nexface 0.0.9

A face recognition and embedding extraction library

NexFace

NexFace is a modular face recognition library built on top of modern deep learning models. It supports face detection, embedding extraction, clustering, and identification using ONNX, FaceNet, and Scikit-learn-compatible algorithms.

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🚀 Features

• ✅ Face Detection (YuNet with OpenCV & ONNX)
• ✅ Face Embedding Extraction (FaceNet .h5)
• ✅ Clustering (DBSCAN & HDBSCAN)
• ✅ Recognition via Prototypes
• ✅ Clean and extensible object-oriented design

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🧠 How It Works

1. Face Detection:
   Uses YuNet ONNX model via cv2.FaceDetectorYN.

2. Embedding Extraction:
   FaceNet model (Keras .h5) extracts 128-D facial embeddings.

3. Clustering & Prototypes:
   Cluster face embeddings via DBSCAN or HDBSCAN.
   Compute cluster centers (prototypes) for recognition.

4. Recognition:
   New face embeddings are compared against cluster prototypes using cosine or Euclidean similarity.

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You can also install using pip install -r requirements.txt.

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📌 To Do

• Add ArcFace / InsightFace support
• Improve alignment and augmentation
• Evaluation metrics (precision, recall, etc.)

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🧑‍💻 Author

Fatih Dağdeviren
[e-mail]

GitHub: github.com/fatihdagdeviren