Face Recognition and Emotion Predictor using KNeighborsClassifier - scikit-learn

Description: This project implements a facial recognition and emotion prediction system using the KNeighborsClassifier algorithm. The system is designed with a graphical user interface (GUI) using CustomTkinter for easy interaction. Users can train the model using various faces, and the system will recognize the faces and predict the associated emotions.

Features:

• Face recognition: Detects and identifies faces in uploaded images.
• Emotion prediction: Predicts the emotions expressed by the detected faces.
• CustomTkinter GUI: Provides an intuitive interface for users to interact with the system.
• KNeighborsClassifier: Utilizes the KNeighborsClassifier algorithm for facial recognition and emotion prediction.

Installation:

1. Clone the repository:

   git clone https://github.com/akhil838/FREP_scikit-learn.git
   

2. Navigate to the project directory:

   cd FREP_scikit-learn
   

3. Install the required dependencies:

   pip install -r requirements.txt
   

Usage:

1. Run the main script:

   python main.py
   

2. Use the add_faces to train the machine to recognise a new face.
3. View the recognized faces and predicted emotions.

UI:

• Home Page
• Test
• Train

Contributing: Contributions are welcome! If you have any suggestions, feature requests, or bug reports, please feel free to open an issue or create a pull request on the GitHub repository.

License: This project is licensed under the MIT License. See the LICENSE file for more details.

References:

• Scikit-learn
• Link to CustomTkinter documentation