Comments (3)
You mean to optimize a real image instead of optimizing the random noise? It doesn't matter what image you are optimizing (noise, real image, all white, all pink) It should work. Double check your code.
from pytorch-cnn-visualizations.
I wonder why this input is self.processed_image, it seems that it has nothing to do with the iteration
from pytorch-cnn-visualizations.
Optimizer is optimizing self.processed_image and at each iteration it updates this image. Howcome it has nothing to do with the iteration?
optimizer = Adam([self.processed_image], lr=0.1, weight_decay=1e-6)
for i in range(1, x):
optimizer.zero_grad()
...
loss = -torch.mean(self.conv_output)
loss.backward()
optimizer.step()
...
from pytorch-cnn-visualizations.
Related Issues (20)
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- RUN
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