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Face detection performed with the help of the Haar Cascade Frontal Face Model.
Implemented with OpenCV (Python 3) in Python, this repository contains code that enables the use of Computer Vision algorithms and facilities. These faces can be further used as inputs to a facial recognition model.
The Haar-Cascade algorithm is a machine learning object detection algorithm, that can be used to identify specific objects based upon the features that are found in an image or many images played together (i.e., video).
This package assumes you use Python 3.x.
Expected package dependencies are listed in the "requirements.txt" file for PIP, you need to run the following command to get dependencies:
pip install -r requirements.txt
Use a folder with one/multiple photo(s) with one or more faces, as an input for the algorithm.
Run main.py.
> Enter Path Where Images Exists.
C:\SPECIFY_PATH_OF_EXISTANCE
> Enter Path Where You Would Like to Push.
C:\SPECIFY_PATH_TO_PUSH
Photos corresponding to individual faces get pushed to the folder specified in path
If you found any mistakes in my code, or if you can enhance the quality of documention, please feel free to contribute! Here are 3 steps to contributing.
| Name | Github | Phone | ||
|---|---|---|---|---|
| Viswalahiri Swamy Hejeebu | @viswalahiri | @viswalahiri | (+91) 630-152-9655 |
Distributed under the MIT License. See LICENSE for more information.