Introduction

Emotion Detection project that utilizes artificial intelligence to recognize and classify human emotions from images or video streams. This project aims to provide a simple yet powerful tool for understanding human emotions using deep learning techniques.

Features

• Train your own emotion detection model using the provided train.py script.
• Easily customize the number of classes to detect different emotions according to your requirements.
• Experiment with different pre-trained models to achieve the best performance for your application.
• Utilize the test.py file to perform real-time emotion detection on images or video streams.
• Dive into the world of deep learning and explore the fascinating real of emotion recognition.

Usage

1. Training the Model:

   • Use the train.py file to train your emotion detection model. You can modify the script to adjust parameters, architecture, or dataset according to your needs.

   bashCopy code
   python train.py
   

2. Customization:

   • Adjust the number of classes in the dataset and model architecture to accommodate different emotional states or expressions.
   • Experiment with various pre-trained models to find the most suitable one for your application.

3. Real-time Emotion Detection:

   • Execute the test.py script to perform real-time emotion detection on images or video streams.

   bashCopy code
   python test.py
   

Requirements

• Python 3.x
• Deep learning framework (e.g., TensorFlow, PyTorch)
• OpenCV (for real-time image and video processing)

Contribution

Contributions to PyPower project are welcome! Whether you want to report bugs, suggest features, or contribute code, your input is appreciated.