Name		Name	Last commit message	Last commit date
parent directory ..
example_outputs		example_outputs
README.md		README.md
demo.py		demo.py
facial_expression_recognition_mobilefacenet_2022july.onnx		facial_expression_recognition_mobilefacenet_2022july.onnx
facial_expression_recognition_mobilefacenet_2022july_int8.onnx		facial_expression_recognition_mobilefacenet_2022july_int8.onnx
facial_fer_model.py		facial_fer_model.py

README.md

Progressive Teacher

Note:

Progressive Teacher is contributed by Jing Jiang.
MobileFaceNet is used as the backbone and the model is able to classify seven basic facial expressions (angry, disgust, fearful, happy, neutral, sad, surprised).
facial_expression_recognition_mobilefacenet_2022july.onnx is implemented thanks to Chengrui Wang.

Results of accuracy evaluation on RAF-DB.

Models	Accuracy
Progressive Teacher	88.27%

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 the facial expression on images
python demo.py --input /path/to/image -v

Note: Zoom in to to see the recognized facial expression in the top-left corner of each face boxes.

All files in this directory are licensed under Apache 2.0 License.