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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.
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