A face recognition system using yoloface and facenet
Project description
Face-Recognition-AI
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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for face-recognition-ai-0.0.2.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | f30fc3b45eefed832943365ff8159fa087e1326e36eefff69b8441965ab9f992 |
|
MD5 | dc6745f181da95a1c7c3979fbfadd16c |
|
BLAKE2b-256 | 8f420267bc4ba69a59c594d457d2b86b30e8a88beceb31d783c4ec9e81754e34 |
Hashes for face_recognition_ai-0.0.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f47ab0e212bd421c5d4e446a92964c80d799d612f45059e7ea0e8e525a291cf6 |
|
MD5 | b48ad802ea2d6cd2b03adcbd3c4eaafc |
|
BLAKE2b-256 | 68a29dfa7f05e503fba4e97173dc6abb12dfd43f7207b25e46876e2912ac01fe |