The best option is to source the originals again at a higher size. Or you can ignore it, use a high quality upscaler, remove the images, or reduce the `resolution` you're training. You might be ok if it is very small percentage of your dataset, but it is something you should check on.
### Errors with PIL
Run this script to check images if your training crashes and PIL or you get any errors that seems image related:
This will help identify invalid or malformatted images. You can then try using a typical image editor (Photoshop, Gimp, Paint.net, etc.) to fix them, or simply delete them.