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README.md
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license: apache-2.0
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license: apache-2.0
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---
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# AuthentiVision π
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<div align="center">
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<img src="assets/img_1.jpg" alt="Logo" width="300"/>
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**State-of-the-art Face Authentication for Detecting AI-Generated Images**
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[Huggingface](https://medium.com/@haijian06/authentivision-detecting-ai-generated-faces) | [Data](https://huggingface.co/datasets/haijian06/face-auth-dataset) | [Demo](https://huggingface.co/spaces/haijian06/AuthentiVision) | [Technical Paper](https://arxiv.org/abs/xxx)
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</div>
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</div>
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## π― Real vs. AI-Generated Face Comparison
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<div align="center">
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<table>
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<tr>
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<td><b>Real Face</b></td>
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<td><b>AI-Generated Face</b></td>
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</tr>
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<tr>
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<td>
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<img src="assets/real_face_example.jpg" alt="Real Face" width="200"/>
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</td>
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<td>
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<img src="assets/ai_face.jpg" alt="AI-Generated Face" width="200"/>
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</td>
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</tr>
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<tr>
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<td>
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<img src="assets/real_face_example.jpg" alt="Real Face" width="200"/>
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</td>
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<td>
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<img src="assets/ai_face_2.jpg" alt="AI-Generated Face" width="200"/>
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</td>
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</tr>
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</table>
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</div>
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## π Features
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- High accuracy in distinguishing real faces from AI-generated ones
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- Multiple feature extraction techniques for robust detection
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- Easy-to-use API for quick integration
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- Lightweight and efficient inference
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- Comprehensive documentation and examples
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## π Quick Start
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```bash
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git clone https://github.com/haijian06/AuthentiVision
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cd AuthentiVision
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pip install -e .
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```
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```python
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from authentivision import AuthentiVision
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# Initialize detector
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detector = AuthentiVision()
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# Make prediction
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label, confidence = detector.predict("path_to_image.jpg")
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print(f"Prediction: {label} (Confidence: {confidence:.2f})")
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```
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## π Documentation
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For detailed documentation, please visit our [tech blog](https://timelabhub.github.io/).
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## π― Use Cases(Coming soon)
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- Identity verification systems
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- Social media content moderation
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- Digital forensics
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- Security applications
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## π License
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This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
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## π Acknowledgments
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- Thanks to all contributors and researchers in the field
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- Special thanks to the open-source community
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## π Citation
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If you use AuthentiVision in your research or project, please cite our technical blog:
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```bibtex
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@online{authentivision2024,
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title={AuthentiVision: Finding Yourself in the Real World},
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author={Haijian Wang and Zhangbei Ding and Yefan Niu and Xiaoming Zhang},
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year={2024},
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url={https://timelabhub.github.io/},
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note={Medium blog post}
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}
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