SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
Note:
- SFace is contributed by Yaoyao Zhong.
- Model files encode MobileFaceNet instances trained on the SFace loss function, see the SFace paper for reference.
- ONNX file conversions from original code base thanks to Chengrui Wang.
- (As of Sep 2021) Supporting 5-landmark warping for now, see below for details.
Results of accuracy evaluation with tools/eval.
Models | Accuracy |
---|---|
SFace | 0.9940 |
SFace quant | 0.9932 |
*: 'quant' stands for 'quantized'.
NOTE: This demo uses ../face_detection_yunet as face detector, which supports 5-landmark detection for now (2021sep).
Run the following command to try the demo:
# recognize on images
python demo.py --input1 /path/to/image1 --input2 /path/to/image2
# get help regarding various parameters
python demo.py --help
All files in this directory are licensed under Apache 2.0 License.