Usage: fid.py [OPTIONS] COMMAND [ARGS]...

  Calculate Frechet Inception Distance (FID).

  Examples:

  # Generate 50000 images and save them as fid-tmp/*/*.png
  torchrun --standalone --nproc_per_node=1 generate.py --outdir=fid-tmp --seeds=0-49999 --subdirs \
      --network=https://nvlabs-fi-cdn.nvidia.com/edm/pretrained/edm-cifar10-32x32-cond-vp.pkl

  # Calculate FID
  torchrun --standalone --nproc_per_node=1 fid.py calc --images=fid-tmp \
      --ref=https://nvlabs-fi-cdn.nvidia.com/edm/fid-refs/cifar10-32x32.npz

  # Compute dataset reference statistics
  python fid.py ref --data=datasets/my-dataset.zip --dest=fid-refs/my-dataset.npz

Options:
  --help  Show this message and exit.

Commands:
  calc  Calculate FID for a given set of images.
  ref   Calculate dataset reference statistics needed by 'calc'.


Usage: fid.py calc [OPTIONS]

  Calculate FID for a given set of images.

Options:
  --images PATH|ZIP  Path to the images  [required]
  --ref NPZ|URL      Dataset reference statistics   [required]
  --num INT          Number of images to use  [default: 50000; x>=2]
  --seed INT         Random seed for selecting the images  [default: 0]
  --batch INT        Maximum batch size  [default: 64; x>=1]
  --help             Show this message and exit.


Usage: fid.py ref [OPTIONS]

  Calculate dataset reference statistics needed by 'calc'.

Options:
  --data PATH|ZIP  Path to the dataset  [required]
  --dest NPZ       Destination .npz file  [required]
  --batch INT      Maximum batch size  [default: 64; x>=1]
  --help           Show this message and exit.