-
模型代码:hardnet.py
-
验证集数据处理:
# 图像后端:pil # 输入图像大小: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]) ])
-
模型细节:
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
-
引用:
@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} }