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3 changes: 1 addition & 2 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -30,8 +30,7 @@ Karkkainen, K., & Joo, J. (2021). FairFace: Face Attribute Dataset for Balanced
```
pip install dlib
```
- Download our models
Download our pretrained models from [here](https://drive.google.com/drive/folders/1F_pXfbzWvG-bhCpNsRj6F_xsdjpesiFu?usp=sharing) and save it in the same folder as where predict.py is located. Two models are included, race_4 model predicts race as White, Black, Asian and Indian and race_7 model predicts races as White, Black, Latino_Hispanic, East, Southeast Asian, Indian, Middle Eastern.
- Download our pretrained models from [here](https://drive.google.com/drive/folders/1F_pXfbzWvG-bhCpNsRj6F_xsdjpesiFu?usp=sharing) and save it in the same folder as where predict.py is located. Two models are included, race_4 model predicts race as White, Black, Asian and Indian and race_7 model predicts races as White, Black, Latino_Hispanic, East, Southeast Asian, Indian, Middle Eastern.
- Unzip the downloaded FairFace model as well as dlib face detection models in dlib_models.
- Prepare the images
- prepare a csv and provide the paths of testing images where the colname name of testing images is "img_path" (see our [template csv file](https://github.com/dchen236/FairFace/blob/master/test_imgs.csv).
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