https://github.com/anubhavchaturvedi-github/emotion-recognition
Emotion Recognition is a cutting-edge deep learning project designed to detect and classify human emotions based on facial expressions. Using a Convolutional Neural Network (CNN), the model is trained on the FER2013 dataset and can accurately recognize seven distinct emotions
https://github.com/anubhavchaturvedi-github/emotion-recognition
emotion emotion-recognition emotiondetection nthytech project python
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Emotion Recognition is a cutting-edge deep learning project designed to detect and classify human emotions based on facial expressions. Using a Convolutional Neural Network (CNN), the model is trained on the FER2013 dataset and can accurately recognize seven distinct emotions
- Host: GitHub
- URL: https://github.com/anubhavchaturvedi-github/emotion-recognition
- Owner: AnubhavChaturvedi-GitHub
- Created: 2024-11-22T15:56:37.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-23T05:35:57.000Z (over 1 year ago)
- Last Synced: 2024-12-03T09:09:43.398Z (over 1 year ago)
- Topics: emotion, emotion-recognition, emotiondetection, nthytech, project, python
- Language: Python
- Homepage: https://www.youtube.com/@NetHyTech
- Size: 8.15 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Emotion Recognition
## Overview
**Emotion Recognition** is a cutting-edge deep learning project designed to detect and classify human emotions based on facial expressions. Using a Convolutional Neural Network (CNN), the model is trained on the FER2013 dataset and can accurately recognize seven distinct emotions:
**Angry**, **Disgust**, **Fear**, **Happy**, **Sad**, **Surprise**, and **Neutral**.
## Features
- **Real-Time Emotion Detection**: Analyze emotions live using webcam input.
- **High Accuracy**: Powered by TensorFlow and trained on a robust dataset.
- **User-Friendly Interface**: Simple, intuitive design for seamless interaction.
## Technologies Used
- **Programming Language**: Python
- **Libraries and Frameworks**:
- TensorFlow
- OpenCV
- NumPy
- Matplotlib
- Pandas
- scikit-learn
---
## Installation
To get started with this project, follow these steps:
1. **Clone the Repository**:
```bash
git clone https://github.com/AnubhavChaturvedi-GitHub/Emotion-Recognition.git
cd Emotion-Recognition
```
2. **Create a Virtual Environment** *(Optional but Recommended)*:
```bash
python -m venv venv
source venv/bin/activate # For Windows: venv\Scripts\activate
```
3. **Install Dependencies**:
```bash
pip install -r requirements.txt
```
---
## Usage
### Train the Model
Train the CNN model on the FER2013 dataset:
```bash
python model_maker.py
```
After training, the model will be saved as **`emotion_model.h5`**.
### Run Real-Time Emotion Detection
Start the webcam-based emotion detection system:
```bash
python main.py
```
Press **`q`** to exit the webcam feed.
---
## Contributing
Contributions are welcome! If you have any ideas for improvements or new features, feel free to submit an issue or open a pull request.
---
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
---
## Acknowledgements
- **FER2013 Dataset**: A publicly available dataset for emotion recognition.
- **OpenCV**: For real-time video processing.
- **TensorFlow**: For deep learning model training and inference.