Comments (3)
For the complex transformation, I would recommend a small lambda_cycle (e.g. 1 or 2). Could you show some your results as well as loss plots? How big are your G and D losses?
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@junyanz how much the lambda_cycle you use for horse2zebra?
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Hey @junyanz, this is Rohit. First, thanks for your code. It's really helpful.
I trained your model on around 1.5 k images at A and B sides. I am observing loss as attached image.
Do I expect Discriminators' errors to go to 0.5 ideally? If yes, should I train for more epochs or try changing lambda_cycle? Please suggest, how can I improve..
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Related Issues (20)
- Source of summer2winter_yosemite
- Blurry image B, but clear image A reconstruction HOT 1
- try to use my own dataset on colab but fail.
- CSV file
- Test size is smaller than train size
- test is failing with libjpeg pkg is missing
- cuDNN lib error when selected CPU
- torch install
- cublas runtime error : library not initialized at /home/username/torch/extra/cutorch/lib/THC/THCGeneral.c:405
- Are there some points between "Tensorflow-simple" and "official implementation"?
- __global__ function call is not configured HOT 1
- Could you provide the tutorial and source codes of evaluation models for CycleGAN and CyCADA?
- network applicability HOT 1
- About the loss of the generator HOT 1
- Failure cases portraying war criminal
- About generate video
- pythorch to onnx conversion HOT 1
- Holes showing up while training HOT 4
- combine_A_and_B issue
- Google Colab Notebook
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