Open source computer vision library is an open source computer vision and machine learning library. It was built with a vision to provide basic infrastructure to the computer vision application.
It is a machine learning algorithm used to identify objects in image or video based on the concepts of features proposed by Paul Viola and Michael Jones in 2001.
The algorithm contains four stages:
- Haar Feature Selection
- Creating Intergal Images
- Adaboost Training
- Cascading Classifiers
- Jupyter Notebook
- Python — OpenCV, numpy
- Insert haarcascade_eye.xml & haarcascade_frontalface_default.xml files in the same folder.
- Importing the libraries
- Loading the cascades
- Defining a function that will do the detections
- Doing some Face Recognition with the webcam