Image Emotion Detection

Overview

This project uses a deep learning model for emotion detection in facial images. The model recognizes seven emotions: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral.

Prerequisites

• Python
• TensorFlow
• OpenCV

Getting Started

1. Clone the repository: git clone https://github.com/Kishankumar1328/your-repo.git
2. Navigate to the project directory: cd your-repo
3. Install dependencies: pip install -r requirements.txt
4. Download and organize the dataset.
5. Train the model: python train.py
6. Run emotion detection: python predict_emotion.py --image_path path/to/test_image.jpg

Dataset

Describe the dataset source and format.

Model

Briefly explain the model architecture.

Training

Include basic information about training.

Usage

Show users how to use the trained model.

Contributing

1. Fork the repository.
2. Create a new branch: git checkout -b feature-name
3. Make changes, commit, and push.
4. Create a pull request.

License

Specify the project's license under Apache-2.0 license.

Contact

For support or collaboration, contact [Kishan kumar Suresh Kumar] at [kishkumar132005@gmail.com].