metadata
license: agpl-3.0
tags:
- pytorch
- YOLOv8
- Ultralytics
base_model:
- Ultralytics/YOLOv8
library_name: ultralytics
pipeline_tag: image-classification
Race Classification YOLOv8
This model is based on FairFace 0.25 padding variant dataset composed by Microsoft researchers, aiming to reduce bias by better balancing classes in dataset.
Karkkainen, Kimmo, and Joo, Jungseock.
FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age for Bias Measurement and Mitigation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2021, pp. 1548–1558.
FairFace Dataset on GitHub
You also can find their pretrained model here.
This YOLOv8 training is meant only for race classification. I wanted a really really fast model for tagging, and this is likely what it's useful for! I will provide a pipeline for running it on your datasets in future.
| Model | Target | top1_acc | Classes | Dataset size | Training Resolution |
|---|---|---|---|---|---|
| Race-CLS-FairFace_yolov8n | Face: Real | 0.717 | 7(Black, East Asian, Indian, Latino_Hispanic, Middle Eastern, Southeast Asian, White) | ~86740(train), ~10950(val) | 224 |
| Race-CLS-FairFace_yolov8s | Face: Real | 0.721 | 7(Black, East Asian, Indian, Latino_Hispanic, Middle Eastern, Southeast Asian, White) | ~86740(train), ~10950(val) | 224 |
| Race-CLS-FairFace_yolov8m | Face: Real | 0.725 | 7(Black, East Asian, Indian, Latino_Hispanic, Middle Eastern, Southeast Asian, White) | ~86740(train), ~10950(val) | 224 |