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--- |
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task_categories: |
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- image-classification |
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pretty_name: MS-Celeb-1M |
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size_categories: |
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- 1M<n<10M |
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--- |
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# MS-Celeb-1M (v3) |
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This dataset is introduced in the Lightweight Face Recognition Challenge at ICCV 2019. [Paper](https://openaccess.thecvf.com/content_ICCVW_2019/papers/LSR/Deng_Lightweight_Face_Recognition_Challenge_ICCVW_2019_paper.pdf). |
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There are 5,179,510 images and 93,431 ids. All images are aligned based on facial landmarks predicted by RetinaFace and resized to 112x112. |
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This was downloaded from `https://github.com/deepinsight/insightface/tree/master/recognition/_datasets_` (MS1M-RetinaFace). The original dataset format is MXNet RecordIO. It was converted to WebDataset in this copy here. There are 100 shards in total. |
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## Usage |
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```python |
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import webdataset as wds |
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url = "https://huggingface.co/datasets/gaunernst/ms1mv3-wds/resolve/main/ms1mv3-{{0000..0099}}.tar" |
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ds = wds.WebDataset(url).decode("pil").to_tuple("jpg", "cls") |
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img, label = next(iter(ds)) |
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``` |
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