Comments (3)
Hello, thanks for mentioning the issue.
I just found out that --custom_data
was not set to True
by default in main.py
. I think that's what caused your issue since custom_data may have been set as False
by default. I fixed this issue now.
You can update your code to the latest commit and try following the instruction section in the readme again. You should not get the issue now.
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Downloaded the latest scripts. Still getting the same error.
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--custom_data
is set to True
by default in the latest commit.
Are you perhaps trying to use A_train.npy
and B_train.npy
by setting --custom_data
to False
? In that case, since those files are not provided and the error would occur. Instead, you can use two directories A
and B
for training. You can refer to step 5 in the instructions section of the readme on how to create two directories A
and B
with the required data.
If the above is not the case (i.e., you did not set --custom_data
to False
), do let me know.
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Related Issues (19)
- 复制模型连接失效 HOT 1
- i keep getting this error whenever i want to train with my own dataset HOT 1
- More training data HOT 1
- Tensorflow version HOT 3
- Color of the images after running extract.py HOT 1
- ValueError: Can't load save_path when it is None. HOT 2
- vgg19.npy not found HOT 2
- Issue in Inference Mode HOT 3
- 请问显存用的很少,训练很慢是什么原因呢? HOT 1
- make3D HOT 1
- tensorflow version issue HOT 2
- issue in training HOT 9
- The replicate.tar.gz file can't be downloaded HOT 2
- When I finished the work,the checkpoint is directory HOT 1
- could Dehaze-GAN apply on image inpainting? HOT 2
- When I run main.py and replicating.py, I meet a same error. HOT 3
- training image size HOT 1
- Time taken to train and system configuration HOT 1
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