uniface/docs/index.md

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UniFace

All-in-One Open-Source Face Analysis Library

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### :material-face-recognition: Face Detection ONNX-optimized detectors (RetinaFace, SCRFD, YOLO) with 5-point landmarks.

### :material-account-check: Face Recognition AdaFace, ArcFace, MobileFace, and SphereFace embeddings for identity verification.

### :material-map-marker: Landmarks Accurate 106-point facial landmark localization for detailed face analysis.

### :material-account-details: Attributes Age, gender, race (FairFace), and emotion detection from faces.

### :material-face-man-shimmer: Face Parsing BiSeNet semantic segmentation with 19 facial component classes.

### :material-eye: Gaze Estimation Real-time gaze direction prediction with MobileGaze models.

### :material-motion-play: Tracking Multi-object tracking with BYTETracker for persistent face IDs across video frames.

### :material-shield-check: Anti-Spoofing Face liveness detection with MiniFASNet to prevent fraud.

### :material-blur: Privacy Face anonymization with 5 blur methods for privacy protection.

### :material-database-search: Vector Indexing FAISS-backed embedding store for fast multi-identity face search.

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Installation

UniFace runs inference primarily via ONNX Runtime; some optional components (e.g., emotion TorchScript, torchvision NMS) require PyTorch.

Standard

pip install uniface

GPU (CUDA)

pip install uniface[gpu]

From Source

git clone https://github.com/yakhyo/uniface.git
cd uniface
pip install -e .

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Next Steps

### :material-rocket-launch: Quickstart Get up and running in 5 minutes with common use cases.

Quickstart Guide →

### :material-school: Tutorials Step-by-step examples for common workflows.

View Tutorials →

### :material-api: API Reference Explore individual modules and their APIs.

Browse API →

### :material-book-open-variant: Guides Learn about the architecture and design principles.

Read Guides →

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License

UniFace is released under the MIT License.