Hi, I'm trying to use CyCADA on my own custom datasets. I've set them up according to the cylcegan tutorial (https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/docs/tips.md) and adapted them into cycada. If I turn off the semantic consistency loss, the model will train fine. But when I turn it on, I get an error:
However if I set the load_size to 32 (the same size as the SVHN/MNIST demo) I will not get the size mismatch error, but it is not desirable to use images so small. If I start training with the SVHN/MNIST, but set the images larger than 32, the code will not crash. How do I process my datasets or change the feature extraction so I can use custom data with larger images?
Hi, I'm trying to use CyCADA on my own custom datasets. I've set them up according to the cylcegan tutorial (https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/docs/tips.md) and adapted them into cycada. If I turn off the semantic consistency loss, the model will train fine. But when I turn it on, I get an error:
However if I set the load_size to 32 (the same size as the SVHN/MNIST demo) I will not get the size mismatch error, but it is not desirable to use images so small. If I start training with the SVHN/MNIST, but set the images larger than 32, the code will not crash. How do I process my datasets or change the feature extraction so I can use custom data with larger images?