Faces

Detection and Recognition of faces using ML Classification Algorithms, Neural Networks, Siamese Network and face-recognition library at Python

Phase 1

1. Face Detection using HAAR-LIKE features
2. Finding similarity between two faces using Classification algorithms (1==similar && 0==dissimilar)
3. Using the concept of Principle Component Analysis for building Eigen faces over the dataset lfw_people from sklearn.datasets with min_faces_per_person = 50
4. Using a Neural Network to distinguish between 12 people faces using softmax in the outer layer.
5. Building the same neural network using PyTorch
6. Implement a Siamese Network (Didn't train it)

The above implementations can be found in Faces.ipynb and Siamese_network.ipynb

I have also made a video for explaining the PHASE 1

Phase 2

7. Face Detection and recognition on the webcam. (Done using python library face_recognition)

The above implementation can be found in face_recognition_on_webcam.py