Loading README.md +5 −1 Original line number Diff line number Diff line Loading @@ -180,8 +180,12 @@ Step 3: Create ZIP archive using `dataset_tool.py` from this repository: python dataset_tool.py --source=/tmp/ffhq-unpacked --dest=~/datasets/ffhq.zip # Scaled down 256x256 resolution. # # Note: --resize-filter=box is required to reproduce FID scores shown in the # paper. If you don't need to match exactly, it's better to leave this out # and default to Lanczos. See https://github.com/NVlabs/stylegan2-ada-pytorch/issues/283#issuecomment-1731217782 python dataset_tool.py --source=/tmp/ffhq-unpacked --dest=~/datasets/ffhq256x256.zip \ --width=256 --height=256 --width=256 --height=256 --resize-filter=box ``` **MetFaces**: Download the [MetFaces dataset](https://github.com/NVlabs/metfaces-dataset) and create ZIP archive: Loading Loading
README.md +5 −1 Original line number Diff line number Diff line Loading @@ -180,8 +180,12 @@ Step 3: Create ZIP archive using `dataset_tool.py` from this repository: python dataset_tool.py --source=/tmp/ffhq-unpacked --dest=~/datasets/ffhq.zip # Scaled down 256x256 resolution. # # Note: --resize-filter=box is required to reproduce FID scores shown in the # paper. If you don't need to match exactly, it's better to leave this out # and default to Lanczos. See https://github.com/NVlabs/stylegan2-ada-pytorch/issues/283#issuecomment-1731217782 python dataset_tool.py --source=/tmp/ffhq-unpacked --dest=~/datasets/ffhq256x256.zip \ --width=256 --height=256 --width=256 --height=256 --resize-filter=box ``` **MetFaces**: Download the [MetFaces dataset](https://github.com/NVlabs/metfaces-dataset) and create ZIP archive: Loading