README.md

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Demonstration of different algorithms and operations on faces

Recognition-Algorithms

Despite a variety of open-source face recognition algorithms available, there was no ready-made solution to implement. So In this project all kind of algorithms are implemented and even with various operations that can be implemented in a frontal face. The available algorithms processed only high-resolution static shots and have performed sufficiently well.

There are several approaches for recognizing a face. The algorithm can use statistics, try to find a pattern which represents a specific person or use a convolutional neural network.

Requirements 👇

• Python3.6+
• virtualenv (pip install virtualenv)

Installation 👇

• Create virtual environment-

- `python -m venv env`
- `source env/bin/activate`  (Linux)
- `env\Scripts\activate`  (Windows)
- `pip install -r requirements.txt`

⭐ How to get started?

You can refer to the following articles on the basics of Git and Github.

• Watch this video to get started, if you have no clue about open source
• Forking a Repo
• Cloning a Repo
• How to create a Pull Request
• Getting started with Git and GitHub

💥 How to Contribute in Face-X?

• Take a look at the Existing Issues or create your own Issues!
• Wait for the Issue to be assigned to you.
• Fork the repository

click on the uppermost button

• Clone the repository using-

git clone https://github.com/akshitagupta15june/Face-X.git

• Read the Code of Conduct
• Create a Pull Request which will be reviewed and suggestions would be added to improve it.
• Add Screenshots to help us know what this enhancement/implementation is all about.

Face-X is a part these open source programs❄

Get Started with Open Source programs 👨‍💻

Start Open Source an article by Anush Krishna

❤️ Project Admin

akshitagupta15june 👑 Admin

🌟 Contributors

Thanks goes to these wonderful people ✨✨: