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https://github.com/NNNNAI/VGGFace2-HQ
What this repository contains
train/VGGFac01.ziptotrain/VGGFac10.zip: the VGGFace2-HQ project's training release, downloaded from its Google Drive and re-packaged into ten ZIP files.test/test.zip: not part of the project's release. It was generated for this repository from the VGGFace2 test set with the project's own scripts: FFHQ alignment (scripts/crop_align_vggface2_FFHQalign.py), then GFPGAN restoration (scripts/inference_gfpgan_forvggface2.pywithGFPGANCleanv1-NoCE-C2.pth). It holds 61,841 restored images.
Removal requests
If you appear in this dataset, or hold rights in any of its media, and want it removed, open a discussion in this repository's Community tab with the file paths or IDs involved.
Bounded streaming
datasets==5.0.0 does not execute loading scripts from the Hub. Clone code and
metadata without downloading Git LFS objects, then import the loader directly:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/ProgramComputer/VGGFace2-HQ
Pin both data revisions when constructing the stream:
from VGGFace2_HQ import load_streaming
dataset = load_streaming(
"train",
revision="ee41c3e64981063524744286b468e739190cfbed",
raw_revision="ad5f6b5a5f560621fd7efb9b79c956d27d427a08",
cache_dir="/bounded/cache",
scratch_dir="/bounded/scratch",
)
first_record = next(iter(dataset))
ZIP shards use bounded HTTP-range reads. A full-shard scratch fallback is
disabled unless allow_full_shard_fallback=True is passed with explicit byte
limits.
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