I have met this error when run train.py ... about bmsg-gan HOT 20 OPEN

Could you please show what is the version of your python, torch and numpy?
Please try updating to the latest versions for torch and numpy.
The code is tested for python == 3.6.5.
Please let me know if you still face this issue.

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Could you try updating pytorch to 1.0.0? I hope this solves the problem.

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@bemoregt,

I am glad that it is working now. Just wanted to point out that since you are synthesizing Japanese celebs at 256 x 256 resolution, the latent_size = 128 might not be enough to make the generator expressive enough. Please try to use latent_size=512.

Also, if you are able to get good results, please feel free to share these with us, I'll be happy to include them on the readme like @huangzh13's cartoons 😄.

Hope this helps.

👍
Best regards,
@akanimax

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@bemoregt,

I see. There is no handling of Grayscale image case. I'll fix this by tomorrow when I get access to my code (I am currently travelling). For now, could you please remove all the grayscale (black and white) images from your dataset?

Thanks.
@akanimax

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@bemoregt,

I see. There is no handling of Grayscale image case. I'll fix this by tomorrow when I get access to my code (I am currently travelling). For now, could you please remove all the grayscale (black and white) images from your dataset?

Thanks.
@akanimax

Hi, @akanimax

I'd be happy to test MSG-GAN on radiology data.

Is there a way to allow for output grayscale images in your next update?

Thanks!

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@Pascal900,

Great to hear that you would like to use the MSG-GAN for radiology data. Earlier when I said that I'll handle the Grayscale case, I meant just ignoring the grayscale images from the dataset. But for your case, it seems that all the images in the dataset would be grayscale. Will create a new branch for this development. It is a new addition to the network. Till then one thing you could try is to make RGB images from your gray-scale ones. The network will just learn to output the same values for the R, G and B channels. I have tried it before on MNIST data, it worked pretty well.

Please feel free to ask if you have any more queries.

Best regards,
@akanimax

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Hi, @owang @sridharmahadevan @akanimax @huangzh13

My Environment:

Ubuntu 17.x x64, Python 3.6.7, CUDA 10.1, Pytorch 0.4.1, numpy 1.15.4

Thanks.

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Could you please try again with python 3.6?
The error comes after the first training log itself.

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Hi, @owang @sridharmahadevan @akanimax @huangzh13

It's same at python3.6 ...

What's wrong to me?

Thanks at any rate .... _;

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OK, I'll try that...

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It works , Thanks a lot.

from @bemoregt

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But, ...

Elapsed [0:04:07.511359] batch: 108 d_loss: 0.040370 g_loss: 18.472263
Elapsed [0:04:15.999767] batch: 112 d_loss: 0.000000 g_loss: 12.169998
Elapsed [0:04:24.425038] batch: 116 d_loss: 0.053961 g_loss: 16.491339
Elapsed [0:04:32.862795] batch: 120 d_loss: 0.000000 g_loss: 11.238050
Traceback (most recent call last):
File "train.py", line 254, in
main(parse_arguments())
File "train.py", line 248, in main
start=args.start
File "/home/oem/BMSG-GAN/sourcecode/MSG_GAN/GAN.py", line 417, in train
for (i, batch) in enumerate(data, 1):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 637, in next
return self._process_next_batch(batch)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 658, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
RuntimeError: Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 138, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 209, in default_collate
return torch.stack(batch, 0, out=out)
RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 0. Got 3 and 1 in dimension 1 at /pytorch/aten/src/TH/generic/THTensorMoreMath.cpp:1307

another error happens ..

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Hi, @akanimax

OK, I see.

I could understand my data's problems...

My images include some rotated & zero-padded images.

Because of those images, May be It happens...

Many Thanks ~

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@akanimax

At current sample state
epoch=227

https://3.bp.blogspot.com/-KY44bqw_nd8/XMD7JNG-6SI/AAAAAAABAkY/lI9VEv8nhWw4xbMFh4RI8tb8nhkjZuImACLcBGAs/s1600/epoch227.png

https://3.bp.blogspot.com/-KY44bqw_nd8/XMD7JNG-6SI/AAAAAAABAkY/lI9VEv8nhWw4xbMFh4RI8tb8nhkjZuImACLcBGAs/s1600/epoch227.png

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Hi, @bemoregt
Could you tell me something about your celebJapan dataset?

Best regards.

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Hi, @huangzh13 @akanimax

Ok, My celebJapan dataset's information is..

• Total 3,591 images, including Horizontal Flipped Augmented.
• 100x100 sized Color Image
• about 20KB file size
• jpg+png format.

Is this too small dataset for MSG-GAN?

Thanks.

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@bemoregt,
The results seem good to me given the size of your dataset. BTW, could you share a full size sheet of the generated images. The one you shared seems to be a screenshot of the image viewer. I think you should let it train for longer and one more thing you could try is to calculate the FID of the models for an objective evalutaion. The data size ok for the resolution. Also try increasing the latent size.
Hope this helps.

Best regards,
@akanimax

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Hi, @akanimax @huangzh13 @owang @sridharmahadevan

It seems that rotated face is very weak for generation using MSG-GAN.

What is the image augmentation technics suitable for face generating GAN?

Thanks .

from @bemoregt

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Since I am also working on grayscale radiology data and needed support for that immediately, I've implemented this in #14. @Pascal900, maybe you can try my branch if this use case is still relevant to you. I'd be happy to hear feedback.

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