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README.md
face_data.py
face_rec.py
haarcascade_frontalface_alt.xml
haarcascade_frontalface_default.xml

README.md

It uses KNN algorithm for face detection

K-NN

K nearest neighbors is a simple algorithm that stores all available cases and classifies new cases based on a similarity measure (e.g., distance functions). KNN has been used in statistical estimation and pattern recognition already in the beginning of 1970’s as a non-parametric technique. A case is classified by a majority vote of its neighbors, with the case being assigned to the class most common amongst its K nearest neighbors measured by a distance function. If K = 1, then the case is simply assigned to the class of its nearest neighbor.

knn_similarity

Code tutorial

https://youtu.be/yZ-hH89H5Tc

Project demo

https://youtu.be/FH79poerjVc

Haar-cascade Detection in OpenCV

OpenCV comes with a trainer as well as detector. If you want to train your own classifier for any object like car, planes etc. We use haarcascade_frontalface_default.xml to detect faces in image

Collecting Face data

For collecting data of differents faces "face_data.py" file is used and faces are stored in the form of Numpy array

Face recognisation

For live face recognisation "face_rec.py" file is used which usses K-NN algorithm to check the given face