readme.md

Face Detection Using OpenCV

This Project is built on Python to detect Faces for a Given input image. Using Haar-Cascade Classifier the faces were detected and using LBPH face recognizer the model was trained to store two classes of images.

Dependencies

I suggest to run it on virtual environment to avoid previous dependencies.

pip install virtualenv
virtualenv [foldername]
source activate foldername/bin/activate

Extract the zip file and place it in filename folder.

Then install OpenCV libraries.

pip install opencv-python
pip install opencv-contrib-python

File Structure

After Extracting the zip file in [foldername]. This file structure Appears.

A typical top-level directory layout

.
├── bin                   # Virtual Environment files
├── include               # Virtual Environment files
├── lib                   # Virtual Environment files
├── Q3                    # Project Root Folder
└── README.md

Contents of Project folder is down below.

Project folder

.
├── Test                    # Test files 
│   ├── example.jpg
│   ├── tomlookalike.jpg
│   └── tom1.jpeg 
├── Train
│   ├── 0                   # Contains 200 images
│   │   ├──1.jpg
│   │   └──...
│   └── 1                   # Contains 214 images
│       ├──1.jpg
│       └──...
├── haarcascade_frontalface_default.xml   # Haar-cascade file
├── test.py                 # Run this to get output
├── train.py                # Contains logic for face detection and training using 
│                             LBPH Recognizer
└── trainData.yml           # Contains labels of trained data in yml format. 

Usage

python test.py Test/example.jpg

Add new images in your desired folder and run the above code accordingly.

References

Face Recognition with OpenCV.