train.py error about pytorch-inpainting-with-partial-conv

[naoto0804]

Thank you for reporting! I'm sorry to update the README.md. The minimum requirement for PyTorch is 0.4.1. Could you install it and try again?

[123liluky]

After installing torch0.4.1, new error is

And I can't find out how to solve it.

[naoto0804]

Could you pull the latest master and try again? I haven't faced such problems currently.

[123liluky]

Thanks for your answering.

1. I found above error was caused by setting --image_size=256 in train.py. Now I am wondering the meaning of the third and forth line of output images in snapshots/default/images.
2. Besides I use 2242243 training images and 2242241 masks. Is it OK? I found generate_data.py generates 3 chanel masks in which pixel value is in [0,255]. But pixels in my masks is 0 or 255, without other values in (0,255).
3. Is the code suitable for inpainting images covered by big maks like below?
   
   I found another code is only suitable for inpainting very small masks like below
   

[naoto0804]

1. I've added the description here.
2. So you mean there are non-black or non-white pixels in the masks and it might harm the performance, right?
3. Please refer to the original paper by the original authors. Personally I think its possible

[123liluky]

After training, I tested the model and got results like below
input image of network:

mask:

inpainting results:

The result is blurry. Do you have any suggestions to generate more plausible results.
loss_tv curve in tensorboard is like below:

[naoto0804]

One general advice is that the hyper-parameters that the author reported are for datasets of natural images like Places2, they might be not suitable for your setting.
I'm sorry if there still remains a bug.

[naoto0804]

In addition, the style/content loss is calculated based on pre-trained VGG. I'm not sure using these losses works for your grayscale images.