Train AnoGAN on pcam dataset in h5 format

[tymsoncyferki]

Train AnoGAN on pcam dataset in h5 format

[tymsoncyferki]

Thanks a lot.

Just wanted to say that every time I tried running python train_wgangp.py "." -f my computer crashed after couple of gigabytes downloaded. I guess it was a problem with memory leak. However I have downloaded PCAM manually, pasted it in pcam folder and I guess it's working:)

[A03ki]

Hi, @tymsoncyferki.
Thanks for using this repository.

1. If you use the PCAM dataset, you can modify code as follows.

First, replace ImageFolder with PCAM in your_own_dataset.

# from torchvision.datasets import ImageFolder
from torchvision.datasets import PCAM

Next, change dataset = ImageFolder() to dataset = PCAM().

# dataset = ImageFolder(opt.train_root, transform=transform)
dataset = PCAM(opt.train_root, split="train", transform=transform,
               download=opt.force_download)

If the file is your_own_dataset/save_compared_images.py or test_anomaly_detection.py, replace split="train" with split="test"and opt.train_root with opt.test_root.

Then run the following command:

python train_wgangp.py "." -f

2. Yes, it will work. It will resize 96x96x3 to 64x64x3. If you want to train models on 96x96x3 images, please include the following option --img_size 96.

python train_wgangp.py "." -f --img_size 96

I hope you will go well.

[A03ki]

I'm glad to hear that you managed to get it working!