efficientnet_b5_ap 41.420 41.418 58.580 58.582 62.082 62.084 37.918 37.916 30.39 456 0.934 bicubic -42.834 -34.894 -34.890 -5 -4
22 tf_efficientnet_b6_ap 41.091 41.099 58.909 58.901 62.359 62.355 37.641 37.645 43.04 528 0.942 bicubic -43.695 -43.689 -34.779 -34.783 -8
23 tf_efficientnet_b4_ap 40.476 40.484 59.524 59.516 61.713 61.723 38.287 38.277 19.34 380 0.922 bicubic -42.772 -42.764 -34.675 -34.669 +1
24 tf_efficientnet_b3_ns 39.582 39.584 60.418 60.416 61.463 61.453 38.537 38.547 12.23 300 0.904 bicubic -44.472 -44.464 -35.449 -35.457 -4
25 tf_efficientnet_b5 38.328 38.356 61.672 61.644 59.928 59.913 40.072 40.087 30.39 456 0.934 bicubic -45.488 -45.456 -36.822 -36.835 -3
26 tf_efficientnet_b3_ap resnest269e 37.061 37.315 62.939 62.685 57.236 57.468 42.764 42.532 12.23 110.93 300 416 0.904 0.928 bicubic -44.767 -47.203 -38.388 -39.518 +13 -11
27 resnest269e tf_efficientnet_b3_ap 36.670 37.055 63.330 62.945 56.810 57.240 43.190 42.760 110.93 12.23 416 300 0.875 0.904 bilinear bicubic -47.516 -44.767 -40.112 -38.384 -10 +12
28 tf_efficientnet_b2_ns 36.177 36.183 63.823 63.817 57.555 57.551 42.445 42.449 9.11 260 0.890 bicubic -46.203 -46.197 -38.697 +4
29 ecaresnet101d 36.006 36.004 63.994 63.996 56.154 56.165 43.846 43.835 44.57 224 0.875 bicubic -46.160 -46.168 -39.898 -39.881 +6
30 swsl_resnet18 resnest200e 35.860 35.931 64.140 64.069 58.437 55.849 41.563 44.151 11.69 70.20 224 320 0.875 0.909 bilinear bicubic -37.426 -47.901 -33.295 -41.045 +192 -9
31 resnest200e swsl_resnet18 35.847 35.858 64.153 64.142 55.890 58.455 44.110 41.545 70.20 11.69 320 224 0.875 bilinear -47.987 -37.418 -40.948 -33.279 -10 +195
32 resnest101e 35.365 35.373 64.635 64.627 55.786 55.780 44.214 44.220 48.28 256 0.875 bilinear -47.525 -47.517 -40.538 -40.540 -4
33 ssl_resnext101_32x16d 34.609 34.603 65.391 65.397 55.914 55.931 44.086 44.069 194.03 224 0.875 bilinear -47.227 -47.241 -40.180 -40.165 +5
34 resnest50d_4s2x40d 34.361 34.355 65.639 65.645 54.711 54.725 45.289 45.275 30.42 224 0.875 bicubic -46.753 -40.857 -40.833 +16
35 tf_efficientnet_b1_ns 34.153 34.157 65.847 65.843 55.489 44.511 7.79 240 0.882 bicubic -47.233 -47.231 -40.249 +11 +12
36 tf_efficientnet_b4 34.062 34.064 65.938 65.936 54.216 54.198 45.784 45.802 19.34 380 0.922 bicubic -48.954 -48.958 -42.082 -42.102 -9
37 ssl_resnext101_32x8d 34.021 34.017 65.979 65.983 55.593 55.601 44.407 44.399 88.79 224 0.875 bilinear -47.605 -47.599 -40.445 -40.437 +5 +6
38 tf_efficientnet_b6 34.005 33.998 65.995 66.002 54.540 54.544 45.460 45.456 43.04 528 0.942 bicubic -50.107 -50.112 -42.344 -42.342 -19
39 efficientnet_b3_pruned 33.996 66.004 54.110 54.108 45.890 45.892 9.86 300 0.904 bicubic -46.860 -46.862 -41.130 -41.134 +18
40 tresnet_xl 33.259 33.257 66.741 66.743 52.296 52.294 47.704 47.706 78.44 224 0.875 bilinear -48.811 -48.797 -43.632 -43.642 -4
41 resnest50d_1s4x24d 33.139 33.147 66.861 66.853 52.831 52.839 47.169 47.161 25.68 224 0.875 bicubic -47.851 -47.841 -42.491 -42.483 +11
42 resnest50d rexnet_200 32.968 32.987 67.032 67.013 52.701 52.939 47.299 47.061 27.48 16.37 224 0.875 bilinear bicubic -47.990 -48.645 -42.681 -42.729 +11 0
43 tf_efficientnet_b3 resnest50d 32.864 32.972 67.136 67.028 52.962 52.713 47.038 47.287 12.23 27.48 300 224 0.904 0.875 bicubic bilinear -48.776 -48.002 -42.760 -42.665 -2 +10
44 inception_resnet_v2 tf_efficientnet_b3 32.736 32.860 67.264 67.140 50.640 52.950 49.360 47.050 55.84 12.23 299 300 0.897 0.904 bicubic -47.724 -48.776 -44.670 -42.767 +22 -3
45 gluon_resnet152_v1d pnasnet5large 32.730 32.848 67.270 67.152 51.084 50.500 48.916 49.500 60.21 86.06 224 331 0.875 0.911 bicubic -47.740 -49.934 -44.122 -45.540 +20 -16
46 tf_efficientnet_b2_ap nasnetalarge 32.679 32.775 67.321 67.225 52.233 50.141 47.767 49.859 9.11 88.75 260 331 0.890 0.911 bicubic -47.627 -49.845 -42.795 -45.906 +28 -15
47 nasnetalarge inception_resnet_v2 32.583 32.738 67.417 67.262 49.787 50.648 50.213 49.352 88.75 55.84 331 299 0.875 0.897 bicubic -49.975 -47.720 -46.249 -44.658 -16 +20
48 tresnet_l gluon_resnet152_v1d 32.567 32.734 67.433 67.266 51.141 51.088 48.859 48.912 55.99 60.21 224 0.875 bilinear bicubic -48.921 -47.740 -44.487 -44.118 -3 +17
49 pnasnet5large tf_efficientnet_b2_ap 32.532 32.681 67.468 67.319 50.188 52.239 49.812 47.761 86.06 9.11 331 260 0.875 0.890 bicubic -50.208 -47.619 -45.852 -42.789 -20 +27
50 ens_adv_inception_resnet_v2 tresnet_l 32.370 32.559 67.629 67.441 50.427 51.139 49.573 48.861 55.84 55.99 299 224 0.897 0.875 bicubic bilinear -47.606 -48.929 -44.519 -44.485 +34 -4
51 gluon_resnet152_v1s ens_adv_inception_resnet_v2 32.331 32.370 67.669 67.629 50.539 50.427 49.461 49.573 60.32 55.84 224 299 0.875 0.897 bicubic -48.681 -47.611 -44.877 -44.509 = +36
52 gluon_seresnext101_64x4d gluon_resnet152_v1s 32.194 32.331 67.806 67.669 50.327 50.526 49.673 49.474 88.23 60.32 224 0.875 bicubic -48.696 -48.685 -44.977 -44.886 +4 -1
53 gluon_seresnext101_32x4d gluon_seresnext101_64x4d 32.115 32.205 67.885 67.795 51.241 50.319 48.759 49.681 48.96 88.23 224 0.875 bicubic -48.787 -48.689 -44.053 -44.989 +2 +3
54 efficientnet_b3a gluon_seresnext101_32x4d 31.728 32.107 68.272 67.893 51.322 51.237 48.678 48.763 12.23 48.96 320 224 1.000 0.875 bicubic -50.146 -48.797 -44.518 -44.057 -17 +1
55 efficientnet_b3 cspresnext50 31.565 31.822 68.435 68.178 51.272 51.602 48.728 48.398 12.23 20.57 300 224 0.904 0.875 bicubic bilinear -49.933 -48.218 -44.446 -43.342 -11 +30
56 resnet50 efficientnet_b3a 31.545 31.732 68.455 68.268 50.172 51.325 49.828 48.675 25.56 12.23 224 320 0.875 1.000 bicubic -47.487 -50.134 -44.212 -44.511 +64 -19
57 ssl_resnext101_32x4d efficientnet_b3 31.433 31.555 68.567 68.445 52.115 51.276 47.885 48.724 44.18 12.23 224 300 0.875 0.904 bilinear bicubic -49.495 -49.939 -43.613 -44.440 -3 -12
58 inception_v4 resnet50 31.382 31.547 68.618 68.453 49.237 50.170 50.763 49.830 42.68 25.56 299 224 0.875 bicubic -48.774 -47.491 -45.737 -44.220 +22 +68
59 ecaresnetlight ssl_resnext101_32x4d 31.133 31.423 68.868 68.577 50.252 52.121 49.748 47.879 30.16 44.18 224 0.875 bicubic bilinear -49.321 -49.501 -45.004 -43.607 +8 -5
60 gluon_resnet101_v1s inception_v4 31.113 31.378 68.887 68.622 49.791 49.244 50.209 50.756 44.67 42.68 224 299 0.875 bicubic -49.187 -48.790 -45.359 -45.724 +15 +20
61 tf_efficientnet_cc_b0_8e rexnet_150 31.081 31.366 68.919 68.634 50.773 51.288 49.227 48.712 24.01 9.73 224 0.875 bicubic -46.827 -48.944 -42.883 -43.878 +98 +13
62 ecaresnet50d ecaresnetlight 31.064 31.121 68.936 68.879 50.846 50.243 49.154 49.757 25.58 30.16 224 0.875 bicubic -49.540 -49.341 -44.476 -45.007 = +4
63 gluon_resnet152_v1c gluon_resnet101_v1s 31.007 31.115 68.993 68.885 48.936 49.793 51.064 50.207 60.21 44.67 224 0.875 bicubic -48.909 -49.187 -45.906 -45.367 +23 +12
64 tresnet_m tf_efficientnet_cc_b0_8e 30.993 31.087 69.007 68.913 48.690 50.761 51.310 49.239 31.39 24.01 224 0.875 bilinear bicubic -49.803 -46.821 -46.166 -42.892 -4 +100
65 gluon_resnext101_64x4d ecaresnet50d 30.981 31.058 69.019 68.942 48.553 50.848 51.447 49.152 83.46 25.58 224 0.875 bicubic -49.621 -49.534 -46.441 -44.472 -2
66 tf_efficientnet_cc_b1_8e cspdarknet53 30.901 31.018 69.099 68.981 50.074 50.390 49.926 49.610 39.72 27.64 240 256 0.882 0.887 bicubic bilinear -48.397 -49.040 -44.290 -44.694 +42 +18
67 ecaresnet101d_pruned tresnet_m 30.895 30.997 69.105 69.003 50.001 48.682 49.999 51.318 24.88 31.39 224 0.875 bicubic bilinear -49.913 -49.805 -45.627 -46.178 -8 -7
68 gluon_resnext101_32x4d gluon_resnet152_v1c 30.881 30.991 69.119 69.009 48.537 48.924 51.463 51.076 44.18 60.21 224 0.875 bicubic -49.453 -48.919 -46.389 -45.916 +4 +22
69 tf_efficientnet_lite4 gluon_resnext101_64x4d 30.840 30.987 69.160 69.013 50.398 48.549 49.602 51.451 13.01 83.46 380 224 0.920 0.875 bilinear bicubic -50.688 -49.617 -45.270 -46.439 -26 -7
70 dpn107 tf_efficientnet_cc_b1_8e 30.680 30.899 69.320 69.101 48.806 50.080 51.194 49.920 86.92 39.72 224 240 0.875 0.882 bicubic -49.484 -48.409 -46.106 -44.290 +9 +42
71 ese_vovnet39b ecaresnet101d_pruned 30.677 30.897 69.323 69.103 49.893 50.013 50.107 49.987 24.57 24.88 224 0.875 bicubic -48.643 -49.921 -44.817 -45.615 +33 -13
72 tresnet_xl_448 gluon_resnext101_32x4d 30.620 30.877 69.380 69.123 49.072 48.537 50.928 51.463 78.44 44.18 448 224 0.875 bilinear bicubic -52.428 -49.457 -47.102 -46.389 -46 0
73 gluon_resnet152_v1b tf_efficientnet_lite4 30.618 30.830 69.382 69.170 48.529 50.386 51.471 49.614 60.19 13.01 224 380 0.875 0.920 bicubic bilinear -49.074 -50.706 -46.209 -45.282 +22 -29
74 ssl_resnext50_32x4d dpn107 30.594 30.678 69.406 69.322 50.653 48.810 49.347 51.190 25.03 86.92 224 0.875 bilinear bicubic -49.734 -49.478 -44.751 -46.100 -1 +7
75 gluon_resnet101_v1d ese_vovnet39b 30.509 30.657 69.490 69.343 47.975 49.875 52.025 50.125 44.57 24.57 224 0.875 bicubic -49.915 -48.663 -47.045 -44.837 -6 +35
76 resnest26d gluon_resnet152_v1b 30.500 30.623 69.500 69.376 50.677 48.521 49.323 51.479 17.07 60.19 224 0.875 bilinear bicubic -47.982 -49.063 -43.613 -46.215 +62 +24
77 efficientnet_b2a tresnet_xl_448 30.423 30.614 69.577 69.386 49.675 49.069 50.325 50.931 9.11 78.44 288 448 1.000 0.875 bicubic bilinear -50.185 -52.436 -45.635 -47.104 -16 -51
78 tf_efficientnet_b1_ap ssl_resnext50_32x4d 30.419 30.594 69.581 69.406 49.553 50.657 50.447 49.343 7.79 25.03 240 224 0.882 0.875 bicubic bilinear -48.859 -49.724 -44.755 -44.749 +32 -5
79 dpn98 gluon_resnet101_v1d 30.058 30.523 69.942 69.477 48.240 47.950 51.760 52.050 61.57 44.57 224 0.875 bicubic -49.578 -49.891 -46.354 -47.064 +18 -10
80 tf_efficientnet_b2 dpn68b 30.020 30.517 69.980 69.483 49.590 49.158 50.410 50.842 9.11 12.61 260 224 0.890 0.875 bicubic -50.070 -48.699 -45.316 -45.256 +2 +39
81 dpn131 resnest26d 30.014 30.490 69.986 69.510 48.144 50.677 51.856 49.323 79.25 17.07 224 0.875 bicubic bilinear -49.814 -47.988 -46.560 -43.621 +9 +63
82 senet154 efficientnet_b2a 30.001 30.435 69.999 69.565 48.032 49.698 51.968 50.302 115.09 9.11 224 288 0.875 1.000 bilinear bicubic -51.303 -50.177 -47.466 -45.620 -35 -21
83 dpn92 tf_efficientnet_b1_ap 29.969 30.421 70.031 69.579 49.160 49.553 50.840 50.447 37.67 7.79 224 240 0.875 0.882 bicubic -50.047 -48.859 -45.678 -44.753 = +33
84 gluon_senet154 seresnet50 29.887 30.077 70.113 69.923 47.873 49.292 52.127 50.708 115.09 28.09 224 0.875 bicubic -51.337 -50.197 -47.483 -45.778 -36 -6
85 xception dpn98 29.849 30.067 70.151 69.933 48.690 48.244 51.310 51.756 22.86 61.57 299 224 0.897 0.875 bicubic -49.199 -49.575 -45.702 -46.354 +34 +17
86 adv_inception_v3 tf_efficientnet_b2 29.824 30.026 70.176 69.974 47.867 49.581 52.133 50.419 23.83 9.11 299 260 0.875 0.890 bicubic -47.756 -50.060 -45.857 -45.327 +80 -3
87 resnetblur50 dpn131 29.623 30.024 70.377 69.976 48.250 48.146 51.750 51.854 25.56 79.25 224 0.875 bicubic -49.667 -49.798 -46.382 -46.564 +22 +7
88 efficientnet_b2 dpn92 29.617 29.953 70.383 70.047 48.773 49.162 51.227 50.838 9.11 37.67 260 224 0.875 bicubic -50.785 -50.055 -46.303 -45.674 -18 -2
89 gluon_xception65 gluon_senet154 29.555 29.877 70.445 70.123 47.523 47.894 52.477 52.106 39.92 115.09 299 224 0.875 bicubic -50.049 -51.357 -47.225 -47.454 +9 -41
90 resnext101_32x8d xception 29.435 29.865 70.565 70.135 48.482 48.686 51.518 51.314 88.79 22.86 224 299 0.875 0.897 bilinear bicubic -49.877 -49.187 -46.044 -45.706 +15 +35
91 ssl_resnet50 adv_inception_v3 29.423 29.816 70.577 70.184 49.773 47.847 50.227 52.153 25.56 23.83 224 299 0.875 bilinear bicubic -49.805 -47.766 -45.059 -45.889 +20 +80
92 resnext50_32x4d gluon_xception65 29.328 29.784 70.671 70.216 47.395 47.755 52.605 52.245 25.03 39.92 224 299 0.875 0.903 bicubic -50.434 -49.932 -47.205 -47.105 = +7
93 ecaresnet50d_pruned resnetblur50 29.216 29.625 70.784 70.375 48.458 48.248 51.542 51.752 19.94 25.56 224 0.875 bicubic -50.502 -49.661 -46.432 -46.390 = +22
94 tresnet_l_448 efficientnet_b2 29.167 29.615 70.833 70.385 47.234 48.777 52.766 51.223 55.99 9.11 448 260 0.875 bilinear bicubic -53.101 -50.777 -48.744 -46.299 -61 -24
95 gluon_inception_v3 resnext101_32x8d 29.114 29.439 70.886 70.561 46.943 48.486 53.057 51.514 23.83 88.79 299 224 0.875 bicubic bilinear -49.690 -49.869 -47.437 -46.032 +32 +16
96 hrnet_w64 ssl_resnet50 28.987 29.423 71.013 70.577 47.140 49.781 52.860 50.219 128.06 25.56 224 0.875 bilinear -50.485 -49.799 -47.510 -45.051 +5 +21
97 tf_efficientnet_b0_ns resnext50_32x4d 28.914 29.331 71.086 70.669 49.011 47.397 50.989 52.603 5.29 25.03 224 0.875 bicubic -49.738 -50.438 -45.357 -47.201 +37 -1
98 tf_efficientnet_b1 ecaresnet50d_pruned 28.892 29.215 71.108 70.785 47.511 48.453 52.489 51.547 7.79 19.94 240 224 0.882 0.875 bicubic -49.940 -50.501 -46.685 -46.427 +28 0
99 gluon_resnet101_v1b tresnet_l_448 28.857 29.165 71.143 70.835 46.371 47.232 53.629 52.768 44.55 55.99 224 448 0.875 bicubic bilinear -50.447 -53.103 -48.153 -48.744 +8 -66
100 skresnext50_32x4d gluon_inception_v3 28.818 29.124 71.182 70.876 46.503 46.957 53.497 53.043 27.48 23.83 224 299 0.875 bicubic -51.332 -49.682 -48.141 -47.413 -19 +33
101 tf_efficientnet_lite3 xception71 28.654 29.047 71.346 70.953 47.358 47.405 52.642 52.595 8.20 42.34 300 299 0.904 0.903 bilinear bicubic -51.158 -50.826 -47.556 -47.517 -10 -9
102 hrnet_w40 hrnet_w64 28.645 28.989 71.355 71.011 47.443 47.142 52.557 52.858 57.56 128.06 224 0.875 bilinear -50.289 -50.485 -47.023 -47.510 +20 +5
103 gluon_seresnext50_32x4d tf_efficientnet_b0_ns 28.641 28.902 71.359 71.098 46.450 49.011 53.550 50.989 27.56 5.29 224 0.875 bicubic -51.271 -49.756 -48.368 -45.365 -16 +36
104 skresnet34 xception65 28.629 28.896 71.371 71.104 47.957 47.167 52.043 52.833 22.28 39.92 224 299 0.875 0.903 bicubic -48.281 -50.656 -45.359 -47.487 +81 0
105 resnet152 tf_efficientnet_b1 28.535 28.886 71.465 71.114 47.114 47.503 52.886 52.497 60.19 7.79 224 240 0.875 0.882 bilinear bicubic -49.777 -49.940 -46.932 -46.695 +40 +27
106 hrnet_w48 gluon_resnet101_v1b 28.407 28.878 71.593 71.121 47.574 46.389 52.426 53.611 77.47 44.55 224 0.875 bilinear bicubic -50.903 -50.427 -46.944 -48.135 = +7
107 gluon_resnext50_32x4d skresnext50_32x4d 28.383 28.818 71.617 71.182 45.326 46.497 54.674 53.503 25.03 27.48 224 0.875 bicubic -50.973 -51.338 -49.098 -48.145 -4 -25
108 efficientnet_b2_pruned tf_efficientnet_lite3 28.366 28.660 71.634 71.340 47.059 47.354 52.941 52.646 8.31 8.20 260 300 0.890 0.904 bicubic bilinear -51.552 -51.160 -47.789 -47.560 -23 -13
109 tf_efficientnet_b0_ap gluon_seresnext50_32x4d 28.350 28.651 71.650 71.349 47.531 46.436 52.469 53.564 5.29 27.56 224 0.875 bicubic -48.734 -51.267 -45.723 -48.386 +72 -21
110 dla102x2 skresnet34 28.319 28.645 71.681 71.355 46.757 47.953 53.243 52.047 41.75 22.28 224 0.875 bilinear bicubic -51.133 -48.267 -47.887 -45.369 -8 +78
111 dla169 hrnet_w40 28.311 28.641 71.689 71.359 47.399 47.454 52.601 52.546 53.99 57.56 224 0.875 bilinear -50.399 -50.279 -46.939 -47.016 +19 +17
112 tf_efficientnet_cc_b0_4e resnet152 28.311 28.533 71.689 71.467 47.364 47.118 52.636 52.882 13.31 60.19 224 0.875 bicubic bilinear -48.993 -49.779 -45.968 -46.920 +62 +38
113 mixnet_xl hrnet_w48 28.293 28.413 71.707 71.587 46.717 47.586 53.283 52.414 11.90 77.47 224 0.875 bicubic bilinear -52.185 -50.887 -48.215 -46.926 -49 +1
114 gluon_resnet50_v1d gluon_resnext50_32x4d 28.236 28.375 71.764 71.624 45.876 45.328 54.124 54.672 25.58 25.03 224 0.875 bicubic -50.838 -50.978 -48.600 -49.098 +3 -5
115 wide_resnet101_2 efficientnet_b2_pruned 28.106 28.362 71.894 71.638 46.425 47.051 53.575 52.949 126.89 8.31 224 260 0.875 0.890 bilinear bicubic -50.740 -51.554 -47.859 -47.805 +10 -26
116 gluon_resnet101_v1c tf_efficientnet_b0_ap 28.102 28.346 71.898 71.654 45.953 47.531 54.047 52.469 44.57 5.29 224 0.875 bicubic -51.442 -48.740 -48.633 -45.725 -16 +68
117 densenet161 tf_efficientnet_cc_b0_4e 28.100 28.315 71.900 71.685 46.651 47.364 53.349 52.636 28.68 13.31 224 0.875 bicubic -49.248 -48.991 -46.997 -45.970 +56 +61
118 regnetx_320 dla102x2 28.079 28.313 71.921 71.687 45.120 46.761 54.880 53.239 107.81 41.28 224 0.875 bicubic bilinear -52.167 -51.135 -49.902 -47.879 -41 -10
119 regnety_320 dla169 28.071 28.313 71.929 71.687 45.460 47.391 54.540 52.609 145.05 53.39 224 0.875 bicubic bilinear -52.743 -50.375 -49.780 -46.945 -61 +19
120 dpn68b mixnet_xl 27.884 28.287 72.116 71.713 47.460 46.702 52.540 53.298 12.61 11.90 224 0.875 bicubic -49.630 -52.189 -46.362 -48.234 +48 -56
121 regnetx_160 gluon_resnet50_v1d 27.825 28.246 72.175 71.754 45.631 45.878 54.369 54.122 54.28 25.58 224 0.875 bicubic -52.041 -50.828 -49.197 -48.592 -32 +2
122 tf_inception_v3 wide_resnet101_2 27.786 28.108 72.214 71.892 45.711 46.401 54.289 53.599 23.83 126.89 299 224 0.875 bicubic bilinear -50.070 -50.748 -47.933 -47.881 +38 +9
123 res2net101_26w_4s gluon_resnet101_v1c 27.774 28.104 72.226 71.896 45.171 45.961 54.829 54.039 45.21 44.57 224 0.875 bilinear bicubic -51.422 -51.430 -49.269 -48.617 -8 -18
124 regnety_160 regnetx_320 27.639 28.093 72.361 71.907 45.534 45.126 54.466 54.874 83.59 107.81 224 0.875 bicubic -52.661 -52.154 -49.428 -49.900 -48 -45
125 hrnet_w44 densenet161 27.625 28.081 72.375 71.919 45.831 46.641 54.169 53.359 67.06 28.68 224 0.875 bilinear bicubic -51.269 -49.277 -48.539 -46.997 -2 +52
126 inception_v3 regnety_320 27.570 28.059 72.430 71.941 45.261 45.444 54.739 54.556 23.83 145.05 299 224 0.875 bicubic -49.866 -52.753 -48.215 -49.800 +45 -67
127 regnetx_080 xception41 27.411 27.888 72.589 72.112 45.022 45.890 54.978 54.110 39.57 26.97 224 299 0.875 0.903 bicubic -51.787 -50.628 -49.536 -48.388 -13 +14
128 hrnet_w30 regnetx_160 27.385 27.817 72.615 72.183 46.542 45.617 53.458 54.383 37.71 54.28 224 0.875 bilinear bicubic -50.811 -52.039 -47.678 -49.213 +21 -35
129 hrnet_w32 tf_inception_v3 27.377 27.780 72.623 72.220 45.990 45.721 54.010 54.279 41.23 23.83 224 299 0.875 bilinear bicubic -51.071 -50.078 -48.198 -47.917 +13 +38
130 gluon_resnet50_v1s res2net101_26w_4s 27.326 27.768 72.674 72.232 45.214 45.179 54.786 54.821 25.68 45.21 224 0.875 bicubic bilinear -51.386 -51.430 -49.028 -49.253 -1 -9
131 densenet201 regnety_160 27.261 27.623 72.739 72.377 46.224 45.532 53.776 54.468 20.01 83.59 224 0.875 bicubic -50.029 -52.673 -47.254 -49.430 +45 -54
132 regnety_064 hrnet_w44 27.228 27.621 72.772 72.379 44.851 45.837 55.149 54.163 30.58 67.06 224 0.875 bicubic bilinear -52.484 -51.275 -49.923 -48.531 -38 -3
133 densenetblur121d inception_v3 27.224 27.556 72.776 72.444 46.307 45.263 53.693 54.737 8.00 23.83 224 299 0.875 bicubic -49.352 -49.884 -46.883 -48.213 +57 +42
134 efficientnet_b1_pruned regnetx_080 27.195 27.405 72.805 72.595 45.872 45.002 54.128 54.998 6.33 39.57 240 224 0.882 0.875 bicubic -51.047 -51.789 -47.960 -49.558 +13 -12
135 res2net50_26w_8s hrnet_w30 27.073 27.381 72.927 72.619 44.432 46.554 55.568 53.446 48.40 37.71 224 0.875 bilinear -52.137 -50.825 -49.930 -47.668 -22 +19
136 dla102x hrnet_w32 27.023 27.369 72.977 72.631 45.495 45.994 54.505 54.006 26.77 41.23 224 0.875 bilinear -51.485 -51.081 -48.739 -48.192 = +11
137 resnet101 gluon_resnet50_v1s 26.968 27.326 73.031 72.674 45.236 45.222 54.764 54.778 44.55 25.68 224 0.875 bilinear bicubic -50.406 -51.386 -48.310 -49.016 +35 -2
138 resnext50d_32x4d densenet201 26.874 27.265 73.126 72.735 44.430 46.222 55.570 53.778 25.05 20.01 224 0.875 bicubic -52.800 -50.021 -50.438 -47.256 -42 +41
139 regnetx_120 densenetblur121d 26.864 27.228 73.136 72.772 44.682 46.299 55.318 53.701 46.11 8.00 224 0.875 bicubic -52.726 -49.360 -50.058 -46.893 -40 +55
140 seresnext101_32x4d regnety_064 26.819 27.220 73.181 72.780 43.508 44.847 56.492 55.153 48.96 30.58 224 0.875 bilinear bicubic -53.417 -52.502 -51.520 -49.921 -62 -43
141 densenet169 efficientnet_b1_pruned 26.811 27.181 73.189 72.819 45.375 45.872 54.625 54.128 14.15 6.33 224 240 0.875 0.882 bicubic -49.101 -51.055 -47.649 -47.962 +55 +12
142 regnetx_064 rexnet_130 26.802 27.094 73.198 72.906 44.904 45.933 55.096 54.067 26.21 7.56 224 0.875 bicubic -52.264 -52.406 -49.552 -48.749 -24 -36
143 regnety_120 res2net50_26w_8s 26.782 27.078 73.218 72.921 44.440 44.428 55.560 55.572 51.82 48.40 224 0.875 bicubic bilinear -53.600 -52.120 -50.688 -49.940 -72 -23
144 regnetx_032 dla102x 26.707 27.061 73.293 72.939 45.226 45.475 54.774 54.525 15.30 26.31 224 0.875 bicubic bilinear -51.459 -51.449 -48.854 -48.753 +6 -2
145 densenet121 resnet101 26.676 26.963 73.324 73.037 45.900 45.234 54.100 54.766 7.98 44.55 224 0.875 bicubic bilinear -48.898 -50.411 -46.756 -48.306 +55 +31
146 seresnet152 resnext50d_32x4d 26.672 26.876 73.328 73.124 43.945 44.436 56.055 55.564 66.82 25.05 224 0.875 bilinear bicubic -51.986 -52.800 -50.429 -50.430 -13 -45
147 tf_efficientnet_el regnetx_120 26.623 26.868 73.377 73.132 44.636 44.682 55.364 55.318 10.59 46.11 300 224 0.904 0.875 bicubic -53.825 -52.728 -50.524 -50.056 -79 -44
148 efficientnet_es rexnet_100 26.617 26.831 73.383 73.169 45.106 45.369 54.894 54.631 5.44 4.80 224 0.875 bicubic -51.437 -51.027 -48.824 -48.501 +4 +18
149 res2net50_26w_6s densenet169 26.587 26.829 73.413 73.171 43.978 45.373 56.022 54.627 37.05 14.15 224 0.875 bilinear bicubic -51.987 -49.077 -50.148 -47.653 -14 +51
150 dla60x regnety_120 26.564 26.788 73.436 73.212 45.039 44.454 54.961 55.546 17.65 51.82 224 0.875 bilinear bicubic -51.678 -53.578 -48.983 -50.672 -4 -79
151 regnety_080 regnetx_064 26.515 26.784 73.485 73.216 44.355 44.927 55.645 55.073 39.18 26.21 224 0.875 bicubic -53.353 -52.288 -50.477 -49.531 -63 -27
152 tf_efficientnet_b0 regnetx_032 26.491 26.703 73.509 73.297 45.656 45.236 54.344 54.764 5.29 15.30 224 0.875 bicubic -50.349 -51.469 -47.570 -48.852 +34 +3
153 res2net50_14w_8s densenet121 26.471 26.664 73.529 73.336 44.369 45.900 55.631 54.100 25.06 7.98 224 0.875 bilinear bicubic -51.681 -48.914 -49.473 -46.752 -2 +51
154 gluon_resnet50_v1b tf_efficientnet_el 26.432 26.623 73.568 73.377 44.033 44.648 55.967 55.352 25.56 10.59 224 300 0.875 0.904 bicubic -51.146 -53.817 -49.685 -50.516 +13 -86
155 regnetx_040 efficientnet_es 26.239 26.621 73.760 73.379 44.424 45.112 55.576 54.888 22.12 5.44 224 0.875 bicubic -52.247 -51.445 -49.818 -48.814 -18 +2
156 dpn68 res2net50_26w_6s 26.122 26.595 73.878 73.405 44.233 43.990 55.767 56.010 12.61 37.05 224 0.875 bicubic bilinear -50.184 -51.975 -48.737 -50.134 +37 -16
157 hrnet_w18 dla60x 25.976 26.552 74.024 73.448 44.809 45.023 55.191 54.977 21.30 17.35 224 0.875 bilinear -50.780 -51.694 -48.633 -48.994 +30 -6
158 regnety_040 regnety_080 25.913 26.524 74.087 73.476 43.854 44.359 56.146 55.641 20.65 39.18 224 0.875 bicubic -53.309 -53.352 -50.802 -50.471 -46 -67
159 resnet34 tf_efficientnet_b0 25.884 26.485 74.116 73.515 43.990 45.646 56.010 54.354 21.80 5.29 224 0.875 bilinear bicubic -49.228 -50.363 -48.298 -47.582 +49 +30
160 res2net50_26w_4s res2net50_14w_8s 25.870 26.483 74.130 73.517 43.161 44.371 56.839 55.629 25.70 25.06 224 0.875 bilinear -52.076 -51.667 -50.691 -49.477 -2 -4
161 tresnet_m_448 gluon_resnet50_v1b 25.850 26.436 74.150 73.564 42.868 44.035 57.132 55.965 31.39 25.56 448 224 0.875 bilinear bicubic -55.862 -51.144 -52.702 -49.681 -121 +11
162 gluon_resnet50_v1c regnetx_040 25.795 26.243 74.205 73.757 43.017 44.438 56.983 55.562 25.58 22.12 224 0.875 bicubic -52.215 -52.239 -50.971 -49.806 -8 -19
163 selecsls60 dpn68 25.729 26.129 74.272 73.871 44.069 44.228 55.931 55.772 30.67 12.61 224 0.875 bicubic -52.253 -50.189 -49.763 -48.750 -6 +33
164 dla60_res2net hrnet_w18 25.642 25.986 74.358 74.014 43.589 44.813 56.411 55.187 21.15 21.30 224 0.875 bilinear -52.830 -50.772 -50.615 -48.631 -25 +27
165 dla60_res2next regnety_040 25.638 25.923 74.362 74.077 43.670 43.848 56.330 56.152 17.33 20.65 224 0.875 bilinear bicubic -52.810 -53.297 -50.474 -50.808 -24 -47
166 tf_efficientnet_lite1 resnet34 25.506 25.888 74.493 74.112 43.583 43.982 56.417 56.018 5.42 21.80 240 224 0.882 0.875 bicubic bilinear -51.132 -49.222 -49.649 -48.302 +23 +47
167 mixnet_l res2net50_26w_4s 25.499 25.866 74.501 74.134 43.463 43.155 56.537 56.845 7.33 25.70 224 0.875 bicubic bilinear -53.477 -52.098 -50.721 -50.699 -46 -4
168 efficientnet_b1 tresnet_m_448 25.483 25.852 74.517 74.148 43.286 42.874 56.714 57.126 7.79 31.39 240 448 0.875 bicubic bilinear -53.215 -55.862 -50.866 -52.698 -37 -128
169 tv_resnext50_32x4d gluon_resnet50_v1c 25.469 25.784 74.531 74.216 42.791 43.031 57.209 56.969 25.03 25.58 224 0.875 bilinear bicubic -52.149 -52.228 -50.907 -50.957 -5 -10
170 tf_mixnet_l selecsls60 25.420 25.729 74.580 74.272 42.544 44.065 57.456 55.935 7.33 30.67 224 0.875 bicubic -53.350 -52.254 -51.460 -49.763 -42 -8
171 res2next50 dla60_res2net 25.395 25.652 74.606 74.348 42.492 43.599 57.508 56.401 24.67 20.85 224 0.875 bilinear -52.847 -52.812 -51.400 -50.607 -23 -25
172 selecsls60b dla60_res2next 25.328 25.640 74.672 74.360 43.554 43.670 56.446 56.330 32.77 17.03 224 0.875 bicubic bilinear -53.090 -52.800 -50.612 -50.482 -29 -24
173 seresnet101 mixnet_l 25.328 25.512 74.672 74.488 42.828 43.455 57.172 56.545 49.33 7.33 224 0.875 bilinear bicubic -53.068 -53.464 -51.430 -50.727 -29 -46
174 regnety_032 tf_efficientnet_lite1 25.324 25.499 74.676 74.501 42.907 43.585 57.093 56.415 19.44 5.42 224 240 0.875 0.882 bicubic -53.546 -51.143 -51.495 -49.641 -50 +19
175 dla102 efficientnet_b1 25.314 25.469 74.686 74.531 43.837 43.284 56.163 56.716 33.73 7.79 224 240 0.875 bilinear bicubic -52.712 -53.229 -50.113 -50.860 -22 -38
176 wide_resnet50_2 tv_resnext50_32x4d 25.310 25.455 74.690 74.545 42.178 42.787 57.822 57.213 68.88 25.03 224 0.875 bilinear -53.158 -52.165 -51.908 -50.909 -36 -7
177 resnest14d tf_mixnet_l 25.282 25.422 74.718 74.578 44.121 42.534 55.879 57.466 10.61 7.33 224 0.875 bilinear bicubic -50.222 -53.352 -48.393 -51.464 +25 -43
178 seresnext50_32x4d res2next50 25.218 25.389 74.782 74.611 41.938 42.508 58.062 57.492 27.56 24.67 224 0.875 bilinear -53.858 -52.857 -52.496 -51.384 -62 -26
179 res2net50_48w_2s regnety_032 25.023 25.332 74.977 74.668 42.202 42.911 57.798 57.089 25.29 19.44 224 0.875 bilinear bicubic -52.491 -53.554 -51.346 -51.501 -10 -49
180 efficientnet_b0 selecsls60b 25.015 25.332 74.985 74.668 42.785 43.559 57.215 56.441 5.29 32.77 224 0.875 bicubic -52.677 -53.080 -50.747 -50.614 -18 -31
181 gluon_resnet34_v1b dla102 24.948 25.316 75.052 74.684 42.237 43.827 57.763 56.173 21.80 33.27 224 0.875 bicubic bilinear -49.632 -52.716 -49.751 -50.119 +35 -23
182 mobilenetv2_120d wide_resnet50_2 24.933 25.308 75.067 74.692 43.064 42.178 56.936 57.822 5.83 68.88 224 0.875 bicubic bilinear -52.361 -53.170 -50.438 -51.916 -7 -37
183 dla60 resnest14d 24.927 25.284 75.073 74.716 43.302 44.114 56.698 55.886 22.33 10.61 224 0.875 bilinear -52.097 -50.222 -50.006 -48.404 -1 +23
184 regnety_016 res2net50_48w_2s 24.819 25.027 75.181 74.973 42.626 42.208 57.374 57.792 11.20 25.29 224 0.875 bicubic bilinear -53.033 -52.495 -51.090 -51.346 -23 -11
185 tf_efficientnet_em efficientnet_b0 24.534 25.015 75.466 74.985 42.410 42.787 57.590 57.213 6.90 5.29 240 224 0.882 0.875 bicubic -54.164 -52.683 -51.910 -50.745 -53 -17
186 tf_efficientnet_lite2 gluon_resnet34_v1b 24.530 24.939 75.470 75.061 42.292 42.243 57.708 57.757 6.09 21.80 260 224 0.890 0.875 bicubic -52.930 -49.649 -51.454 -49.747 -16 +34
187 skresnet18 mobilenetv2_120d 24.494 24.937 75.505 75.063 42.538 43.058 57.462 56.942 11.96 5.83 224 0.875 bicubic -48.550 -52.347 -48.640 -50.434 +36 -7
188 regnetx_016 dla60 24.477 24.933 75.523 75.067 42.502 43.296 57.498 56.704 9.19 22.04 224 0.875 bicubic bilinear -52.453 -52.099 -50.916 -50.022 -4 -3
189 tf_efficientnet_lite0 regnety_016 24.371 24.811 75.629 75.189 42.510 42.616 57.490 57.384 4.65 11.20 224 0.875 bicubic -50.471 -53.051 -49.660 -51.104 +22 -24
190 tv_resnet50 tf_efficientnet_em 24.092 24.542 75.908 75.458 41.309 42.412 58.691 57.588 25.56 6.90 224 240 0.875 0.882 bilinear bicubic -52.038 -54.166 -51.553 -51.902 +4 -54
191 seresnet34 tf_efficientnet_lite2 24.037 24.530 75.963 75.470 41.895 42.280 58.105 57.720 21.96 6.09 224 260 0.875 0.890 bilinear bicubic -50.771 -52.938 -50.231 -51.474 +21 -17
192 tv_densenet121 skresnet18 23.846 24.483 76.154 75.517 41.921 42.536 58.079 57.464 7.98 11.96 224 0.875 bicubic -50.906 -48.555 -50.231 -48.632 +21 +35
193 tf_efficientnet_es regnetx_016 23.824 24.473 76.176 75.527 41.319 42.514 58.681 57.486 5.44 9.19 224 0.875 bicubic -53.440 -52.477 -52.281 -50.906 -16 -7
194 mobilenetv2_140 tf_efficientnet_lite0 23.710 24.373 76.290 75.627 41.469 42.487 58.531 57.513 6.11 4.65 224 0.875 bicubic -52.814 -50.457 -51.521 -49.689 -3 +22
195 mixnet_m tv_resnet50 23.709 24.070 76.291 75.930 41.139 41.313 58.861 58.687 5.01 25.56 224 0.875 bicubic bilinear -53.547 -52.068 -52.279 -51.551 -17 +3
196 dla34 efficientnet_lite0 23.677 23.909 76.323 76.091 41.543 42.088 58.457 57.912 15.78 4.65 224 0.875 bilinear bicubic -50.959 -51.575 -50.521 -50.422 +19 +11
197 seresnet50 tv_densenet121 23.644 23.844 76.356 76.156 40.081 41.925 59.919 58.075 28.09 7.98 224 0.875 bilinear bicubic -53.992 -50.894 -53.671 -50.225 -34 +20
198 tf_mixnet_m tf_efficientnet_es 23.479 23.819 76.521 76.181 41.005 41.331 58.995 58.669 5.01 5.44 224 0.875 bicubic -53.471 -53.439 -52.151 -52.263 -15 -16
199 tv_resnet34 mobilenetv2_140 23.473 23.712 76.527 76.288 41.367 41.477 58.633 58.523 21.80 6.11 224 0.875 bilinear bicubic -49.841 -52.804 -50.053 -51.520 +22 -4
200 selecsls42b mixnet_m 23.366 23.710 76.633 76.290 40.677 41.141 59.323 58.859 32.46 5.01 224 0.875 bicubic -53.810 -53.550 -52.715 -52.283 -21 -19
201 mobilenetv2_110d dla34 23.070 23.669 76.930 76.331 40.744 41.551 59.256 58.449 4.52 15.74 224 0.875 bicubic bilinear -51.982 -50.961 -51.436 -50.527 +8 +18
202 mobilenetv3_large_100 ese_vovnet19b_dw 22.665 23.535 77.335 76.465 40.785 41.288 59.215 58.712 5.48 6.54 224 0.875 bicubic -53.103 -53.263 -51.755 -51.980 -5 -12
203 mobilenetv3_rw tf_mixnet_m 22.626 23.484 77.374 76.516 40.370 40.989 59.630 59.011 5.48 5.01 224 0.875 bicubic -53.002 -53.458 -52.340 -52.163 -4 -16
204 tf_mobilenetv3_large_100 tv_resnet34 22.571 23.473 77.429 76.527 39.759 41.367 60.241 58.633 5.48 21.80 224 0.875 bilinear -52.945 -49.839 -52.841 -50.059 -3 +21
205 hrnet_w18_small_v2 selecsls42b 22.341 23.357 77.659 76.643 39.847 40.677 60.153 59.323 15.60 32.46 224 0.875 bilinear bicubic -52.785 -53.817 -52.569 -52.713 +1 -22
206 regnety_008 mobilenetv2_110d 22.113 23.066 77.887 76.934 38.896 40.716 61.104 59.284 6.26 4.52 224 0.875 bicubic -54.201 -51.970 -54.166 -51.470 -14 +9
207 seresnext26tn_32x4d mobilenetv3_large_100 22.003 22.655 77.997 77.345 38.492 40.781 61.508 59.219 16.81 5.48 224 0.875 bicubic -55.987 -53.111 -55.256 -51.761 -52 -6
208 seresnext26t_32x4d mobilenetv3_rw 21.987 22.630 78.013 77.370 38.566 40.374 61.434 59.626 16.82 5.48 224 0.875 bicubic -56.001 -53.004 -55.140 -52.334 -52 -5
209 regnety_006 tf_mobilenetv3_large_100 21.973 22.569 78.027 77.431 38.953 39.767 61.047 60.233 6.06 5.48 224 0.875 bicubic bilinear -53.287 -52.949 -53.575 -52.839 -4
210 regnetx_008 hrnet_w18_small_v2 21.952 22.337 78.048 77.663 38.930 39.861 61.070 60.139 7.26 15.60 224 0.875 bicubic bilinear -53.070 -52.777 -53.414 -52.555 = +2
211 resnet26d regnety_008 21.914 22.119 78.086 77.881 38.617 38.900 61.383 61.100 16.01 6.26 224 0.875 bicubic -54.766 -54.197 -54.549 -54.166 -23 -14
212 semnasnet_100 seresnext26tn_32x4d 21.897 21.991 78.103 78.009 38.604 38.482 61.396 61.518 3.89 16.81 224 0.875 bicubic -53.559 -55.995 -53.988 -55.264 -9 -51
213 regnetx_006 seresnext26t_32x4d 21.743 21.985 78.257 78.015 38.904 38.570 61.096 61.430 6.20 16.82 224 0.875 bicubic -52.119 -56.013 -52.776 -55.138 +6 -53
214 gluon_resnet18_v1b regnety_006 21.545 21.971 78.455 78.029 38.873 38.955 61.127 61.045 11.69 6.06 224 0.875 bicubic -49.285 -53.275 -50.883 -53.577 +16 -4
215 fbnetc_100 regnetx_008 21.492 21.940 78.508 78.060 38.165 38.928 61.835 61.072 5.57 7.26 224 0.875 bilinear bicubic -53.628 -53.098 -54.221 -53.408 -8 -1
216 mnasnet_100 resnet26d 21.350 21.907 78.650 78.094 37.715 38.619 62.285 61.381 4.38 16.01 224 0.875 bicubic -53.306 -54.789 -54.411 -54.531 -2 -24
217 resnet26 semnasnet_100 21.295 21.903 78.705 78.097 38.016 38.600 61.984 61.400 16.00 3.89 224 0.875 bicubic -53.997 -53.545 -54.554 -54.004 -13 -9
218 ssl_resnet18 regnetx_006 21.278 21.738 78.722 78.263 39.114 38.904 60.886 61.096 11.69 6.20 224 0.875 bilinear bicubic -51.322 -52.115 -52.302 -52.768 +7 +5
219 mixnet_s gluon_resnet18_v1b 21.258 21.549 78.742 78.451 38.193 38.869 61.807 61.131 4.13 11.69 224 0.875 bicubic -54.730 -49.287 -54.601 -50.893 -24 +14
220 seresnext26d_32x4d fbnetc_100 21.254 21.484 78.746 78.516 37.285 38.161 62.715 61.839 16.81 5.57 224 0.875 bicubic bilinear -56.350 -53.640 -56.327 -54.225 -55 -9
221 seresnext26_32x4d mnasnet_100 21.093 21.350 78.907 78.650 37.639 37.719 62.361 62.281 16.79 4.38 224 0.875 bicubic -56.007 -53.308 -55.671 -54.395 -41 -3
222 regnetx_004 resnet26 20.887 21.295 79.113 78.705 37.548 38.018 62.452 61.982 5.16 16.00 224 0.875 bicubic -51.519 -53.997 -53.282 -54.552 +4 -13
223 spnasnet_100 ssl_resnet18 20.867 21.278 79.133 78.722 37.892 39.113 62.108 60.887 4.42 11.69 224 0.875 bilinear -53.213 -51.332 -53.940 -52.303 -6 +6
224 seresnet18 mixnet_s 20.840 21.254 79.160 78.746 37.645 38.187 62.355 61.813 11.78 4.13 224 0.875 bicubic -50.918 -54.738 -52.689 -54.609 +5 -25
225 mobilenetv2_100 seresnext26d_32x4d 20.761 21.252 79.239 78.748 37.751 37.311 62.249 62.689 3.50 16.81 224 0.875 bicubic -52.217 -56.350 -53.265 -56.297 -1 -55
226 tf_mixnet_s regnetx_004 20.478 20.898 79.522 79.102 36.627 37.566 63.373 62.434 4.13 5.16 224 0.875 bicubic -55.170 -51.498 -56.009 -53.264 -28 +4
227 regnety_004 spnasnet_100 20.417 20.863 79.583 79.137 37.030 37.896 62.970 62.104 4.34 4.42 224 0.875 bicubic bilinear -53.609 -53.221 -54.718 -53.922 -9 -6
228 tf_mobilenetv3_large_075 mobilenetv2_100 20.372 20.773 79.628 79.227 36.770 37.759 63.230 62.241 3.99 3.50 224 0.875 bilinear bicubic -53.070 -52.197 -54.582 -53.257 -8 0
229 hrnet_w18_small tf_mixnet_s 20.366 20.470 79.634 79.530 37.094 36.607 62.906 63.393 13.19 4.13 224 0.875 bilinear bicubic -51.976 -55.180 -53.578 -56.021 -2 -27
230 resnet18 regnety_004 20.228 20.415 79.772 79.585 37.260 37.002 62.740 62.998 11.69 4.34 224 0.875 bilinear bicubic -49.530 -53.619 -51.818 -54.750 +2 -8
231 tf_mobilenetv3_large_minimal_100 hrnet_w18_small 20.116 20.368 79.884 79.632 36.904 37.093 63.096 62.907 3.92 13.19 224 0.875 bilinear -52.128 -51.974 -53.732 -53.585 -3 0
232 regnety_002 tf_mobilenetv3_large_075 17.460 20.366 82.540 79.634 32.443 36.764 67.557 63.236 3.16 3.99 224 0.875 bicubic bilinear -52.822 -53.072 -57.097 -54.586 -1 -8
233 regnetx_002 resnet18 16.951 20.228 83.049 79.772 32.235 37.261 67.765 62.739 2.68 11.69 224 0.875 bicubic bilinear -51.803 -49.520 -56.313 -51.816 = +2
234 dla60x_c tf_mobilenetv3_large_minimal_100 16.326 20.122 83.674 79.878 31.775 36.908 68.225 63.092 1.34 3.92 224 0.875 bilinear -51.582 -52.126 -56.659 -53.722 +1 -2
235 tf_mobilenetv3_small_100 regnety_002 16.233 17.450 83.767 82.550 31.223 32.431 68.777 67.569 2.54 3.16 224 0.875 bilinear bicubic -51.685 -52.802 -56.439 -57.109 -1
236 tf_mobilenetv3_small_075 regnetx_002 14.940 16.962 85.060 83.038 29.572 32.225 70.428 67.775 2.04 2.68 224 0.875 bilinear bicubic -50.778 -51.800 -56.564 -56.331 +1 0
237 dla46_c dla60x_c 14.661 16.310 85.339 83.690 29.374 31.761 70.626 68.239 1.31 1.32 224 0.875 bilinear -50.217 -51.582 -56.912 -56.665 +1
238 dla46x_c tf_mobilenetv3_small_100 14.380 16.226 85.620 83.775 29.177 31.223 70.823 68.777 1.08 2.54 224 0.875 bilinear -51.600 -51.697 -57.803 -56.441 -2 -1
239 tf_mobilenetv3_small_minimal_100 tf_mobilenetv3_small_075 13.968 14.944 86.032 85.056 27.980 29.572 72.019 70.428 2.04 224 0.875 bilinear -48.930 -50.772 -56.250 -56.558 = +1
240 dla46_c 14.657 85.343 29.380 70.620 1.30 224 0.875 bilinear -50.209 -56.912 +1
241 dla46x_c 14.382 85.618 29.191 70.809 1.07 224 0.875 bilinear -51.588 -57.789 -2
242 tf_mobilenetv3_small_minimal_100 13.964 86.036 27.988 72.012 2.04 224 0.875 bilinear -48.942 -56.242 0
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