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pytorch-image-models/results/results-imagenet.csv

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Add result csv with summary of all pretrained models
5 years ago
model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation
Update results with new models
5 years ago
tf_efficientnet_l2_ns,88.352,11.648,98.648,1.352,480.31,800,0.96,bicubic
Update results with latest NoisyStudent models and SelectiveKernel models
5 years ago
tf_efficientnet_l2_ns_475,88.234,11.766,98.546,1.454,480.31,475,0.936,bicubic
Update results with new models
5 years ago
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
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
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
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,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
gluon_resnet152_v1s,81.012,18.988,95.416,4.584,60.32,224,0.875,bicubic
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
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,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
Update results-all.csv with latest models/weights
5 years ago
gluon_resnext101_32x4d,80.334,19.666,94.926,5.074,44.18,224,0.875,bicubic
Update results with new models
5 years ago
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
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
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
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
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
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
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
res2net50_26w_8s,79.21,20.79,94.362,5.638,48.4,224,0.875,bilinear
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
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
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
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
res2next50,78.242,21.758,93.892,6.108,24.67,224,0.875,bilinear
hrnet_w30,78.196,21.804,94.218,5.782,37.71,224,0.875,bilinear
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
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
gluon_resnet50_v1b,77.578,22.422,93.718,6.282,25.56,224,0.875,bicubic
adv_inception_v3,77.576,22.424,93.724,6.276,23.83,299,0.875,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_v3,77.434,22.566,93.478,6.522,27.16,299,0.875,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
dla60,77.022,22.978,93.308,6.692,22.33,224,0.875,bilinear
tf_mixnet_m,76.95,23.05,93.156,6.844,5.01,224,0.875,bicubic
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
mobilenetv2_140,76.524,23.476,92.99,7.01,6.11,224,0.875,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,75.628,24.372,92.708,7.292,5.48,224,0.875,bicubic
tf_mobilenetv3_large_100,75.516,24.484,92.6,7.4,5.48,224,0.875,bilinear
semnasnet_100,75.456,24.544,92.592,7.408,3.89,224,0.875,bicubic
Update results-all.csv with latest models/weights
5 years ago
resnet26,75.292,24.708,92.57,7.43,16,224,0.875,bicubic
Update results with new models
5 years ago
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
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
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
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_resnet18,72.6,27.4,91.418,8.582,11.69,224,0.875,bilinear
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
resnet18,69.758,30.242,89.078,10.922,11.69,224,0.875,bilinear
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