Live human-face recognition with OpenCV using Haar Cascade Classifiers; frontal_face dataset and LBPH Algorithm, works with small computing devices.

• Run face_add.py to 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_recognition when face is detected using LBPH
• Edit/add id names in usr_id_label in 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.

• Haar-cascade Detection

• Cascade Classifier Training

• Haarcascades pre-trained dataset useful for various subjects.

• Marcelo for introducing confidences level.

• Aswinth similar guide using Raspberry Pi.