mirror of
https://github.com/yakhyo/uniface.git
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63 lines
5.0 KiB
Markdown
63 lines
5.0 KiB
Markdown
# Interactive Notebooks
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Run UniFace examples directly in your browser with Google Colab, or download and run locally with Jupyter.
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---
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## Available Notebooks
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| Notebook | Colab | Description |
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| [Face Detection](https://github.com/yakhyo/uniface/blob/main/examples/01_face_detection.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/01_face_detection.ipynb) | Detect faces and 5-point landmarks |
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| [Face Alignment](https://github.com/yakhyo/uniface/blob/main/examples/02_face_alignment.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/02_face_alignment.ipynb) | Align faces for recognition |
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| [Face Verification](https://github.com/yakhyo/uniface/blob/main/examples/03_face_verification.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/03_face_verification.ipynb) | Compare faces for identity |
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| [Face Search](https://github.com/yakhyo/uniface/blob/main/examples/04_face_search.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/04_face_search.ipynb) | Find a person in group photos |
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| [Face Analyzer](https://github.com/yakhyo/uniface/blob/main/examples/05_face_analyzer.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/05_face_analyzer.ipynb) | Unified face analysis |
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| [Face Parsing](https://github.com/yakhyo/uniface/blob/main/examples/06_face_parsing.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/06_face_parsing.ipynb) | Semantic face segmentation |
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| [Face Anonymization](https://github.com/yakhyo/uniface/blob/main/examples/07_face_anonymization.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/07_face_anonymization.ipynb) | Privacy-preserving blur |
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| [Gaze Estimation](https://github.com/yakhyo/uniface/blob/main/examples/08_gaze_estimation.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/08_gaze_estimation.ipynb) | Gaze direction estimation |
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| [Face Segmentation](https://github.com/yakhyo/uniface/blob/main/examples/09_face_segmentation.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/09_face_segmentation.ipynb) | Face segmentation with XSeg |
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| [Face Vector Store](https://github.com/yakhyo/uniface/blob/main/examples/10_face_vector_store.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/10_face_vector_store.ipynb) | FAISS-backed face database |
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| [Head Pose Estimation](https://github.com/yakhyo/uniface/blob/main/examples/11_head_pose_estimation.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/11_head_pose_estimation.ipynb) | 3D head orientation estimation |
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| [Face Recognition](https://github.com/yakhyo/uniface/blob/main/examples/12_face_recognition.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/12_face_recognition.ipynb) | Standalone face recognition pipeline |
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| [Portrait Matting](https://github.com/yakhyo/uniface/blob/main/examples/13_portrait_matting.ipynb) | [](https://colab.research.google.com/github/yakhyo/uniface/blob/main/examples/13_portrait_matting.ipynb) | Portrait matting with MODNet |
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## Running Locally
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Download and run notebooks on your machine:
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```bash
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# Clone the repository
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git clone https://github.com/yakhyo/uniface.git
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cd uniface
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# Install dependencies
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pip install "uniface[cpu]" jupyter # or uniface[gpu] for CUDA
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# Launch Jupyter
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jupyter notebook examples/
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```
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---
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## Running on Google Colab
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Click any **"Open in Colab"** badge above. The notebooks automatically:
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1. Install UniFace via pip
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2. Clone the repository to access test images
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3. Set up the correct working directory
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!!! tip "GPU Acceleration"
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In Colab, go to **Runtime → Change runtime type → GPU** for faster inference.
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---
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## Next Steps
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- [Quickstart](quickstart.md) - Code snippets for common use cases
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- [Tutorials](recipes/image-pipeline.md) - Step-by-step workflow guides
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- [API Reference](modules/detection.md) - Detailed module documentation
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