YuNet is a light-weight, fast and accurate face detection model, which achieves 0.834(AP_easy), 0.824(AP_medium), 0.708(AP_hard) on the WIDER Face validation set.
Notes:
- Model source: here.
- For details on training this model, please visit https://github.com/ShiqiYu/libfacedetection.train.
- This ONNX model has fixed input shape, but OpenCV DNN infers on the exact shape of input image. See opencv#44 for more information.
Results of accuracy evaluation with tools/eval.
| Models | Easy AP | Medium AP | Hard AP |
|---|---|---|---|
| YuNet | 0.8498 | 0.8384 | 0.7357 |
| YuNet quant | 0.7751 | 0.8145 | 0.7312 |
*: 'quant' stands for 'quantized'.
Run the following command to try the demo:
# detect on camera input
python demo.py
# detect on an image
python demo.py --input /path/to/image
All files in this directory are licensed under MIT License.