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This repository contains a comprehensive face recognition system that combines YOLOv8 for face detection and FaceNet for face recognition.

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Face-Recognition

This repository contains a comprehensive face recognition system that combines YOLOv8 for face detection and FaceNet for face recognition. Face recognition is a critical technology with applications in security, surveillance, and user authentication. This project leverages state-of-the-art deep learning models to achieve accurate and reliable face recognition.

  • Detect faces in images using YOLO.
  • Crop and save the detected faces.
  • Recognize faces using DeepFace and categorize them based on a pre-trained model.
  • Do whatever you feel like from the features extracted.

Demo

Experience the functionality of our face recognition model, which has been trained on a dataset featuring faces of few politicians, by visiting Live Demo. Please keep in mind that this deployment is specifically designed for demonstration purposes and may not be fine-tuned for optimal performance in real-world scenarios. The best place to start and learn about the project's evolution is the "o-testing" folder. Here, you'll find different levels of understanding, providing comprehensive insights into the project's development.

testing.mp4
Acknowledgement : For details on the deployment of the model using Streamlit, refer to this repository.

Installation

  1. Clone the Repository : https://github.com/sOR-o/Face-Recognition.git
  2. Install Dependencies : pip install -r requirements.txt
  3. play with code.

-Can be improved by transfer learning (obviously 😉)

Contributing

Contributions to this project are welcome! If you'd like to contribute, feel free to submit issues, feature requests, or pull requests.

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This repository contains a comprehensive face recognition system that combines YOLOv8 for face detection and FaceNet for face recognition.

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