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

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python face-recognition faces-detection pytorch siamese-neural-network neural-network classification-algorithms eigenfaces haar-cascade-classifier machine-learning deep-learning siamese-network

face_detection_and_recognition's Introduction

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

IMAGE ALT TEXT HERE

Phase 2

  1. 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

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