Classification
ImageNet
| Network Name | Accuracy (top1) | Quantized | Input Resolution (HxWxC) | Params (M) | FLOPs (G) | Pretrained | Source | Compiled |
|---|---|---|---|---|---|---|---|---|
| efficientnet_l | 80.47 | 79.07 | 300x300x3 | 10.55 | 9.70 | link | link | link |
| efficientnet_m🚀 | 78.98 | 78.35 | 240x240x3 | 6.87 | 3.68 | link | link | link |
| efficientnet_s | 77.61 | 76.93 | 224x224x3 | 5.41 | 2.36 | link | link | link |
| efficientnet_lite0 | 74.93 | 74.25 | 224x224x3 | 4.63 | 0.39 | link | link | link |
| efficientnet_lite1 | 76.66 | 76.16 | 240x240x3 | 5.39 | 0.61 | link | link | link |
| efficientnet_lite2 | 77.44 | 76.23 | 260x260x3 | 6.06 | 0.87 | link | link | link |
| efficientnet_lite3 | 79.2 | 78.49 | 280x280x3 | 8.16 | 1.40 | link | link | link |
| efficientnet_lite4 | 80.79 | 80.01 | 300x300x3 | 12.95 | 2.58 | link | link | link |
| hardnet39ds | 73.44 | 71.81 | 224x224x3 | 3.48 | 0.43 | link | link | link |
| hardnet68 | 75.48 | 75.06 | 224x224x3 | 17.56 | 4.25 | link | link | link |
| inception_v1 | 69.76 | 69.55 | 224x224x3 | 6.62 | 1.50 | link | link | link |
| mobilenet_v1 | 71.02 | 70.18 | 224x224x3 | 4.22 | 0.57 | link | link | link |
| mobilenet_v2_1.0🚀 | 71.84 | 71.13 | 224x224x3 | 3.49 | 0.31 | link | link | link |
| mobilenet_v2_1.4 | 74.11 | 73.15 | 224x224x3 | 6.09 | 0.59 | link | link | link |
| mobilenet_v3 | 72.27 | 71.79 | 224x224x3 | 4.07 | 1.00 | link | link | link |
| mobilenet_v3_large_minimalistic🚀 | 72.12 | 71.14 | 224x224x3 | 3.91 | 0.21 | link | link | link |
| regnetx_1.6gf | 77.07 | 76.47 | 224x224x3 | 9.17 | 1.61 | link | link | link |
| regnetx_800mf🚀 | 75.07 | 74.42 | 224x224x3 | 7.24 | 0.80 | link | link | link |
| regnety_200mf | 70.32 | 69.85 | 224x224x3 | 3.15 | 0.20 | link | link | link |
| resmlp12_relu | 75.26 | 74.06 | 224x224x3 | 15.77 | 3.02 | link | link | link |
| resnet_v1_18 | 71.21 | 70.61 | 224x224x3 | 11.68 | 1.82 | link | link | link |
| resnet_v1_34 | 72.68 | 71.81 | 224x224x3 | 21.79 | 3.67 | link | link | link |
| resnet_v1_50🚀⭐ | 75.21 | 74.61 | 224x224x3 | 25.53 | 3.49 | link | link | link |
| resnet_v2_18 | 69.58 | 68.2 | 224x224x3 | 11.68 | 1.82 | link | link | link |
| resnet_v2_34 | 73.1 | 72.63 | 224x224x3 | 21.79 | 3.67 | link | link | link |
| resnext26_32x4d | 76.08 | 74.76 | 224x224x3 | 15.37 | 2.48 | link | link | link |
| resnext50_32x4d | 79.32 | 78.4 | 224x224x3 | 24.99 | 4.24 | link | link | link |
| shufflenet_g8_w1 | 66.29 | 65.44 | 224x224x3 | 2.46 | 0.18 | link | link | link |
| squeezenet_v1.1 | 59.88 | 59.02 | 224x224x3 | 1.24 | 0.39 | link | link | link |
- Network available in Hailo Benchmark are marked with 🚀
- Networks available in TAPPAS are marked with ⭐
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