Thanks for uploading your code and dataset.
After a short view I'm considering your predicting process is like: generating masks with scripts on test data, using test data and their masks to feed into trained model to predict.
But I was confused that in your test.py file, you get dataset like this:
Is it fair to distinguish masks by label_name in the testing process?
I also wonder how to create Mask/ folder when you predict fake images that donot have corresponding real images?
If i misunderstand anything please correct me, thanks a lot!
Thanks for uploading your code and dataset. After a short view I'm considering your predicting process is like: generating masks with scripts on test data, using test data and their masks to feed into trained model to predict. But I was confused that in your test.py file, you get dataset like this:
then you differ masks of real and fake photos by using their labels in dataset.py:
Is it fair to distinguish masks by label_name in the testing process? I also wonder how to create Mask/ folder when you predict fake images that donot have corresponding real images?
If i misunderstand anything please correct me, thanks a lot!