https://github.com/sloweyyy/emotionsense

EmotionSense is an application that predicts facial expressions of humans through pictures.
https://github.com/sloweyyy/emotionsense

artificial-intelligence cv machine-learning tensorflow

Last synced: 16 days ago
JSON representation

EmotionSense is an application that predicts facial expressions of humans through pictures.

• Host: GitHub
• URL: https://github.com/sloweyyy/emotionsense
• Owner: sloweyyy
• Created: 2024-06-12T14:03:03.000Z (6 months ago)
• Default Branch: master
• Last Pushed: 2024-07-20T06:32:27.000Z (5 months ago)
• Last Synced: 2024-12-07T21:48:47.107Z (16 days ago)
• Topics: artificial-intelligence, cv, machine-learning, tensorflow
• Language: TypeScript
• Homepage:
• Size: 680 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Welcome to EmotionSense 👋

EmotionSense is an application that predicts facial expressions of humans through pictures. This project combines the power of machine learning and user-friendly interface to provide an insightful tool for understanding emotions conveyed through facial expressions.

## Project Overview

EmotionSense leverages a pre-trained machine learning model to analyze facial features in images and classify them into various emotional categories. The application is built using React Native for a cross-platform experience and utilizes a backend server for image processing and communication.

## Get Started

**Frontend:**

1. **Install dependencies:**

    ```bash

    npm install

    ```

2. **Start the app:**

    ```bash

    npx expo start

    ```

**Backend:**

The backend code is hosted on a separate repository: [Here](https://github.com/sloweyyy/EmotionSenseBackend)

**Machine Learning Model:**

The machine learning model used for facial expression recognition is available at: [Here](https://github.com/sloweyyy/Facial-expression-recognition-through-Portrait-Images)

**Research Paper:**

For a detailed explanation of the methodology and performance of the machine learning model, please refer to the research paper: [Facial Emotion Recognition through Portrait Images](https://www.researchgate.net/publication/380533775_Facial_Expression_Recognition_using_Traditional_Machine_Learning_Models)

## Contributing

Contributions to EmotionSense are welcome! If you'd like to contribute to the project, please fork the repository and submit a pull request.

## License

This project is licensed under the MIT License.