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VGGFace2

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This dataset contains images or recordings of real, identifiable people that third parties collected from the web. Copyright in the media (images, audio and video) stays with its original owners, and access here is not a licence to it. Some parts, such as the original publishers' annotations, carry their own licences; these conditions do not limit any rights those licences give you. Recognition evaluation on the dataset itself is allowed. Read the dataset card before use.

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Bounded streaming

datasets==5.0.0 does not execute this repository's remote Python loader through load_dataset(). Clone code and metadata without downloading Git LFS objects, then use the project-side module directly:

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/ProgramComputer/VGGFace2

Archive bytes are read sequentially and are not extracted or cached.

from VGGFace2 import load_streaming

dataset = load_streaming(
    split="train",
    revision="ad5f6b5a5f560621fd7efb9b79c956d27d427a08",
    cache_dir="./metadata-cache",
    scratch_dir="./stream-scratch",
)
first_hundred = list(dataset.take(100))

@article{DBLP:journals/corr/abs-1710-08092,
  author       = {Qiong Cao and
                  Li Shen and
                  Weidi Xie and
                  Omkar M. Parkhi and
                  Andrew Zisserman},
  title        = {VGGFace2: {A} dataset for recognising faces across pose and age},
  journal      = {CoRR},
  volume       = {abs/1710.08092},
  year         = {2017},
  url          = {http://arxiv.org/abs/1710.08092},
  eprinttype    = {arXiv},
  eprint       = {1710.08092},
  timestamp    = {Wed, 04 Aug 2021 07:50:14 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-1710-08092.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
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