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Basic Face Recognition System

Overview

This repository contains the implementation of a basic face recognition system developed as part of the Computer Vision Project for the Winter Term 2023/24, under the guidance of Florian Kordon, Vincent Christlein, Mathias Seuret, Thomas Köhler, and Mathias Zinnen. The project aims to train a system on facial data for identification and re-identification purposes in video data, covering both supervised and unsupervised learning techniques.

System Components

  • Training Module (training.py): Supports identification mode for collecting labeled training data and a clustering mode for acquiring unlabeled data.
  • Testing Module (test.py): Utilizes trained models for face identification or re-identification and visualizes results.

Repository Contents

  • osr_learning.py: Implementation of open-set recognition with known classes and known unknown classes.
  • ex4_additional.ipynb: Jupyter notebook with additional analysis and results.
  • evaluation_final.py: Script for evaluating face recognition performance.
  • dir_curve.py: Script for generating Detection and Identification Rate (DIR) curves.
  • face_recognition_final.py: Final implementation of face recognition functionalities.
  • face_detector_final.py: Face detection, tracking, and alignment module.
  • training.py, test.py: Main training and testing scripts for the face recognition system.
  • requirements.txt: List of Python package dependencies for the project.

Installation

Ensure you have Python 3.x installed, then clone this repository and install the required dependencies:

git clone <repository-url>
cd <repository-directory>
pip install -r requirements.txt

Usage

  • To train the system, run:

    python training.py

  • To test the system, run:

    python test.py

For detailed usage of other scripts, refer to the inline documentation within each file.

Dependencies

  • mtcnn>=0.1.0
  • numpy>=1.16.4
  • opencv-python>=4.1
  • scipy>=1.3.0

Contributions

Contributions to this project are welcome. Please open an issue to discuss proposed changes or notify of any issues.

Acknowledgments

Special thanks to Thomas Köhler for his invaluable guidance and to all contributors to the YouTube Faces database and other resources utilized in this project.