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Origin Repo:PingoLH/Pytorch-HarDNet
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Code:hardnet.py
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Evaluate Transforms:
# backend: pil # input_size: 224x224 transforms = T.Compose([ T.Resize(256), T.CenterCrop(224), T.ToTensor(), T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) ])
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Model Details:
Model Model Name Params (M) FLOPs (G) Top-1 (%) Top-5 (%) Pretrained Model HarDNet-68 hardnet_68 17.6 4.3 76.48 93.01 Download HarDNet-85 hardnet_85 36.7 9.1 78.04 93.89 Download HarDNet-39-ds hardnet_39_ds 3.5 0.4 72.08 90.43 Download HarDNet-68-ds hardnet_68_ds 4.2 0.8 74.29 91.87 Download
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Citation:
@misc{chao2019hardnet, title={HarDNet: A Low Memory Traffic Network}, author={Ping Chao and Chao-Yang Kao and Yu-Shan Ruan and Chien-Hsiang Huang and Youn-Long Lin}, year={2019}, eprint={1909.00948}, archivePrefix={arXiv}, primaryClass={cs.CV} }