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Feature Maps, More Models, CutMix

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@rwightman rwightman released this 13 Aug 16:52
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Aug 12, 2020

  • New/updated weights from training experiments
    • EfficientNet-B3 - 82.1 top-1 (vs 81.6 for official with AA and 81.9 for AdvProp)
    • RegNetY-3.2GF - 82.0 top-1 (78.9 from official ver)
    • CSPResNet50 - 79.6 top-1 (76.6 from official ver)
  • Add CutMix integrated w/ Mixup. See pull request for some usage examples
  • Some fixes for using pretrained weights with in_chans != 3 on several models.

Aug 5, 2020

Universal feature extraction, new models, new weights, new test sets.

  • All models support the features_only=True argument for create_model call to return a network that extracts feature maps from the deepest layer at each stride.
  • New models
    • CSPResNet, CSPResNeXt, CSPDarkNet, DarkNet
    • ReXNet
    • (Modified Aligned) Xception41/65/71 (a proper port of TF models)
  • New trained weights
    • SEResNet50 - 80.3 top-1
    • CSPDarkNet53 - 80.1 top-1
    • CSPResNeXt50 - 80.0 top-1
    • DPN68b - 79.2 top-1
    • EfficientNet-Lite0 (non-TF ver) - 75.5 (submitted by @hal-314)
  • Add 'real' labels for ImageNet and ImageNet-Renditions test set, see results/README.md
  • Test set ranking/top-n diff script by @KushajveerSingh
  • Train script and loader/transform tweaks to punch through more aug arguments
  • README and documentation overhaul. See initial (WIP) documentation at https://rwightman.github.io/pytorch-image-models/
  • adamp and sgdp optimizers added by @hellbell