Comments (6)
yunxiaoshi
commented on August 20, 2024
As you say, the implementation is strictly mirrored from the paper, if you take a closer look you will see that the implementation is correct.
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VoVAllen
commented on August 20, 2024
Sorry for the mistake. I realized it's right. Thanks!
Another minor problem I found is Dropout. Due to pytorch features, you need to explicit call model.eval() in valuation and test period to turn the Dropout into right mode to get right forward result.
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yunxiaoshi
commented on August 20, 2024
Fixed the dropout issue
I didn't see any typo that you mentioned
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VoVAllen
commented on August 20, 2024
可能是我看错了……应该没有typo……
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VoVAllen
commented on August 20, 2024
Also I see you might also need to add model.eval() at valuation period
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luqiang360
commented on August 20, 2024
The EMD loss still seems to be wrong, my opinion is the sum operation should be inside of torch.abs
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Related Issues (20)
- hi, my training process looks OK, the final loss is about 0.0988. but the result seems random HOT 1
- fully connected layers HOT 2
- About AVA dataset HOT 8
- Some mistake in main.py
- It requires me to install so much packages
- No such file or directory - Please Help HOT 6
- The torchvision pretrained VGG-16 requires normalization of inputs and you do not do this HOT 3
- 你好，我没有训练模型的硬件条件，但是还是想用图像美学。可以分享一下，训练好的权重文件吗？？？ HOT 1
- how to test myself photo? HOT 2
- Is there pretrained weight for InceptionNet?
- The score for the same picture varies HOT 5
- the google drive link for pretrained model is invalid HOT 8
- The link to the pre-trained model is not working HOT 9
- About the test.py
- csv文件
- AVA dataset download
- test_labels.csv HOT 16
- userwaring: possibly corrupt EXIF data
- Pre-trained model link not working HOT 1
- who can share the pre-train model? HOT 2
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