# Laion-Face

[LAION-Face](https://github.com/FacePerceiver/LAION-Face) is the human face subset of [LAION-400M](https://laion.ai/laion-400-open-dataset/), it consists of 50 million image-text pairs. Face detection is conducted to find images with faces. Apart from the 50 million full-set(LAION-Face 50M), there is a 20 million sub-set(LAION-Face 20M) for fast evaluation. 

LAION-Face is first used as the training set of [FaRL](https://github.com/FacePerceiver/FaRL), which provides powerful pre-training transformer backbones for face analysis tasks.

For more details, please check the offical repo at https://github.com/FacePerceiver/LAION-Face .

## Download and convert metadata
```bash
wget -l1 -r --no-parent https://the-eye.eu/public/AI/cah/laion400m-met-release/laion400m-meta/
mv the-eye.eu/public/AI/cah/laion400m-met-release/laion400m-meta/ .
wget https://huggingface.co/datasets/FacePerceiver/laion-face/resolve/main/laion_face_ids.pth
wget https://raw.githubusercontent.com/FacePerceiver/LAION-Face/master/convert_parquet.py
python convert_parquet.py ./laion_face_ids.pth ./laion400m-meta ./laion_face_meta
```

## Download the images with img2dataset
When metadata is ready, you can start download the images.

```bash
wget https://raw.githubusercontent.com/FacePerceiver/LAION-Face/master/download.sh
bash download.sh ./laion_face_meta ./laion_face_data
```

Please be patient, this command might run over days, and cost about 2T disk space, and it will download 50 million image-text pairs as 32 parts.

- To use the **LAION-Face 50M**, you should use all the 32 parts.
- To use the **LAION-Face 20M**, you should use these parts.
    ```
    0,2,5,8,13,15,17,18,21,22,24,25,28
    ```

checkout `download.sh` and [img2dataset](https://github.com/rom1504/img2dataset) for more details and parameter setting.




region:us
{}
TAGS
#region-us 

# Laion-Face

LAION-Face is the human face subset of LAION-400M, it consists of 50 million image-text pairs. Face detection is conducted to find images with faces. Apart from the 50 million full-set(LAION-Face 50M), there is a 20 million sub-set(LAION-Face 20M) for fast evaluation. 

LAION-Face is first used as the training set of FaRL, which provides powerful pre-training transformer backbones for face analysis tasks.

For more details, please check the offical repo at URL .

## Download and convert metadata


## Download the images with img2dataset
When metadata is ready, you can start download the images.



Please be patient, this command might run over days, and cost about 2T disk space, and it will download 50 million image-text pairs as 32 parts.

- To use the LAION-Face 50M, you should use all the 32 parts.
- To use the LAION-Face 20M, you should use these parts.
    

checkout 'URL' and img2dataset for more details and parameter setting.




# Laion-Face

LAION-Face is the human face subset of LAION-400M, it consists of 50 million image-text pairs. Face detection is conducted to find images with faces. Apart from the 50 million full-set(LAION-Face 50M), there is a 20 million sub-set(LAION-Face 20M) for fast evaluation. 

LAION-Face is first used as the training set of FaRL, which provides powerful pre-training transformer backbones for face analysis tasks.

For more details, please check the offical repo at URL . ## Download and convert metadata ## Download the images with img2dataset
When metadata is ready, you can start download the images.



Please be patient, this command might run over days, and cost about 2T disk space, and it will download 50 million image-text pairs as 32 parts.

- To use the LAION-Face 50M, you should use all the 32 parts.
- To use the LAION-Face 20M, you should use these parts.
    

checkout 'URL' and img2dataset for more details and parameter setting.
TAGS
#region-us 
 # Laion-Face

LAION-Face is the human face subset of LAION-400M, it consists of 50 million image-text pairs. Face detection is conducted to find images with faces. Apart from the 50 million full-set(LAION-Face 50M), there is a 20 million sub-set(LAION-Face 20M) for fast evaluation. 

LAION-Face is first used as the training set of FaRL, which provides powerful pre-training transformer backbones for face analysis tasks.

For more details, please check the offical repo at URL . ## Download and convert metadata ## Download the images with img2dataset
When metadata is ready, you can start download the images.



Please be patient, this command might run over days, and cost about 2T disk space, and it will download 50 million image-text pairs as 32 parts.

- To use the LAION-Face 50M, you should use all the 32 parts.
- To use the LAION-Face 20M, you should use these parts.
    

checkout 'URL' and img2dataset for more details and parameter setting.