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huanghoujing / EANet

EANet: Enhancing Alignment for Cross-Domain Person Re-identification
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The part_segmentation model #15

Closed wlw208dzy closed 5 years ago

wlw208dzy commented 5 years ago

Thanks for your wonderful job. I have retrained the part segmentation model that you implemented in the repo "https://github.com/huanghoujing/PyTorch-Encoding", but my result is only pixAcc: 0.8866, mIoU: 0.6208. It is much worse than the released model (pixAcc: 0.9034, mIoU: 0.6670). So I wonder whether the training hyper-params is different from yours. I have selected the default hyper-params as follows: CUDA_VISIBLE_DEVICES=0 \ python experiments/coco_part/train.py \ --norm_layer bn \ --train-split train \ --batch-size 16 \ --test-batch-size 16 \ --exp_dir exp/train

wlw208dzy commented 5 years ago

I found the reason. The train-split parameter you selected is train_market1501_cuhk03_duke_style. Thanks!