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

1	model	top1	top1_err	top5	top5_err	param_count	img_size	cropt_pct	interpolation
2	tf_efficientnet_l2_ns	88.352	11.648	98.650	1.350	480.31	800	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	86.840	13.160	98.094	1.906	66.35	600	0.949	bicubic
5	tf_efficientnet_b6_ns	86.452	13.548	97.882	2.118	43.04	528	0.942	bicubic
6	tf_efficientnet_b5_ns	86.088	13.912	97.752	2.248	30.39	456	0.934	bicubic
7	ig_resnext101_32x48d	85.428	14.572	97.572	2.428	828.41	224	0.875	bilinear
8	tf_efficientnet_b8	85.370	14.630	97.390	2.610	87.41	672	0.954	bicubic
9	tf_efficientnet_b8_ap	85.370	14.630	97.294	2.706	87.41	672	0.954	bicubic
10	tf_efficientnet_b4_ns	85.162	14.838	97.470	2.530	19.34	380	0.922	bicubic
11	tf_efficientnet_b7_ap	85.120	14.880	97.252	2.748	66.35	600	0.949	bicubic
12	ig_resnext101_32x32d	85.094	14.906	97.438	2.562	468.53	224	0.875	bilinear
13	tf_efficientnet_b7	84.936	15.064	97.204	2.796	66.35	600	0.949	bicubic
14	tf_efficientnet_b6_ap	84.788	15.212	97.138	2.862	43.04	528	0.942	bicubic
15	resnest269e	84.518	15.482	96.986	3.014	110.93	416	0.928	bicubic
16	swsl_resnext101_32x8d	84.284	15.716	97.176	2.824	88.79	224	0.875	bilinear
17	tf_efficientnet_b5_ap	84.252	15.748	96.974	3.026	30.39	456	0.934	bicubic
18	ig_resnext101_32x16d	84.170	15.830	97.196	2.804	194.03	224	0.875	bilinear
19	tf_efficientnet_b6	84.110	15.890	96.886	3.114	43.04	528	0.942	bicubic
20	tf_efficientnet_b3_ns	84.048	15.952	96.910	3.090	12.23	300	0.904	bicubic
21	resnest200e	83.832	16.168	96.894	3.106	70.20	320	0.909	bicubic
22	tf_efficientnet_b5	83.812	16.188	96.748	3.252	30.39	456	0.934	bicubic
23	swsl_resnext101_32x16d	83.346	16.654	96.846	3.154	194.03	224	0.875	bilinear
24	tf_efficientnet_b4_ap	83.248	16.752	96.392	3.608	19.34	380	0.922	bicubic
25	swsl_resnext101_32x4d	83.230	16.770	96.760	3.240	44.18	224	0.875	bilinear
26	tresnet_xl_448	83.050	16.950	96.174	3.826	78.44	448	0.875	bilinear
27	tf_efficientnet_b4	83.022	16.978	96.300	3.700	19.34	380	0.922	bicubic
28	resnest101e	82.890	17.110	96.320	3.680	48.28	256	0.875	bilinear
29	pnasnet5large	82.782	17.218	96.040	3.960	86.06	331	0.911	bicubic
30	ig_resnext101_32x8d	82.688	17.312	96.636	3.364	88.79	224	0.875	bilinear
31	nasnetalarge	82.620	17.380	96.046	3.954	88.75	331	0.911	bicubic
32	tf_efficientnet_b2_ns	82.380	17.620	96.248	3.752	9.11	260	0.890	bicubic
33	tresnet_l_448	82.268	17.732	95.976	4.024	55.99	448	0.875	bilinear
34	swsl_resnext50_32x4d	82.182	17.818	96.230	3.770	25.03	224	0.875	bilinear
35	ecaresnet101d	82.172	17.828	96.046	3.954	44.57	224	0.875	bicubic
36	tresnet_xl	82.054	17.946	95.936	4.064	78.44	224	0.875	bilinear
37	efficientnet_b3a	81.866	18.134	95.836	4.164	12.23	320	1.000	bicubic
38	ssl_resnext101_32x16d	81.844	18.156	96.096	3.904	194.03	224	0.875	bilinear
39	tf_efficientnet_b3_ap	81.822	18.178	95.624	4.376	12.23	300	0.904	bicubic
40	tresnet_m_448	81.714	18.286	95.572	4.428	31.39	448	0.875	bilinear
41	tf_efficientnet_b3	81.636	18.364	95.718	4.282	12.23	300	0.904	bicubic
42	rexnet_200	81.632	18.368	95.668	4.332	16.37	224	0.875	bicubic
43	ssl_resnext101_32x8d	81.616	18.384	96.038	3.962	88.79	224	0.875	bilinear
44	tf_efficientnet_lite4	81.536	18.464	95.668	4.332	13.01	380	0.920	bilinear
45	efficientnet_b3	81.494	18.506	95.716	4.284	12.23	300	0.904	bicubic
46	tresnet_l	81.488	18.512	95.624	4.376	55.99	224	0.875	bilinear
47	tf_efficientnet_b1_ns	81.388	18.612	95.738	4.262	7.79	240	0.882	bicubic
48	gluon_senet154	81.234	18.766	95.348	4.652	115.09	224	0.875	bicubic
49	swsl_resnet50	81.166	18.834	95.972	4.028	25.56	224	0.875	bilinear
50	resnest50d_4s2x40d	81.108	18.892	95.558	4.442	30.42	224	0.875	bicubic
51	gluon_resnet152_v1s	81.016	18.984	95.412	4.588	60.32	224	0.875	bicubic
52	resnest50d_1s4x24d	80.988	19.012	95.322	4.678	25.68	224	0.875	bicubic
53	resnest50d	80.974	19.026	95.378	4.622	27.48	224	0.875	bilinear
54	ssl_resnext101_32x4d	80.924	19.076	95.728	4.272	44.18	224	0.875	bilinear
55	gluon_seresnext101_32x4d	80.904	19.096	95.294	4.706	48.96	224	0.875	bicubic
56	gluon_seresnext101_64x4d	80.894	19.106	95.308	4.692	88.23	224	0.875	bicubic
57	efficientnet_b3_pruned	80.858	19.142	95.242	4.758	9.86	300	0.904	bicubic
58	ecaresnet101d_pruned	80.818	19.182	95.628	4.372	24.88	224	0.875	bicubic
59	regnety_320	80.812	19.188	95.244	4.756	145.05	224	0.875	bicubic
60	tresnet_m	80.802	19.198	94.860	5.140	31.39	224	0.875	bilinear
61	efficientnet_b2a	80.612	19.388	95.318	4.682	9.11	288	1.000	bicubic
62	gluon_resnext101_64x4d	80.604	19.396	94.988	5.012	83.46	224	0.875	bicubic
63	ecaresnet50d	80.592	19.408	95.320	4.680	25.58	224	0.875	bicubic
64	mixnet_xl	80.476	19.524	94.936	5.064	11.90	224	0.875	bicubic
65	gluon_resnet152_v1d	80.474	19.526	95.206	4.794	60.21	224	0.875	bicubic
66	ecaresnetlight	80.462	19.538	95.250	4.750	30.16	224	0.875	bicubic
67	inception_resnet_v2	80.458	19.542	95.306	4.694	55.84	299	0.897	bicubic
68	tf_efficientnet_el	80.440	19.560	95.164	4.836	10.59	300	0.904	bicubic
69	gluon_resnet101_v1d	80.414	19.586	95.014	4.986	44.57	224	0.875	bicubic
70	efficientnet_b2	80.392	19.608	95.076	4.924	9.11	260	0.875	bicubic
71	regnety_120	80.366	19.634	95.126	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	80.318	19.682	95.406	4.594	25.03	224	0.875	bilinear
74	rexnet_150	80.310	19.690	95.166	4.834	9.73	224	0.875	bicubic
75	gluon_resnet101_v1s	80.302	19.698	95.160	4.840	44.67	224	0.875	bicubic
76	tf_efficientnet_b2_ap	80.300	19.700	95.028	4.972	9.11	260	0.890	bicubic
77	regnety_160	80.296	19.704	94.962	5.038	83.59	224	0.875	bicubic
78	seresnet50	80.274	19.726	95.070	4.930	28.09	224	0.875	bicubic
79	regnetx_320	80.246	19.754	95.026	4.974	107.81	224	0.875	bicubic
80	inception_v4	80.168	19.832	94.968	5.032	42.68	299	0.875	bicubic
81	dpn107	80.156	19.844	94.910	5.090	86.92	224	0.875	bicubic
82	skresnext50_32x4d	80.156	19.844	94.642	5.358	27.48	224	0.875	bicubic
83	tf_efficientnet_b2	80.086	19.914	94.908	5.092	9.11	260	0.890	bicubic
84	cspdarknet53	80.058	19.942	95.084	4.916	27.64	256	0.887	bilinear
85	cspresnext50	80.040	19.960	94.944	5.056	20.57	224	0.875	bilinear
86	dpn92	80.008	19.992	94.836	5.164	37.67	224	0.875	bicubic
87	ens_adv_inception_resnet_v2	79.982	20.018	94.936	5.064	55.84	299	0.897	bicubic
88	gluon_seresnext50_32x4d	79.918	20.082	94.822	5.178	27.56	224	0.875	bicubic
89	efficientnet_b2_pruned	79.916	20.084	94.856	5.144	8.31	260	0.890	bicubic
90	gluon_resnet152_v1c	79.910	20.090	94.840	5.160	60.21	224	0.875	bicubic
91	regnety_080	79.876	20.124	94.830	5.170	39.18	224	0.875	bicubic
92	xception71	79.874	20.126	94.922	5.078	42.34	299	0.903	bicubic
93	regnetx_160	79.856	20.144	94.830	5.170	54.28	224	0.875	bicubic
94	dpn131	79.822	20.178	94.710	5.290	79.25	224	0.875	bicubic
95	tf_efficientnet_lite3	79.820	20.180	94.914	5.086	8.20	300	0.904	bilinear
96	resnext50_32x4d	79.768	20.232	94.598	5.402	25.03	224	0.875	bicubic
97	regnety_064	79.722	20.278	94.768	5.232	30.58	224	0.875	bicubic
98	ecaresnet50d_pruned	79.716	20.284	94.880	5.120	19.94	224	0.875	bicubic
99	gluon_xception65	79.716	20.284	94.860	5.140	39.92	299	0.903	bicubic
100	gluon_resnet152_v1b	79.686	20.314	94.736	5.264	60.19	224	0.875	bicubic
101	resnext50d_32x4d	79.676	20.324	94.866	5.134	25.05	224	0.875	bicubic
102	dpn98	79.642	20.358	94.598	5.402	61.57	224	0.875	bicubic
103	regnetx_120	79.596	20.404	94.738	5.262	46.11	224	0.875	bicubic
104	xception65	79.552	20.448	94.654	5.346	39.92	299	0.903	bicubic
105	gluon_resnet101_v1c	79.534	20.466	94.578	5.422	44.57	224	0.875	bicubic
106	rexnet_130	79.500	20.500	94.682	5.318	7.56	224	0.875	bicubic
107	hrnet_w64	79.474	20.526	94.652	5.348	128.06	224	0.875	bilinear
108	dla102x2	79.448	20.552	94.640	5.360	41.28	224	0.875	bilinear
109	gluon_resnext50_32x4d	79.354	20.646	94.426	5.574	25.03	224	0.875	bicubic
110	ese_vovnet39b	79.320	20.680	94.712	5.288	24.57	224	0.875	bicubic
111	resnext101_32x8d	79.308	20.692	94.518	5.482	88.79	224	0.875	bilinear
112	tf_efficientnet_cc_b1_8e	79.308	20.692	94.370	5.630	39.72	240	0.882	bicubic
113	gluon_resnet101_v1b	79.306	20.694	94.524	5.476	44.55	224	0.875	bicubic
114	hrnet_w48	79.300	20.700	94.512	5.488	77.47	224	0.875	bilinear
115	resnetblur50	79.286	20.714	94.638	5.362	25.56	224	0.875	bicubic
116	tf_efficientnet_b1_ap	79.280	20.720	94.306	5.694	7.79	240	0.882	bicubic
117	ssl_resnet50	79.222	20.778	94.832	5.168	25.56	224	0.875	bilinear
118	regnety_040	79.220	20.780	94.656	5.344	20.65	224	0.875	bicubic
119	dpn68b	79.216	20.784	94.414	5.586	12.61	224	0.875	bicubic
120	res2net50_26w_8s	79.198	20.802	94.368	5.632	48.40	224	0.875	bilinear
121	res2net101_26w_4s	79.198	20.802	94.432	5.568	45.21	224	0.875	bilinear
122	regnetx_080	79.194	20.806	94.560	5.440	39.57	224	0.875	bicubic
123	gluon_resnet50_v1d	79.074	20.926	94.470	5.530	25.58	224	0.875	bicubic
124	regnetx_064	79.072	20.928	94.458	5.542	26.21	224	0.875	bicubic
125	xception	79.052	20.948	94.392	5.608	22.86	299	0.897	bicubic
126	resnet50	79.038	20.962	94.390	5.610	25.56	224	0.875	bicubic
127	mixnet_l	78.976	21.024	94.182	5.818	7.33	224	0.875	bicubic
128	hrnet_w40	78.920	21.080	94.470	5.530	57.56	224	0.875	bilinear
129	hrnet_w44	78.896	21.104	94.368	5.632	67.06	224	0.875	bilinear
130	regnety_032	78.886	21.114	94.412	5.588	19.44	224	0.875	bicubic
131	wide_resnet101_2	78.856	21.144	94.282	5.718	126.89	224	0.875	bilinear
132	tf_efficientnet_b1	78.826	21.174	94.198	5.802	7.79	240	0.882	bicubic
133	gluon_inception_v3	78.806	21.194	94.370	5.630	23.83	299	0.875	bicubic
134	tf_mixnet_l	78.774	21.226	93.998	6.002	7.33	224	0.875	bicubic
135	gluon_resnet50_v1s	78.712	21.288	94.238	5.762	25.68	224	0.875	bicubic
136	tf_efficientnet_em	78.708	21.292	94.314	5.686	6.90	240	0.882	bicubic
137	efficientnet_b1	78.698	21.302	94.144	5.856	7.79	240	0.875	bicubic
138	dla169	78.688	21.312	94.336	5.664	53.39	224	0.875	bilinear
139	tf_efficientnet_b0_ns	78.658	21.342	94.376	5.624	5.29	224	0.875	bicubic
140	res2net50_26w_6s	78.570	21.430	94.124	5.876	37.05	224	0.875	bilinear
141	xception41	78.516	21.484	94.278	5.722	26.97	299	0.903	bicubic
142	dla102x	78.510	21.490	94.228	5.772	26.31	224	0.875	bilinear
143	regnetx_040	78.482	21.518	94.244	5.756	22.12	224	0.875	bicubic
144	resnest26d	78.478	21.522	94.298	5.702	17.07	224	0.875	bilinear
145	wide_resnet50_2	78.478	21.522	94.094	5.906	68.88	224	0.875	bilinear
146	dla60_res2net	78.464	21.536	94.206	5.794	20.85	224	0.875	bilinear
147	hrnet_w32	78.450	21.550	94.186	5.814	41.23	224	0.875	bilinear
148	dla60_res2next	78.440	21.560	94.152	5.848	17.03	224	0.875	bilinear
149	selecsls60b	78.412	21.588	94.174	5.826	32.77	224	0.875	bicubic
150	resnet152	78.312	21.688	94.038	5.962	60.19	224	0.875	bilinear
151	dla60x	78.246	21.754	94.018	5.982	17.35	224	0.875	bilinear
152	res2next50	78.246	21.754	93.892	6.108	24.67	224	0.875	bilinear
153	efficientnet_b1_pruned	78.236	21.764	93.834	6.166	6.33	240	0.882	bicubic
154	hrnet_w30	78.206	21.794	94.222	5.778	37.71	224	0.875	bilinear
155	regnetx_032	78.172	21.828	94.088	5.912	15.30	224	0.875	bicubic
156	res2net50_14w_8s	78.150	21.850	93.848	6.152	25.06	224	0.875	bilinear
157	efficientnet_es	78.066	21.934	93.926	6.074	5.44	224	0.875	bicubic
158	dla102	78.032	21.968	93.946	6.054	33.27	224	0.875	bilinear
159	gluon_resnet50_v1c	78.012	21.988	93.988	6.012	25.58	224	0.875	bicubic
160	seresnext26t_32x4d	77.998	22.002	93.708	6.292	16.82	224	0.875	bicubic
161	seresnext26tn_32x4d	77.986	22.014	93.746	6.254	16.81	224	0.875	bicubic
162	selecsls60	77.982	22.018	93.828	6.172	30.67	224	0.875	bicubic
163	res2net50_26w_4s	77.964	22.036	93.854	6.146	25.70	224	0.875	bilinear
164	tf_efficientnet_cc_b0_8e	77.908	22.092	93.654	6.346	24.01	224	0.875	bicubic
165	regnety_016	77.862	22.138	93.720	6.280	11.20	224	0.875	bicubic
166	rexnet_100	77.858	22.142	93.870	6.130	4.80	224	0.875	bicubic
167	tf_inception_v3	77.858	22.142	93.638	6.362	23.83	299	0.875	bicubic
168	efficientnet_b0	77.698	22.302	93.532	6.468	5.29	224	0.875	bicubic
169	tv_resnext50_32x4d	77.620	22.380	93.696	6.304	25.03	224	0.875	bilinear
170	seresnext26d_32x4d	77.602	22.398	93.608	6.392	16.81	224	0.875	bicubic
171	adv_inception_v3	77.582	22.418	93.736	6.264	23.83	299	0.875	bicubic
172	gluon_resnet50_v1b	77.580	22.420	93.716	6.284	25.56	224	0.875	bicubic
173	res2net50_48w_2s	77.522	22.478	93.554	6.446	25.29	224	0.875	bilinear
174	tf_efficientnet_lite2	77.468	22.532	93.754	6.246	6.09	260	0.890	bicubic
175	inception_v3	77.440	22.560	93.476	6.524	23.83	299	0.875	bicubic
176	resnet101	77.374	22.626	93.540	6.460	44.55	224	0.875	bilinear
177	densenet161	77.358	22.642	93.638	6.362	28.68	224	0.875	bicubic
178	tf_efficientnet_cc_b0_4e	77.306	22.694	93.334	6.666	13.31	224	0.875	bicubic
179	densenet201	77.286	22.714	93.478	6.522	20.01	224	0.875	bicubic
180	mobilenetv2_120d	77.284	22.716	93.492	6.508	5.83	224	0.875	bicubic
181	mixnet_m	77.260	22.740	93.424	6.576	5.01	224	0.875	bicubic
182	tf_efficientnet_es	77.258	22.742	93.594	6.406	5.44	224	0.875	bicubic
183	selecsls42b	77.174	22.826	93.390	6.610	32.46	224	0.875	bicubic
184	tf_efficientnet_b0_ap	77.086	22.914	93.256	6.744	5.29	224	0.875	bicubic
185	dla60	77.032	22.968	93.318	6.682	22.04	224	0.875	bilinear
186	regnetx_016	76.950	23.050	93.420	6.580	9.19	224	0.875	bicubic
187	tf_mixnet_m	76.942	23.058	93.152	6.848	5.01	224	0.875	bicubic
188	skresnet34	76.912	23.088	93.322	6.678	22.28	224	0.875	bicubic
189	tf_efficientnet_b0	76.848	23.152	93.228	6.772	5.29	224	0.875	bicubic
190	ese_vovnet19b_dw	76.798	23.202	93.268	6.732	6.54	224	0.875	bicubic
191	hrnet_w18	76.758	23.242	93.444	6.556	21.30	224	0.875	bilinear
192	resnet26d	76.696	23.304	93.150	6.850	16.01	224	0.875	bicubic
193	tf_efficientnet_lite1	76.642	23.358	93.226	6.774	5.42	240	0.882	bicubic
194	densenetblur121d	76.588	23.412	93.192	6.808	8.00	224	0.875	bicubic
195	mobilenetv2_140	76.516	23.484	92.996	7.004	6.11	224	0.875	bicubic
196	dpn68	76.318	23.682	92.978	7.022	12.61	224	0.875	bicubic
197	regnety_008	76.316	23.684	93.066	6.934	6.26	224	0.875	bicubic
198	tv_resnet50	76.138	23.862	92.864	7.136	25.56	224	0.875	bilinear
199	mixnet_s	75.992	24.008	92.796	7.204	4.13	224	0.875	bicubic
200	densenet169	75.906	24.094	93.026	6.974	14.15	224	0.875	bicubic
201	mobilenetv3_large_100	75.766	24.234	92.542	7.458	5.48	224	0.875	bicubic
202	tf_mixnet_s	75.650	24.350	92.628	7.372	4.13	224	0.875	bicubic
203	mobilenetv3_rw	75.634	24.366	92.708	7.292	5.48	224	0.875	bicubic
204	densenet121	75.578	24.422	92.652	7.348	7.98	224	0.875	bicubic
205	tf_mobilenetv3_large_100	75.518	24.482	92.606	7.394	5.48	224	0.875	bilinear
206	resnest14d	75.506	24.494	92.518	7.482	10.61	224	0.875	bilinear
207	efficientnet_lite0	75.484	24.516	92.510	7.490	4.65	224	0.875	bicubic
208	semnasnet_100	75.448	24.552	92.604	7.396	3.89	224	0.875	bicubic
209	resnet26	75.292	24.708	92.570	7.430	16.00	224	0.875	bicubic
210	regnety_006	75.246	24.754	92.532	7.468	6.06	224	0.875	bicubic
211	fbnetc_100	75.124	24.876	92.386	7.614	5.57	224	0.875	bilinear
212	hrnet_w18_small_v2	75.114	24.886	92.416	7.584	15.60	224	0.875	bilinear
213	resnet34	75.110	24.890	92.284	7.716	21.80	224	0.875	bilinear
214	regnetx_008	75.038	24.962	92.336	7.664	7.26	224	0.875	bicubic
215	mobilenetv2_110d	75.036	24.964	92.186	7.814	4.52	224	0.875	bicubic
216	tf_efficientnet_lite0	74.830	25.170	92.176	7.824	4.65	224	0.875	bicubic
217	tv_densenet121	74.738	25.262	92.150	7.850	7.98	224	0.875	bicubic
218	mnasnet_100	74.658	25.342	92.114	7.886	4.38	224	0.875	bicubic
219	dla34	74.630	25.370	92.078	7.922	15.74	224	0.875	bilinear
220	gluon_resnet34_v1b	74.588	25.412	91.990	8.010	21.80	224	0.875	bicubic
221	spnasnet_100	74.084	25.916	91.818	8.182	4.42	224	0.875	bilinear
222	regnety_004	74.034	25.966	91.752	8.248	4.34	224	0.875	bicubic
223	regnetx_006	73.852	26.148	91.672	8.328	6.20	224	0.875	bicubic
224	tf_mobilenetv3_large_075	73.438	26.562	91.350	8.650	3.99	224	0.875	bilinear
225	tv_resnet34	73.312	26.688	91.426	8.574	21.80	224	0.875	bilinear
226	swsl_resnet18	73.276	26.724	91.734	8.266	11.69	224	0.875	bilinear
227	skresnet18	73.038	26.962	91.168	8.832	11.96	224	0.875	bicubic
228	mobilenetv2_100	72.970	27.030	91.016	8.984	3.50	224	0.875	bicubic
229	ssl_resnet18	72.610	27.390	91.416	8.584	11.69	224	0.875	bilinear
230	regnetx_004	72.396	27.604	90.830	9.170	5.16	224	0.875	bicubic
231	hrnet_w18_small	72.342	27.658	90.678	9.322	13.19	224	0.875	bilinear
232	tf_mobilenetv3_large_minimal_100	72.248	27.752	90.630	9.370	3.92	224	0.875	bilinear
233	gluon_resnet18_v1b	70.836	29.164	89.762	10.238	11.69	224	0.875	bicubic
234	regnety_002	70.252	29.748	89.540	10.460	3.16	224	0.875	bicubic
235	resnet18	69.748	30.252	89.078	10.922	11.69	224	0.875	bilinear
236	regnetx_002	68.762	31.238	88.556	11.444	2.68	224	0.875	bicubic
237	tf_mobilenetv3_small_100	67.922	32.078	87.664	12.336	2.54	224	0.875	bilinear
238	dla60x_c	67.892	32.108	88.426	11.574	1.32	224	0.875	bilinear
239	dla46x_c	65.970	34.030	86.980	13.020	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