Usage: dataset_tool.py [OPTIONS] Convert an image dataset into a dataset archive usable with StyleGAN2 ADA PyTorch. The input dataset format is guessed from the --source argument: --source *_lmdb/ - Load LSUN dataset --source cifar-10-python.tar.gz - Load CIFAR-10 dataset --source path/ - Recursively load all images from path/ --source dataset.zip - Recursively load all images from dataset.zip The output dataset format can be either an image folder or a zip archive. Specifying the output format and path: --dest /path/to/dir - Save output files under /path/to/dir --dest /path/to/dataset.zip - Save output files into /path/to/dataset.zip archive Images within the dataset archive will be stored as uncompressed PNG. Image scale/crop and resolution requirements: Output images must be square-shaped and they must all have the same power- of-two dimensions. To scale arbitrary input image size to a specific width and height, use the --width and --height options. Output resolution will be either the original input resolution (if --width/--height was not specified) or the one specified with --width/height. Use the --transform=center-crop or --transform=center-crop-wide options to apply a center crop transform on the input image. These options should be used with the --width and --height options. For example: python dataset_tool.py --source LSUN/raw/cat_lmdb --dest /tmp/lsun_cat \ --transform=center-crop-wide --width 512 --height=384 Options: --source PATH Directory or archive name for input dataset [required] --dest PATH Output directory or archive name for output dataset [required] --max-images INTEGER Output only up to `max-images` images --resize-filter [box|lanczos] Filter to use when resizing images for output resolution [default: lanczos] --transform [center-crop|center-crop-wide] Input crop/resize mode --width INTEGER Output width --height INTEGER Output height --help Show this message and exit.