It is based on local binary operator. It is widely used in facial recognition due to its computational simplicity and discriminative power.
It is very efficient texture operator which labels the pixels of an image by thresholding the neighborhood of each pixel and considers the result as a binary number. The steps involved to achieve this are:
- creating dataset
- face acquisition
- feature extraction
- classification
The LBPH algorithm is a part of opencv.
pip install numpy
pip install opencv-python
pip install opencv-contrib-python
- Fork the repository
click on the uppermost button
- Create virtual environment
python -m venv env- Linux
source env/bin/activate
- Windows
env\Scripts\activate- Clone the repository using-
git clone https://github.com/akshitagupta15june/LBPH-Face-Recognition.git
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Install Dependencies
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Execute -
python recognition-part-1.py
python recognition-part-2.py
Note: Make sure you have haarcascade_frontalface_default.xml file