Face Recognition

Face Recognition using Haar-Cascade Classifier, OpenCV and Python.

This project is based on face detection and face recognition processes. It is a real time web cam face detection and recognition project which will be used to generate training face images and then detect the known faces. It classifies between known and unknown faces.

Click here to download the project report. You can also find the project report inside docs folder.

Requirements

• Python 3.5
• OpenCV 3.1.0
• Numpy

Outline

This project consist of 3 parts, which are:

1. Creating datasets (datasets.py)
2. Train the model (training.py)
3. Recognize faces (recog.py)

Instructions - How to Run ?

• First run datasets.py to generate datasets. Make sure that it creates two folders(datasets and trainer). The ‘datasets’ folder contains the grayscale images.

• Supply proper ID for the face before running training.py.

• Run recog.py and don’t forget to set each person’s face to unique ID.

• If you have more face to be include, change the ID and run the code again.

Need help?

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