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https://github.com/yakhyo/uniface.git
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5f74487eb3
* feat: Add XSeg for Face Segmentation DeepFaceLab * docs: Update model inference related reference * chore: Update jupyter notebook example for face segmentation
3.8 KiB
3.8 KiB
Interactive Notebooks
Run UniFace examples directly in your browser with Google Colab, or download and run locally with Jupyter.
Available Notebooks
| Notebook | Colab | Description |
|---|---|---|
| Face Detection |  |
Detect faces and 5-point landmarks |
| Face Alignment | |
Align faces for recognition |
| Face Verification | |
Compare faces for identity |
| Face Search | |
Find a person in group photos |
| Face Analyzer | |
All-in-one face analysis |
| Face Parsing | |
Semantic face segmentation |
| Face Anonymization | |
Privacy-preserving blur |
| Gaze Estimation | |
Gaze direction estimation |
| Face Segmentation | |
Face segmentation with XSeg |
Running Locally
Download and run notebooks on your machine:
# Clone the repository
git clone https://github.com/yakhyo/uniface.git
cd uniface
# Install dependencies
pip install uniface jupyter
# Launch Jupyter
jupyter notebook examples/
Running on Google Colab
Click any "Open in Colab" badge above. The notebooks automatically:
- Install UniFace via pip
- Clone the repository to access test images
- Set up the correct working directory
!!! tip "GPU Acceleration" In Colab, go to Runtime → Change runtime type → GPU for faster inference.
Next Steps
- Quickstart - Code snippets for common use cases
- Tutorials - Step-by-step workflow guides
- API Reference - Detailed module documentation