Comments (5)
Please feel free to use the repo https://github.com/jacobgil/pytorch-grad-cam
from scribformer.
Please feel free to use the repo https://github.com/jacobgil/pytorch-grad-cam
Thank you for your reply. I'm going to try it now!
from scribformer.
Please feel free to use the repo https://github.com/jacobgil/pytorch-grad-cam
I tried it and still have some doubts. In cam you need to set the parameter of the corresponding layer, for example target_layers = [model.layer4[-1]]. May I ask how you set this up? I will be grateful if you can answer!
from scribformer.
You can check the setting in the paper. And we visualize both the encoder and decoder layers.
from scribformer.
You can check the setting in the paper. And we visualize both the encoder and decoder layers.
Thank you for your reply. However, I have made many attempts and still have not been able to visualize the results in your paper. If it is convenient, could you send a copy of the code for the class activation graph visualization to my email? I will be grateful if it is possible! 我的邮箱是[email protected]
from scribformer.
Related Issues (6)
- test problem HOT 3
- dataset
- dataset HOT 1
- dataset preprocess HOT 1
- The direction of FCU in the paper. HOT 1
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from scribformer.