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

1	model	rank_diff	top1	top1_diff	top1_err	top5	top5_diff	top5_err	param_count	img_size	cropt_pct	interpolation
2	ig_resnext101_32x48d	+5	58.8143	-26.628	41.1857	81.0863	-16.486	18.9137	828.4100	224	0.8750	bilinear
3	ig_resnext101_32x32d	+9	58.3800	-26.712	41.6200	80.3789	-17.057	19.6211	468.5300	224	0.8750	bilinear
4	ig_resnext101_32x16d	+14	57.7001	-26.476	42.2999	79.9131	-17.283	20.0869	194.0300	224	0.8750	bilinear
5	swsl_resnext101_32x16d	+18	57.4663	-25.872	42.5337	80.3808	-16.471	19.6192	194.0300	224	0.8750	bilinear
6	swsl_resnext101_32x8d	+9	56.4346	-27.859	43.5654	78.9345	-18.239	21.0655	88.7900	224	0.8750	bilinear
7	ig_resnext101_32x8d	+23	54.9176	-27.770	45.0824	77.5452	-19.087	22.4548	88.7900	224	0.8750	bilinear
8	swsl_resnext101_32x4d	+17	53.5911	-29.643	46.4089	76.3387	-20.417	23.6613	44.1800	224	0.8750	bilinear
9	tf_efficientnet_l2_ns_475	-6	51.4866	-36.747	48.5134	73.9295	-24.617	26.0705	480.3100	475	0.9360	bicubic
10	swsl_resnext50_32x4d	+24	50.4490	-31.731	49.5510	73.3577	-22.870	26.6423	25.0300	224	0.8750	bilinear
11	swsl_resnet50	+38	49.5510	-31.629	50.4490	72.3319	-23.654	27.6681	25.5600	224	0.8750	bilinear
12	tf_efficientnet_b7_ns	-8	47.8001	-39.038	52.1999	69.6378	-28.456	30.3622	66.3500	600	0.9490	bicubic
13	tf_efficientnet_b6_ns	-8	47.7510	-38.711	52.2490	69.9621	-27.922	30.0379	43.0400	528	0.9420	bicubic
14	tf_efficientnet_l2_ns	-12	47.5702	-40.782	52.4298	70.0171	-28.631	29.9829	480.3100	800	0.9600	bicubic
15	tf_efficientnet_b8_ap	-6	45.7781	-39.590	54.2219	67.9047	-29.389	32.0953	87.4100	672	0.9540	bicubic
16	tf_efficientnet_b5_ns	-10	45.6071	-40.473	54.3929	67.8516	-29.902	32.1484	30.3900	456	0.9340	bicubic
17	tf_efficientnet_b4_ns	-7	43.4554	-41.703	56.5446	65.5132	-31.955	34.4868	19.3400	380	0.9220	bicubic
18	tf_efficientnet_b8	-10	42.5023	-42.868	57.4977	64.8745	-32.518	35.1255	87.4100	672	0.9540	bicubic
19	tf_efficientnet_b7	-6	41.4372	-43.495	58.5628	63.0274	-34.181	36.9726	66.3500	600	0.9490	bicubic
20	tf_efficientnet_b7_ap	-9	41.4333	-43.685	58.5667	62.8761	-34.376	37.1239	66.3500	600	0.9490	bicubic
21	tf_efficientnet_b5_ap	-5	41.4196	-42.834	58.5804	62.0822	-34.894	37.9178	30.3900	456	0.9340	bicubic
22	tf_efficientnet_b6_ap	-8	41.0914	-43.695	58.9086	62.3593	-34.779	37.6407	43.0400	528	0.9420	bicubic
23	tf_efficientnet_b4_ap	+1	40.4763	-42.772	59.5237	61.7127	-34.675	38.2873	19.3400	380	0.9220	bicubic
24	tf_efficientnet_b3_ns	-4	39.5822	-44.472	60.4178	61.4632	-35.449	38.5368	12.2300	300	0.9040	bicubic
25	tf_efficientnet_b5	-3	38.3285	-45.488	61.6715	59.9285	-36.822	40.0715	30.3900	456	0.9340	bicubic
26	tf_efficientnet_b3_ap	+13	37.0611	-44.767	62.9389	57.2363	-38.388	42.7637	12.2300	300	0.9040	bicubic
27	resnest269e	-10	36.6700	-47.516	63.3300	56.8099	-40.112	43.1901	110.9300	416	0.8750	bilinear
28	tf_efficientnet_b2_ns	+4	36.1768	-46.203	63.8232	57.5547	-38.697	42.4453	9.1100	260	0.8900	bicubic
29	ecaresnet101d	+6	36.0058	-46.160	63.9942	56.1536	-39.898	43.8464	44.5700	224	0.8750	bicubic
30	swsl_resnet18	+192	35.8604	-37.426	64.1396	58.4370	-33.295	41.5630	11.6900	224	0.8750	bilinear
31	resnest200e	-10	35.8466	-47.987	64.1534	55.8903	-40.948	44.1097	70.2000	320	0.8750	bilinear
32	resnest101e	-4	35.3652	-47.525	64.6348	55.7861	-40.538	44.2139	48.2800	256	0.8750	bilinear
33	ssl_resnext101_32x16d	+5	34.6087	-47.227	65.3913	55.9139	-40.180	44.0861	194.0300	224	0.8750	bilinear
34	resnest50d_4s2x40d	+16	34.3611	-46.753	65.6389	54.7112	-40.857	45.2888	30.4200	224	0.8750	bicubic
35	tf_efficientnet_b1_ns	+11	34.1528	-47.233	65.8472	55.4894	-40.249	44.5106	7.7900	240	0.8820	bicubic
36	tf_efficientnet_b4	-9	34.0624	-48.954	65.9376	54.2160	-42.082	45.7840	19.3400	380	0.9220	bicubic
37	ssl_resnext101_32x8d	+5	34.0211	-47.605	65.9789	55.5935	-40.444	44.4065	88.7900	224	0.8750	bilinear
38	tf_efficientnet_b6	-19	34.0054	-50.107	65.9946	54.5403	-42.344	45.4597	43.0400	528	0.9420	bicubic
39	efficientnet_b3_pruned	+18	33.9956	-46.860	66.0044	54.1099	-41.130	45.8901	9.8600	300	0.9040	bicubic
40	tresnet_xl	-4	33.2587	-48.811	66.7413	52.2962	-43.632	47.7038	78.4400	224	0.8750	bilinear
41	resnest50d_1s4x24d	+11	33.1388	-47.851	66.8612	52.8307	-42.491	47.1693	25.6800	224	0.8750	bicubic
42	resnest50d	+11	32.9678	-47.990	67.0322	52.7010	-42.681	47.2990	27.4800	224	0.8750	bilinear
43	tf_efficientnet_b3	-2	32.8637	-48.776	67.1363	52.9623	-42.760	47.0377	12.2300	300	0.9040	bicubic
44	inception_resnet_v2	+22	32.7360	-47.724	67.2640	50.6396	-44.670	49.3604	55.8400	299	0.8975	bicubic
45	gluon_resnet152_v1d	+20	32.7301	-47.740	67.2699	51.0837	-44.122	48.9163	60.2100	224	0.8750	bicubic
46	tf_efficientnet_b2_ap	+28	32.6790	-47.627	67.3210	52.2333	-42.795	47.7667	9.1100	260	0.8900	bicubic
47	nasnetalarge	-16	32.5827	-49.975	67.4173	49.7868	-46.249	50.2132	88.7500	331	0.8750	bicubic
48	tresnet_l	-3	32.5670	-48.921	67.4330	51.1407	-44.487	48.8593	55.9900	224	0.8750	bilinear
49	pnasnet5large	-20	32.5316	-50.208	67.4684	50.1877	-45.852	49.8123	86.0600	331	0.8750	bicubic
50	ens_adv_inception_resnet_v2	+34	32.3705	-47.605	67.6295	50.4274	-44.519	49.5726	55.8400	299	0.8975	bicubic
51	gluon_resnet152_v1s	=	32.3312	-48.681	67.6688	50.5394	-44.877	49.4606	60.3200	224	0.8750	bicubic
52	gluon_seresnext101_64x4d	+4	32.1936	-48.696	67.8064	50.3272	-44.977	49.6728	88.2300	224	0.8750	bicubic
53	gluon_seresnext101_32x4d	+2	32.1150	-48.787	67.8850	51.2409	-44.053	48.7591	48.9600	224	0.8750	bicubic
54	efficientnet_b3a	-17	31.7279	-50.146	68.2721	51.3215	-44.519	48.6785	12.2300	320	1.0000	bicubic
55	efficientnet_b3	-11	31.5648	-49.933	68.4352	51.2724	-44.446	48.7276	12.2300	300	0.9040	bicubic
56	resnet50	+64	31.5451	-47.487	68.4549	50.1719	-44.212	49.8281	25.5600	224	0.8750	bicubic
57	ssl_resnext101_32x4d	-3	31.4331	-49.495	68.5669	52.1154	-43.613	47.8846	44.1800	224	0.8750	bilinear
58	inception_v4	+22	31.3820	-48.774	68.6180	49.2366	-45.737	50.7634	42.6800	299	0.8750	bicubic
59	ecaresnetlight	+8	31.1325	-49.321	68.8675	50.2525	-45.004	49.7475	30.1600	224	0.8750	bicubic
60	gluon_resnet101_v1s	+15	31.1128	-49.187	68.8872	49.7907	-45.359	50.2093	44.6700	224	0.8750	bicubic
61	tf_efficientnet_cc_b0_8e	+98	31.0814	-46.827	68.9186	50.7733	-42.883	49.2267	24.0100	224	0.8750	bicubic
62	ecaresnet50d	=	31.0637	-49.540	68.9363	50.8460	-44.476	49.1540	25.5800	224	0.8750	bicubic
63	gluon_resnet152_v1c	+23	31.0067	-48.909	68.9933	48.9359	-45.906	51.0641	60.2100	224	0.8750	bicubic
64	tresnet_m	-4	30.9929	-49.803	69.0071	48.6903	-46.166	51.3097	31.3900	224	0.8750	bilinear
65	gluon_resnext101_64x4d	-2	30.9812	-49.621	69.0188	48.5527	-46.441	51.4473	83.4600	224	0.8750	bicubic
66	tf_efficientnet_cc_b1_8e	+42	30.9006	-48.397	69.0994	50.0737	-44.290	49.9263	39.7200	240	0.8820	bicubic
67	ecaresnet101d_pruned	-8	30.8947	-49.913	69.1053	50.0010	-45.627	49.9990	24.8800	224	0.8750	bicubic
68	gluon_resnext101_32x4d	+4	30.8809	-49.453	69.1191	48.5370	-46.389	51.4630	44.1800	224	0.8750	bicubic
69	tf_efficientnet_lite4	-26	30.8397	-50.688	69.1603	50.3979	-45.270	49.6021	13.0100	380	0.9200	bilinear
70	dpn107	+9	30.6805	-49.484	69.3195	48.8062	-46.106	51.1938	86.9200	224	0.8750	bicubic
71	ese_vovnet39b	+33	30.6766	-48.643	69.3234	49.8929	-44.817	50.1071	24.5700	224	0.8750	bicubic
72	tresnet_xl_448	-46	30.6196	-52.428	69.3804	49.0715	-47.102	50.9285	78.4400	448	0.8750	bilinear
73	gluon_resnet152_v1b	+22	30.6176	-49.074	69.3824	48.5292	-46.209	51.4708	60.1900	224	0.8750	bicubic
74	ssl_resnext50_32x4d	-1	30.5940	-49.734	69.4060	50.6534	-44.751	49.3466	25.0300	224	0.8750	bilinear
75	gluon_resnet101_v1d	-6	30.5095	-49.914	69.4905	47.9750	-47.045	52.0250	44.5700	224	0.8750	bicubic
76	resnest26d	+62	30.4997	-47.982	69.5003	50.6770	-43.613	49.3230	17.0700	224	0.8750	bilinear
77	efficientnet_b2a	-16	30.4231	-50.185	69.5769	49.6748	-45.635	50.3252	9.1100	288	1.0000	bicubic
78	tf_efficientnet_b1_ap	+32	30.4191	-48.859	69.5809	49.5529	-44.755	50.4471	7.7900	240	0.8820	bicubic
79	dpn98	+18	30.0576	-49.578	69.9424	48.2403	-46.354	51.7597	61.5700	224	0.8750	bicubic
80	tf_efficientnet_b2	+2	30.0202	-50.070	69.9798	49.5903	-45.316	50.4097	9.1100	260	0.8900	bicubic
81	dpn131	+9	30.0143	-49.814	69.9857	48.1440	-46.560	51.8560	79.2500	224	0.8750	bicubic
82	senet154	-35	30.0006	-51.303	69.9994	48.0320	-47.466	51.9680	115.0900	224	0.8750	bilinear
83	dpn92	=	29.9691	-50.047	70.0309	49.1599	-45.678	50.8401	37.6700	224	0.8750	bicubic
84	gluon_senet154	-36	29.8866	-51.337	70.1134	47.8728	-47.483	52.1272	115.0900	224	0.8750	bicubic
85	xception	+34	29.8493	-49.199	70.1507	48.6903	-45.702	51.3097	22.8600	299	0.8975	bicubic
86	adv_inception_v3	+80	29.8237	-47.756	70.1763	47.8669	-45.857	52.1331	23.8300	299	0.8750	bicubic
87	resnetblur50	+22	29.6233	-49.667	70.3767	48.2501	-46.382	51.7499	25.5600	224	0.8750	bicubic
88	efficientnet_b2	-18	29.6174	-50.785	70.3826	48.7728	-46.303	51.2272	9.1100	260	0.8750	bicubic
89	gluon_xception65	+9	29.5545	-50.049	70.4455	47.5230	-47.225	52.4770	39.9200	299	0.8750	bicubic
90	resnext101_32x8d	+15	29.4347	-49.877	70.5653	48.4820	-46.044	51.5180	88.7900	224	0.8750	bilinear
91	ssl_resnet50	+20	29.4229	-49.805	70.5771	49.7730	-45.059	50.2270	25.5600	224	0.8750	bilinear
92	resnext50_32x4d	=	29.3285	-50.434	70.6715	47.3953	-47.205	52.6047	25.0300	224	0.8750	bicubic
93	ecaresnet50d_pruned	=	29.2165	-50.502	70.7835	48.4584	-46.432	51.5416	19.9400	224	0.8750	bicubic
94	tresnet_l_448	-61	29.1674	-53.101	70.8326	47.2342	-48.744	52.7658	55.9900	448	0.8750	bilinear
95	gluon_inception_v3	+32	29.1143	-49.690	70.8857	46.9433	-47.437	53.0567	23.8300	299	0.8750	bicubic
96	hrnet_w64	+5	28.9866	-50.485	71.0134	47.1399	-47.510	52.8601	128.0600	224	0.8750	bilinear
97	tf_efficientnet_b0_ns	+37	28.9139	-49.738	71.0861	49.0106	-45.357	50.9894	5.2900	224	0.8750	bicubic
98	tf_efficientnet_b1	+28	28.8923	-49.940	71.1077	47.5112	-46.685	52.4888	7.7900	240	0.8820	bicubic
99	gluon_resnet101_v1b	+8	28.8569	-50.447	71.1431	46.3715	-48.153	53.6285	44.5500	224	0.8750	bicubic
100	skresnext50_32x4d	-19	28.8176	-51.332	71.1824	46.5032	-48.141	53.4968	27.4800	224	0.8750	bicubic
101	tf_efficientnet_lite3	-10	28.6545	-51.157	71.3455	47.3580	-47.556	52.6420	8.2000	300	0.9040	bilinear
102	hrnet_w40	+20	28.6447	-50.289	71.3553	47.4425	-47.024	52.5575	57.5600	224	0.8750	bilinear
103	gluon_seresnext50_32x4d	-16	28.6408	-51.271	71.3592	46.4501	-48.368	53.5499	27.5600	224	0.8750	bicubic
104	skresnet34	+81	28.6290	-48.281	71.3710	47.9573	-45.359	52.0427	22.2800	224	0.8750	bicubic
105	resnet152	+40	28.5347	-49.777	71.4653	47.1143	-46.932	52.8857	60.1900	224	0.8750	bilinear
106	hrnet_w48	=	28.4069	-50.903	71.5931	47.5741	-46.944	52.4259	77.4700	224	0.8750	bilinear
107	gluon_resnext50_32x4d	-4	28.3833	-50.973	71.6167	45.3261	-49.098	54.6739	25.0300	224	0.8750	bicubic
108	efficientnet_b2_pruned	-23	28.3657	-51.552	71.6343	47.0593	-47.789	52.9407	8.3100	260	0.8900	bicubic
109	tf_efficientnet_b0_ap	+72	28.3499	-48.734	71.6501	47.5309	-45.723	52.4691	5.2900	224	0.8750	bicubic
110	dla102x2	-8	28.3185	-51.133	71.6815	46.7567	-47.887	53.2433	41.7500	224	0.8750	bilinear
111	dla169	+19	28.3106	-50.399	71.6894	47.3992	-46.939	52.6008	53.9900	224	0.8750	bilinear
112	tf_efficientnet_cc_b0_4e	+62	28.3106	-48.993	71.6894	47.3639	-45.968	52.6361	13.3100	224	0.8750	bicubic
113	mixnet_xl	-49	28.2930	-52.185	71.7070	46.7174	-48.215	53.2826	11.9000	224	0.8750	bicubic
114	gluon_resnet50_v1d	+3	28.2360	-50.838	71.7640	45.8763	-48.600	54.1237	25.5800	224	0.8750	bicubic
115	wide_resnet101_2	+10	28.1063	-50.740	71.8937	46.4246	-47.859	53.5754	126.8900	224	0.8750	bilinear
116	gluon_resnet101_v1c	-16	28.1023	-51.442	71.8977	45.9530	-48.633	54.0470	44.5700	224	0.8750	bicubic
117	densenet161	+56	28.1004	-49.248	71.8996	46.6506	-46.997	53.3494	28.6800	224	0.8750	bicubic
118	regnetx_320	-41	28.0788	-52.167	71.9212	45.1198	-49.902	54.8802	107.8100	224	0.8750	bicubic
119	regnety_320	-61	28.0709	-52.743	71.9291	45.4597	-49.780	54.5403	145.0500	224	0.8750	bicubic
120	dpn68b	+48	27.8842	-49.630	72.1158	47.4602	-46.362	52.5398	12.6100	224	0.8750	bicubic
121	regnetx_160	-32	27.8253	-52.041	72.1747	45.6307	-49.197	54.3693	54.2800	224	0.8750	bicubic
122	tf_inception_v3	+38	27.7860	-50.070	72.2140	45.7113	-47.933	54.2887	23.8300	299	0.8750	bicubic
123	res2net101_26w_4s	-8	27.7742	-51.422	72.2258	45.1709	-49.269	54.8291	45.2100	224	0.8750	bilinear
124	regnety_160	-48	27.6386	-52.661	72.3614	45.5344	-49.428	54.4656	83.5900	224	0.8750	bicubic
125	hrnet_w44	-2	27.6248	-51.269	72.3752	45.8311	-48.539	54.1689	67.0600	224	0.8750	bilinear
126	inception_v3	+45	27.5698	-49.866	72.4302	45.2613	-48.215	54.7387	23.8300	299	0.8750	bicubic
127	regnetx_080	-13	27.4106	-51.787	72.5894	45.0215	-49.536	54.9785	39.5700	224	0.8750	bicubic
128	hrnet_w30	+21	27.3851	-50.811	72.6149	46.5425	-47.678	53.4575	37.7100	224	0.8750	bilinear
129	hrnet_w32	+13	27.3772	-51.071	72.6228	45.9903	-48.198	54.0097	41.2300	224	0.8750	bilinear
130	gluon_resnet50_v1s	-1	27.3261	-51.386	72.6739	45.2141	-49.028	54.7859	25.6800	224	0.8750	bicubic
131	densenet201	+45	27.2613	-50.029	72.7387	46.2241	-47.254	53.7759	20.0100	224	0.8750	bicubic
132	regnety_064	-38	27.2279	-52.484	72.7721	44.8506	-49.923	55.1494	30.5800	224	0.8750	bicubic
133	densenetblur121d	+57	27.2240	-49.352	72.7760	46.3067	-46.883	53.6933	8.0000	224	0.8750	bicubic
134	efficientnet_b1_pruned	+13	27.1945	-51.047	72.8055	45.8724	-47.960	54.1276	6.3300	240	0.8820	bicubic
135	res2net50_26w_8s	-22	27.0726	-52.137	72.9274	44.4320	-49.930	55.5680	48.4000	224	0.8750	bilinear
136	dla102x	=	27.0235	-51.484	72.9765	45.4951	-48.739	54.5049	26.7700	224	0.8750	bilinear
137	resnet101	+35	26.9685	-50.405	73.0315	45.2357	-48.310	54.7643	44.5500	224	0.8750	bilinear
138	resnext50d_32x4d	-42	26.8742	-52.800	73.1258	44.4300	-50.438	55.5700	25.0500	224	0.8750	bicubic
139	regnetx_120	-40	26.8644	-52.726	73.1356	44.6816	-50.058	55.3184	46.1100	224	0.8750	bicubic
140	seresnext101_32x4d	-62	26.8192	-53.417	73.1808	43.5084	-51.520	56.4916	48.9600	224	0.8750	bilinear
141	densenet169	+55	26.8113	-49.101	73.1887	45.3752	-47.649	54.6248	14.1500	224	0.8750	bicubic
142	regnetx_064	-24	26.8015	-52.264	73.1985	44.9036	-49.552	55.0964	26.2100	224	0.8750	bicubic
143	regnety_120	-72	26.7818	-53.600	73.2182	44.4399	-50.688	55.5601	51.8200	224	0.8750	bicubic
144	regnetx_032	+6	26.7071	-51.459	73.2929	45.2259	-48.854	54.7741	15.3000	224	0.8750	bicubic
145	densenet121	+55	26.6757	-48.898	73.3243	45.8999	-46.756	54.1001	7.9800	224	0.8750	bicubic
146	seresnet152	-13	26.6718	-51.986	73.3282	43.9447	-50.429	56.0553	66.8200	224	0.8750	bilinear
147	tf_efficientnet_el	-79	26.6226	-53.825	73.3774	44.6364	-50.524	55.3636	10.5900	300	0.9040	bicubic
148	efficientnet_es	+4	26.6168	-51.437	73.3832	45.1060	-48.824	54.8940	5.4400	224	0.8750	bicubic
149	res2net50_26w_6s	-14	26.5873	-51.987	73.4127	43.9781	-50.148	56.0219	37.0500	224	0.8750	bilinear
150	dla60x	-4	26.5637	-51.678	73.4363	45.0392	-48.983	54.9608	17.6500	224	0.8750	bilinear
151	regnety_080	-63	26.5146	-53.353	73.4854	44.3554	-50.477	55.6446	39.1800	224	0.8750	bicubic
152	tf_efficientnet_b0	+34	26.4910	-50.349	73.5090	45.6562	-47.570	54.3438	5.2900	224	0.8750	bicubic
153	res2net50_14w_8s	-2	26.4713	-51.681	73.5287	44.3691	-49.473	55.6309	25.0600	224	0.8750	bilinear
154	gluon_resnet50_v1b	+13	26.4320	-51.146	73.5680	44.0331	-49.685	55.9669	25.5600	224	0.8750	bicubic
155	regnetx_040	-18	26.2395	-52.247	73.7605	44.4241	-49.818	55.5759	22.1200	224	0.8750	bicubic
156	dpn68	+37	26.1216	-50.184	73.8784	44.2335	-48.736	55.7665	12.6100	224	0.8750	bicubic
157	hrnet_w18	+30	25.9761	-50.780	74.0239	44.8093	-48.633	55.1907	21.3000	224	0.8750	bilinear
158	regnety_040	-46	25.9133	-53.309	74.0867	43.8543	-50.802	56.1457	20.6500	224	0.8750	bicubic
159	resnet34	+49	25.8838	-49.228	74.1162	43.9899	-48.298	56.0101	21.8000	224	0.8750	bilinear
160	res2net50_26w_4s	-2	25.8700	-52.076	74.1300	43.1606	-50.691	56.8394	25.7000	224	0.8750	bilinear
161	tresnet_m_448	-121	25.8504	-55.862	74.1496	42.8678	-52.702	57.1322	31.3900	448	0.8750	bilinear
162	gluon_resnet50_v1c	-8	25.7954	-52.215	74.2046	43.0172	-50.971	56.9828	25.5800	224	0.8750	bicubic
163	selecsls60	-6	25.7285	-52.254	74.2715	44.0685	-49.764	55.9315	30.6700	224	0.8750	bicubic
164	dla60_res2net	-25	25.6421	-52.830	74.3579	43.5890	-50.615	56.4110	21.1500	224	0.8750	bilinear
165	dla60_res2next	-24	25.6382	-52.810	74.3618	43.6696	-50.474	56.3304	17.3300	224	0.8750	bilinear
166	tf_efficientnet_lite1	+23	25.5065	-51.132	74.4935	43.5831	-49.649	56.4169	5.4200	240	0.8820	bicubic
167	mixnet_l	-46	25.4986	-53.477	74.5014	43.4632	-50.721	56.5368	7.3300	224	0.8750	bicubic
168	efficientnet_b1	-37	25.4829	-53.215	74.5171	43.2864	-50.866	56.7136	7.7900	240	0.8750	bicubic
169	tv_resnext50_32x4d	-5	25.4692	-52.149	74.5308	42.7912	-50.907	57.2088	25.0300	224	0.8750	bilinear
170	tf_mixnet_l	-42	25.4200	-53.350	74.5800	42.5436	-51.460	57.4564	7.3300	224	0.8750	bicubic
171	res2next50	-23	25.3945	-52.848	74.6055	42.4925	-51.400	57.5075	24.6700	224	0.8750	bilinear
172	selecsls60b	-29	25.3277	-53.090	74.6723	43.5536	-50.612	56.4464	32.7700	224	0.8750	bicubic
173	seresnet101	-29	25.3277	-53.068	74.6723	42.8285	-51.429	57.1715	49.3300	224	0.8750	bilinear
174	regnety_032	-50	25.3237	-53.546	74.6763	42.9071	-51.495	57.0929	19.4400	224	0.8750	bicubic
175	dla102	-22	25.3139	-52.712	74.6861	43.8366	-50.113	56.1634	33.7300	224	0.8750	bilinear
176	wide_resnet50_2	-36	25.3100	-53.158	74.6900	42.1781	-51.908	57.8219	68.8800	224	0.8750	bilinear
177	resnest14d	+25	25.2825	-50.221	74.7175	44.1215	-48.392	55.8785	10.6100	224	0.8750	bilinear
178	seresnext50_32x4d	-62	25.2176	-53.858	74.7824	41.9383	-52.496	58.0617	27.5600	224	0.8750	bilinear
179	res2net50_48w_2s	-10	25.0231	-52.491	74.9769	42.2017	-51.346	57.7983	25.2900	224	0.8750	bilinear
180	efficientnet_b0	-18	25.0152	-52.677	74.9848	42.7853	-50.747	57.2147	5.2900	224	0.8750	bicubic
181	gluon_resnet34_v1b	+35	24.9484	-49.632	75.0516	42.2370	-49.751	57.7630	21.8000	224	0.8750	bicubic
182	mobilenetv2_120d	-7	24.9327	-52.361	75.0673	43.0643	-50.438	56.9357	5.8300	224	0.8750	bicubic
183	dla60	-1	24.9268	-52.097	75.0732	43.3021	-50.006	56.6979	22.3300	224	0.8750	bilinear
184	regnety_016	-23	24.8187	-53.033	75.1813	42.6261	-51.090	57.3739	11.2000	224	0.8750	bicubic
185	tf_efficientnet_em	-53	24.5338	-54.164	75.4662	42.4100	-51.910	57.5900	6.9000	240	0.8820	bicubic
186	tf_efficientnet_lite2	-16	24.5299	-52.930	75.4701	42.2920	-51.454	57.7080	6.0900	260	0.8900	bicubic
187	skresnet18	+36	24.4945	-48.549	75.5055	42.5377	-48.640	57.4623	11.9600	224	0.8750	bicubic
188	regnetx_016	-4	24.4768	-52.453	75.5232	42.5023	-50.916	57.4977	9.1900	224	0.8750	bicubic
189	tf_efficientnet_lite0	+22	24.3707	-50.471	75.6293	42.5102	-49.660	57.4898	4.6500	224	0.8750	bicubic
190	tv_resnet50	+4	24.0917	-52.038	75.9083	41.3095	-51.553	58.6905	25.5600	224	0.8750	bilinear
191	seresnet34	+21	24.0366	-50.771	75.9634	41.8951	-50.231	58.1049	21.9600	224	0.8750	bilinear
192	tv_densenet121	+21	23.8460	-50.906	76.1540	41.9207	-50.231	58.0793	7.9800	224	0.8750	bicubic
193	tf_efficientnet_es	-16	23.8244	-53.440	76.1756	41.3193	-52.281	58.6807	5.4400	224	0.8750	bicubic
194	mobilenetv2_140	-3	23.7104	-52.814	76.2896	41.4687	-51.521	58.5313	6.1100	224	0.8750	bicubic
195	mixnet_m	-17	23.7085	-53.547	76.2915	41.1386	-52.279	58.8614	5.0100	224	0.8750	bicubic
196	dla34	+19	23.6770	-50.959	76.3230	41.5434	-50.521	58.4566	15.7800	224	0.8750	bilinear
197	seresnet50	-34	23.6436	-53.992	76.3564	40.0814	-53.671	59.9186	28.0900	224	0.8750	bilinear
198	tf_mixnet_m	-15	23.4786	-53.471	76.5214	41.0049	-52.151	58.9951	5.0100	224	0.8750	bicubic
199	tv_resnet34	+22	23.4727	-49.841	76.5273	41.3665	-50.053	58.6335	21.8000	224	0.8750	bilinear
200	selecsls42b	-21	23.3665	-53.809	76.6335	40.6768	-52.715	59.3232	32.4600	224	0.8750	bicubic
201	mobilenetv2_110d	+8	23.0698	-51.982	76.9302	40.7436	-51.436	59.2564	4.5200	224	0.8750	bicubic
202	mobilenetv3_large_100	-5	22.6650	-53.103	77.3350	40.7848	-51.755	59.2152	5.4800	224	0.8750	bicubic
203	mobilenetv3_rw	-4	22.6257	-53.002	77.3743	40.3702	-52.340	59.6298	5.4800	224	0.8750	bicubic
204	tf_mobilenetv3_large_100	-3	22.5707	-52.945	77.4293	39.7591	-52.841	60.2409	5.4800	224	0.8750	bilinear
205	hrnet_w18_small_v2	+1	22.3408	-52.785	77.6592	39.8475	-52.569	60.1525	15.6000	224	0.8750	bilinear
206	regnety_008	-14	22.1128	-54.201	77.8872	38.8964	-54.166	61.1036	6.2600	224	0.8750	bicubic
207	seresnext26tn_32x4d	-52	22.0028	-55.987	77.9972	38.4916	-55.256	61.5084	16.8100	224	0.8750	bicubic
208	seresnext26t_32x4d	-52	21.9871	-56.001	78.0129	38.5663	-55.140	61.4337	16.8200	224	0.8750	bicubic
209	regnety_006	-4	21.9733	-53.287	78.0267	38.9534	-53.575	61.0466	6.0600	224	0.8750	bicubic
210	regnetx_008	=	21.9517	-53.070	78.0483	38.9298	-53.414	61.0702	7.2600	224	0.8750	bicubic
211	resnet26d	-23	21.9144	-54.766	78.0856	38.6174	-54.549	61.3826	16.0100	224	0.8750	bicubic
212	semnasnet_100	-9	21.8967	-53.559	78.1033	38.6036	-53.988	61.3964	3.8900	224	0.8750	bicubic
213	regnetx_006	+6	21.7434	-52.119	78.2566	38.9043	-52.776	61.0957	6.2000	224	0.8750	bicubic
214	gluon_resnet18_v1b	+16	21.5449	-49.285	78.4551	38.8728	-50.883	61.1272	11.6900	224	0.8750	bicubic
215	fbnetc_100	-8	21.4919	-53.628	78.5081	38.1654	-54.221	61.8346	5.5700	224	0.8750	bilinear
216	mnasnet_100	-2	21.3504	-53.306	78.6496	37.7154	-54.411	62.2846	4.3800	224	0.8750	bicubic
217	resnet26	-13	21.2954	-53.997	78.7046	38.0161	-54.554	61.9839	16.0000	224	0.8750	bicubic
218	ssl_resnet18	+7	21.2777	-51.322	78.7223	39.1145	-52.301	60.8855	11.6900	224	0.8750	bilinear
219	mixnet_s	-24	21.2580	-54.730	78.7420	38.1929	-54.601	61.8071	4.1300	224	0.8750	bicubic
220	seresnext26d_32x4d	-55	21.2541	-56.350	78.7459	37.2851	-56.327	62.7149	16.8100	224	0.8750	bicubic
221	seresnext26_32x4d	-41	21.0930	-56.007	78.9070	37.6388	-55.671	62.3612	16.7900	224	0.8750	bicubic
222	regnetx_004	+4	20.8866	-51.519	79.1134	37.5484	-53.282	62.4516	5.1600	224	0.8750	bicubic
223	spnasnet_100	-6	20.8670	-53.213	79.1330	37.8923	-53.940	62.1077	4.4200	224	0.8750	bilinear
224	seresnet18	+5	20.8395	-50.918	79.1605	37.6447	-52.689	62.3553	11.7800	224	0.8750	bicubic
225	mobilenetv2_100	-1	20.7609	-52.217	79.2391	37.7508	-53.265	62.2492	3.5000	224	0.8750	bicubic
226	tf_mixnet_s	-28	20.4779	-55.170	79.5221	36.6268	-56.009	63.3732	4.1300	224	0.8750	bicubic
227	regnety_004	-9	20.4170	-53.609	79.5830	37.0296	-54.718	62.9704	4.3400	224	0.8750	bicubic
228	tf_mobilenetv3_large_075	-8	20.3718	-53.070	79.6282	36.7702	-54.582	63.2298	3.9900	224	0.8750	bilinear
229	hrnet_w18_small	-2	20.3659	-51.976	79.6341	37.0945	-53.578	62.9055	13.1900	224	0.8750	bilinear
230	resnet18	+2	20.2283	-49.530	79.7717	37.2595	-51.818	62.7405	11.6900	224	0.8750	bilinear
231	tf_mobilenetv3_large_minimal_100	-3	20.1163	-52.128	79.8837	36.9038	-53.732	63.0962	3.9200	224	0.8750	bilinear
232	regnety_002	-1	17.4596	-52.822	82.5404	32.4432	-57.097	67.5568	3.1600	224	0.8750	bicubic
233	regnetx_002	=	16.9506	-51.803	83.0494	32.2349	-56.313	67.7651	2.6800	224	0.8750	bicubic
234	dla60x_c	+1	16.3257	-51.582	83.6743	31.7750	-56.659	68.2250	1.3400	224	0.8750	bilinear
235	tf_mobilenetv3_small_100	-1	16.2334	-51.685	83.7666	31.2229	-56.439	68.7771	2.5400	224	0.8750	bilinear
236	tf_mobilenetv3_small_075	+1	14.9404	-50.778	85.0596	29.5722	-56.564	70.4278	2.0400	224	0.8750	bilinear
237	dla46_c	+1	14.6613	-50.217	85.3387	29.3737	-56.912	70.6263	1.3100	224	0.8750	bilinear
238	dla46x_c	-2	14.3803	-51.600	85.6197	29.1772	-57.803	70.8228	1.0800	224	0.8750	bilinear
239	tf_mobilenetv3_small_minimal_100	=	13.9677	-48.930	86.0323	27.9805	-56.250	72.0195	2.0400	224	0.8750	bilinear