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HAILO8L_classification.rst

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Public Pre-Trained Models

Here, we give the full list of publicly pre-trained models supported by the Hailo Model Zoo.

  • Network available in Hailo Benchmark are marked with rocket
  • Networks available in TAPPAS are marked with star
  • Benchmark and TAPPAS networks run in performance mode
  • All models were compiled using Hailo Dataflow Compiler v3.29.0

ImageNet

Network Name Accuracy (top1) HW Accuracy FPS (Batch Size=1) FPS (Batch Size=8) Input Resolution (HxWxC) Params (M) OPS (G) Pretrained Source Compiled
cas_vit_m 81.2 80.89 31 68 384x384x3 12.42 10.89 download link download
cas_vit_s 79.93 79.69 41 96 384x384x3 5.5 5.4 download link download
cas_vit_t 81.9 81.6 19 41 384x384x3 21.76 20.85 download link download
deit_base 80.93 80.19 19 58 224x224x3 80.26 35.22 download link download
deit_small 76.25 75.38 26 69 224x224x3 20.52 9.4 download link download
deit_tiny 69.07 68.4 55 195 224x224x3 5.3 2.57 download link download
efficientnet_l 80.47 79.26 76 167 300x300x3 10.55 19.4 download link download
efficientnet_lite0 74.99 73.82 206 598 224x224x3 4.63 0.78 download link download
efficientnet_lite1 76.67 76.3 155 474 240x240x3 5.39 1.22 download link download
efficientnet_lite2 77.46 76.71 107 272 260x260x3 6.06 1.74 download link download
efficientnet_lite3 79.29 78.71 84 207 280x280x3 8.16 2.8 download link download
efficientnet_lite4 80.79 80.08 60 140 300x300x3 12.95 5.10 download link download
efficientnet_m rocket 78.91 78.47 153 435 240x240x3 6.87 7.32 download link download
efficientnet_s 77.63 77.19 162 444 224x224x3 5.41 4.72 download link download
fastvit_sa12 76.8 76.64 103 344 224x224x3 11.99 3.59 download link download
hardnet39ds 73.43 72.97 251 787 224x224x3 3.48 0.86 download link download
hardnet68 75.47 75.3 92 205 224x224x3 17.56 8.5 download link download
inception_v1 69.74 69.53 226 519 224x224x3 6.62 3 download link download
mobilenet_v1 70.97 70.3 1866 1866 224x224x3 4.22 1.14 download link download
mobilenet_v2_1.0 rocket 71.78 70.95 1738 1738 224x224x3 3.49 0.62 download link download
mobilenet_v2_1.4 74.18 73.25 185 592 224x224x3 6.09 1.18 download link download
mobilenet_v3 72.21 71.76 224 753 224x224x3 4.07 2 download link download
mobilenet_v3_large_minimalistic 72.12 70.57 348 1143 224x224x3 3.91 0.42 download link download
regnetx_1.6gf 77.05 76.75 227 659 224x224x3 9.17 3.22 download link download
regnetx_800mf 75.16 74.81 291 945 224x224x3 7.24 1.6 download link download
repghost_1_0x 73.03 72.08 145 484 224x224x3 4.1 0.28 download link download
repghost_2_0x 77.18 76.91 72 205 224x224x3 9.8 1.04 download link download
repvgg_a1 74.4 72.43 246 678 224x224x3 12.79 4.7 download link download
repvgg_a2 76.52 74.39 148 337 224x224x3 25.5 10.2 download link download
resmlp12_relu 75.27 74.93 45 191 224x224x3 15.77 6.04 download link download
resnet_v1_18 71.27 71.11 915 915 224x224x3 11.68 3.64 download link download
resnet_v1_34 72.7 72.34 170 425 224x224x3 21.79 7.34 download link download
resnet_v1_50 rocket star 75.21 74.68 135 499 224x224x3 25.53 6.98 download link download
resnext26_32x4d 76.17 75.97 193 491 224x224x3 15.37 4.96 download link download
resnext50_32x4d 79.3 78.36 114 291 224x224x3 24.99 8.48 download link download
squeezenet_v1.1 59.85 59.36 1730 1730 224x224x3 1.24 0.78 download link download
vit_base 84.5 83.16 17 39 224x224x3 86.5 35.188 download link download
vit_base_bn 79.98 79.28 31 90 224x224x3 86.5 35.188 download link download
vit_small 81.5 79.91 33 100 224x224x3 21.12 8.62 download link download
vit_small_bn 78.12 77.24 95 347 224x224x3 21.12 8.62 download link download
vit_tiny 75.51 73.6 56 195 224x224x3 5.73 2.2 download link download
vit_tiny_bn 68.95 67.28 161 673 224x224x3 5.73 2.2 download link download