Metadata-Version: 2.1
Name: face-recognition-ai
Version: 0.0.2
Summary: A face recognition system using yoloface and facenet
Home-page: https://github.com/muntakim1/face-recognition-ai
Author: Muntakimur Rahaman
Author-email: muntakim.cse@gmail.com
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: facenet-pytorch
Requires-Dist: PyYaml
Requires-Dist: joblib
Requires-Dist: opencv-python
Requires-Dist: yolo5face

# Face-Recognition-AI

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Welcome to Face-Recognition-AI, an advanced face recognition system built with cutting-edge technologies, including FaceNet and YOLO5Face. This project draws inspiration from the popular face-recognition module, aiming to provide users with a professional and efficient solution for face recognition.

# 🚀 Getting Started

To get started with Face-Recognition-AI, follow these simple steps:

`pip install face-recognition-ai`

Run python usage.py

```
from PIL import Image

from face_recognition_ai import match_faces, show_detections

unknown_with_multiple_faces = Image.open("images/multi.jpeg")

known = Image.open("images/sakib.jpg")
known_person_name = "sakib"

print(True if True in match_faces(unknown_with_multiple_faces, known) else False)
img = show_detections(unknown_with_multiple_faces, known, known_person_name)
img.show()



```

# 💡 Features

- FaceNet Integration: Leveraging the power of FaceNet, our system directly learns a mapping from face images to a compact Euclidean space, enabling accurate and efficient face recognition [5].

- YOLO5Face Detection: The YOLO5Face model enhances face detection capabilities, ensuring robust identification of faces in various scenarios.

- Inspired by Face-Recognition Module: We take inspiration from the widely-used face-recognition module, incorporating best practices and user-friendly design.

# 🤝 Contribution Guidelines

We welcome contributions to make Face-Recognition-AI even more professional. If you'd like to contribute, please follow these guidelines:

- Fork the repository.
- Create a new branch: `git checkout -b feature/your-feature`.

- Make your changes and commit them: `git commit -m 'Add your feature'`.

- Push to the branch: `git push origin feature/your-feature`.

- Submit a pull request.

# 📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

# 🌐 Sources

GitHub - Awesome Face Detection and Recognition
GitHub - Face Recognition OpenCV Facenet
Medium - Face Recognition in Python| FaceNet, MTCNN and SVM
Towards Data Science - Using FaceNet For On-Device Face Recognition With Android
ArXiv - A Unified Embedding for Face Recognition and Clustering
Viso AI - DeepFace - Most Popular Deep Face Recognition in 2024
