https://github.com/bananacat123-hue/facial_expression_recognition-sure_trust-
Facial Expression Recognition System using YOLOv9 & Flask. Detects 5 emotions (Angry, Happy, Natural, Sad, Surprised) from images/live camera with mAP50 of 0.731. Features a web interface with file uploads, real-time processing, & emoji feedback. Built with Python, OpenCV, Flask, HTML/CSS/JS. Ideal for HCI & emotion analysis.
https://github.com/bananacat123-hue/facial_expression_recognition-sure_trust-
computer-vision deep-learning emoji-suggestions emotion-dataset face-emotion-recognition flask image-classification opencv python roboflow-dataset sure-trust tensorflow yolov9
Last synced: about 1 month ago
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Facial Expression Recognition System using YOLOv9 & Flask. Detects 5 emotions (Angry, Happy, Natural, Sad, Surprised) from images/live camera with mAP50 of 0.731. Features a web interface with file uploads, real-time processing, & emoji feedback. Built with Python, OpenCV, Flask, HTML/CSS/JS. Ideal for HCI & emotion analysis.
- Host: GitHub
- URL: https://github.com/bananacat123-hue/facial_expression_recognition-sure_trust-
- Owner: Bananacat123-hue
- Created: 2025-04-22T12:12:34.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-04-22T16:34:09.000Z (6 months ago)
- Last Synced: 2025-04-22T17:16:19.009Z (6 months ago)
- Topics: computer-vision, deep-learning, emoji-suggestions, emotion-dataset, face-emotion-recognition, flask, image-classification, opencv, python, roboflow-dataset, sure-trust, tensorflow, yolov9
- Language: Jupyter Notebook
- Size: 47.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Facial Expression Recognition System - Sure Trust 😊
Welcome to the **Facial Expression Recognition System** repository! This project harnesses the power of YOLOv9 and Flask to detect emotions in images and live camera feeds. It identifies five emotions: Angry, Happy, Natural, Sad, and Surprised, achieving a mean Average Precision (mAP50) of 0.731. The system features a user-friendly web interface that supports file uploads, real-time processing, and emoji feedback.
## Table of Contents
- [Project Overview](#project-overview)
- [Features](#features)
- [Technologies Used](#technologies-used)
- [Installation](#installation)
- [Usage](#usage)
- [Demo](#demo)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)
- [Releases](#releases)
## Project Overview
Facial expressions are a vital part of human communication. This project aims to develop a system that can recognize and interpret these expressions. Using deep learning techniques, we built a model that can classify emotions from facial images. This technology has applications in Human-Computer Interaction (HCI), emotion analysis, and more.
## Features
- **Emotion Detection**: Accurately detects five emotions from images and live video feeds.
- **Web Interface**: Easy-to-use interface for uploading images and viewing results.
- **Real-Time Processing**: Analyze live camera input for immediate feedback.
- **Emoji Feedback**: Provides emoji suggestions based on detected emotions.
- **Open Source**: Contribute to the project and improve the system.
## Technologies Used
This project utilizes the following technologies:
- **Python**: The primary programming language for the application.
- **OpenCV**: For image processing and computer vision tasks.
- **Flask**: A lightweight web framework for creating the web interface.
- **HTML/CSS/JS**: For building the front end of the application.
- **YOLOv9**: A state-of-the-art object detection model used for emotion recognition.
- **TensorFlow**: For deep learning tasks and model training.
- **Roboflow Dataset**: A dataset used for training the emotion detection model.
## Installation
To get started with this project, follow these steps:
1. **Clone the Repository**:
```bash
git clone https://github.com/Bananacat123-hue/Facial_Expression_Recognition-Sure_Trust-.git
```
2. **Navigate to the Project Directory**:
```bash
cd Facial_Expression_Recognition-Sure_Trust-
```
3. **Install Required Packages**:
Make sure you have Python installed. Then, install the required packages using pip:
```bash
pip install -r requirements.txt
```
4. **Run the Application**:
Start the Flask server:
```bash
python app.py
```
5. **Access the Web Interface**:
Open your web browser and go to `http://127.0.0.1:5000` to access the application.
## Usage
Once the application is running, you can use it in the following ways:
1. **Upload an Image**: Click on the upload button to select an image file from your device. The system will analyze the image and display the detected emotion.
2. **Use the Live Camera**: Allow the application to access your camera. It will process the video feed in real-time and show the detected emotions as you move.
3. **View Emoji Feedback**: Based on the detected emotion, the application will display an appropriate emoji for quick feedback.
## Demo
Here’s a brief demonstration of how the application works:
You can find the latest releases and updates [here](https://github.com/Bananacat123-hue/Facial_Expression_Recognition-Sure_Trust-/releases).
## Contributing
We welcome contributions to improve this project. Here’s how you can help:
1. **Fork the Repository**: Click on the fork button to create a copy of the repository in your account.
2. **Create a New Branch**: Use a descriptive name for your branch.
```bash
git checkout -b feature/YourFeatureName
```
3. **Make Your Changes**: Implement your feature or fix a bug.
4. **Commit Your Changes**: Write a clear commit message.
```bash
git commit -m "Add your message here"
```
5. **Push to Your Branch**:
```bash
git push origin feature/YourFeatureName
```
6. **Create a Pull Request**: Go to the original repository and submit a pull request.
## License
This project is licensed under the MIT License. Feel free to use, modify, and distribute this software.
## Contact
For questions or feedback, you can reach out to the project maintainer:
- **Email**: your-email@example.com
- **GitHub**: [Bananacat123-hue](https://github.com/Bananacat123-hue)
## Releases
For the latest updates and downloadable files, visit the [Releases section](https://github.com/Bananacat123-hue/Facial_Expression_Recognition-Sure_Trust-/releases).
Thank you for your interest in the Facial Expression Recognition System! We hope you find it useful for your projects and research. Your contributions and feedback are always welcome.