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This application is about facial reading to identify expression points in order to find emotions on our faces. In addition, I'm using the user's audio capture to transcribe while the facial reading is done.

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Face Recognition System

This repository contains a system for facial expression recognition, facial recognition, and age estimation implemented in JavaScript using the face-api library.

Description

The aim of this project is to demonstrate the usage of the face-api library to perform facial expression recognition, facial recognition, and age estimation in images or videos. face-api is a powerful open-source JavaScript library that allows real-time face detection and analysis.

Features

The system offers the following features:

  • Face Detection: Identifies and locates faces in images or videos.

  • Facial Expression Recognition: Recognizes and categorizes the facial expressions of detected faces into categories such as joy, sadness, surprise, anger, and more.

  • Facial Recognition: Performs facial recognition by comparing detected faces with previously registered faces, providing a match.

  • Age Estimation: Estimates the approximate age of a person based on their face.

Installation

  • Clone this repository to your local machine:
git clone https://github.com/omatheusribeiro/facial-recognition.git
  • Navigate to the project directory:
cd facial-recognition

Contribution

Contributions are welcome! If you wish to contribute to this project, follow the steps below:

  1. Fork this repository.
  2. Create a branch for your contribution:
git checkout -b my-contribution
  1. Make the desired changes and commit them:
git commit -m "My contribution"
  1. Push your changes to your fork:
git push origin my-contribution
  1. Open a Pull Request in this repository.

License

This project is licensed under the BSD 3-Clause License.

Acknowledgments

We thank the face-api library for its contribution to this project.

About

This application is about facial reading to identify expression points in order to find emotions on our faces. In addition, I'm using the user's audio capture to transcribe while the facial reading is done.

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