README.md

---
task_categories:
- image-classification
pretty_name: MS-Celeb-1M
size_categories:
- 1M<n<10M
---

# MS-Celeb-1M (v3)

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).

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.

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.

## Usage

```python
import webdataset as wds

url = "https://huggingface.co/datasets/gaunernst/ms1mv3-wds/resolve/main/ms1mv3-{{0000..0099}}.tar"
ds = wds.WebDataset(url).decode("pil").to_tuple("jpg", "cls")

img, label = next(iter(ds))
```