-
Notifications
You must be signed in to change notification settings - Fork 35
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Train AnoGAN on pcam dataset in h5 format #18
Comments
Hi, @tymsoncyferki.
First, replace # from torchvision.datasets import ImageFolder
from torchvision.datasets import PCAM Next, change # 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 Then run the following command: python train_wgangp.py "." -f
python train_wgangp.py "." -f --img_size 96 I hope you will go well. |
Thanks a lot. Just wanted to say that every time I tried running |
I'm glad to hear that you managed to get it working! |
Hi @A03ki,
I want to train f-anogan using pcam dataset. I have two questions:
or maybe I have to generate jpgs myself and put them all in the folder?
Thanks
The text was updated successfully, but these errors were encountered: