Live human-face recognition with OpenCV using Haar Cascade Classifiers; frontal_face dataset and LBPH Algorithm, works with small computing devices.
- Run
face_add.pyto genrate face samples, add id - Train the sample images using
face_train.py - Run facial recogniton script with
facial_recognition.py - Control confidence/success level in
face_recognitionwhen face is detected using LBPH - Edit/add id names in
usr_id_labelin facial_recognition.py
- Face images are stored inside images
- Trained data is located in
train>data.yml
- OpenCV, install using
pip install opencv-contrib-python
-
LBPH docs compressive guide. Sample code is in C++, you might be interested.
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Haarcascades pre-trained dataset useful for various subjects.
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Marcelo for introducing confidences level.
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Aswinth similar guide using Raspberry Pi.