Machine Learning Project to recognise faces with Real time face liveliness detection.
Build with dlib's face-recognition model
- dlib_face_recognition_resnet_model_v1.dat
- shape_predictor_68_face_landmarks.dat
- opencv classifier haarcascade_frontalface_default.xml
- opencv haarcascade_eye_tree_eyeglasses.xml
- opencv haarcascade_lefteye_2splits.xml
- opencv haarcascade_righteye_2splits.xml
- Clone this repository
https://github.com/arijitiiest/Face-Recognition - Download the models and copy to
modelsfolder - Download opencv classifier and copy to
opencvfolder$ pip install requirements.txt $ mkdir data/training_images
- create images, image name should be person name
$ python create_encodings.py $ python webcam.py
- Thanks to Davis King for creating dlib and for providing the trained facial feature detection and face encoding models used in this project.
- Thanks to Adam Geitgey whose blog inspired me to make this project.
- Thanks to Jordon Van Eetveldt for this blog post for the idea to detect liveliness of face.