Face and Emotion Recognition

This repository contains two Python scripts for face recognition and emotion recognition using different approaches.

Face Recognition

Dependencies

• OpenCV: An open-source computer vision library used for image and video processing.
• face_recognition: A library for face recognition that uses dlib and deep learning.

Usage

1. Install the required Python packages:

   pip install -r requirements.txt

2. Prepare a folder named 'Images' in the same directory as the script.

3. Place images of known faces in the 'Images' folder for training.

4. Run the script:

   python face_recognition.py

5. The script will capture video from the webcam and recognize known faces.

Emotion Recognition

Dependencies

• OpenCV: An open-source computer vision library used for image and video processing.
• DeepFace: A deep learning facial analysis library that provides pre-trained models for facial emotion detection.

Usage

1. Install the required Python packages:

   pip install -r requirements.txt

2. Download the Haar cascade XML file (haarcascade_frontalface_default.xml) for face detection from the OpenCV GitHub repository.

3. Run the script:

   python emotion_recognition.py

4. The script will capture video from the webcam, detect faces, and display the dominant emotion on each face.

Notes

• Both scripts use live video stream capture (0 - the first webcam). The video source can be modified as needed.

• Ensure the necessary dependencies are installed before running the scripts.

• The face recognition script requires a 'Images' folder with images of known faces for training.

• The emotion recognition script uses Haar-Cascade for face detection and DeepFace for emotion analysis.

• Press 'Esc' key to exit the video stream in both scripts.

Acknowledgements

• OpenCV: https://github.com/opencv/opencv
• face_recognition: https://github.com/ageitgey/face_recognition
• DeepFace: https://github.com/serengil/deepface