Comments (20)
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.
from bmsg-gan.
Could you try updating pytorch to 1.0.0
? I hope this solves the problem.
from bmsg-gan.
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
from bmsg-gan.
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
from bmsg-gan.
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!
from bmsg-gan.
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
from bmsg-gan.
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.
from bmsg-gan.
Could you please try again with python 3.6?
The error comes after the first training log itself.
from bmsg-gan.
Hi, @owang @sridharmahadevan @akanimax @huangzh13
It's same at python3.6 ...
What's wrong to me?
Thanks at any rate .... _;
from bmsg-gan.
OK, I'll try that...
from bmsg-gan.
It works , Thanks a lot.
from @bemoregt
from bmsg-gan.
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 ..
from bmsg-gan.
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 ~
from bmsg-gan.
At current sample state
epoch=227
from bmsg-gan.
from bmsg-gan.
Hi, @bemoregt
Could you tell me something about your celebJapan dataset?
Best regards.
from bmsg-gan.
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.
from bmsg-gan.
@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
from bmsg-gan.
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
from bmsg-gan.
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.
from bmsg-gan.
Related Issues (20)
- When you update this repo with styleGAN HOT 1
- What are the parameters for CIFAR10 dataset? I have been training with lr=0.003, betas=(0,0.99). Even after 5 epochs, I am not getting recognizable results at any resolution.
- pretrained models
- I want to stop and resume the training continuously. HOT 3
- Would you add compute IS and FID code ?? HOT 1
- Why output of torch.cat() is still C channels??
- WGAN-GP for Training MSG_ProGAN is failed HOT 3
- demo.py
- I got HOT 1
- Model collapse HOT 5
- Why smaller batch size results better results? With the epochs increased, the G loss went up? HOT 1
- when I train the model ? The d_loss is always 0.0 ? Is there some problems ? HOT 4
- WGAN-GP loss: averaging penalties or not?
- Can't load images | KeyError: 'SM_CHANNEL_TRAINING' HOT 2
- Error(s) in loading state_dict for DataParallel in generating_samples.py
- How to process the resolution of Flower dataset
- Question regarding higher resolution generation HOT 1
- Question about projecting generated images back to latent space
- MSG-cycleGAN HOT 3
- Msggan quality results
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from bmsg-gan.