--- license: apache-2.0 --- # AuthentiVision 🔍
Logo **State-of-the-art Face Authentication Model for Detecting AI-Generated Images** [Github](https://github.com/TimeLabHub/AuthentiVision) | [Data](https://huggingface.co/datasets/haijian06/face-auth-dataset) | [Demo](https://huggingface.co/spaces/haijian06/TrueFace) | [Tech Blog](https://timelabhub.github.io/)
## 🎯 Real vs. AI-Generated Face Comparison
Real Face AI-Generated Face
Real Face AI-Generated Face
Real Face AI-Generated Face
## 🌟 Features - High accuracy in distinguishing real faces from AI-generated ones - Multiple feature extraction techniques for robust detection - Easy-to-use API for quick integration - Lightweight and efficient inference - Comprehensive documentation and examples ## 🚀 Quick Start ```bash git clone https://github.com/TimeLabHub/AuthentiVision.git cd AuthentiVision pip install -r requirements.txt ``` ```python from authentivision import AuthentiVision # Initialize detector detector = AuthentiVision() # Make prediction label, confidence = detector.predict("path_to_image.jpg") print(f"Prediction: {label} (Confidence: {confidence:.2f})") ``` ## 📚 Documentation For detailed documentation, please visit our [tech blog](https://timelabhub.github.io/). ## 🎯 Use Cases(Coming soon) - Identity verification systems - Social media content moderation - Digital forensics - Security applications ## 📄 License This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details. ## 🌟 Acknowledgments - Thanks to all contributors and researchers in the field - Special thanks to the open-source community ## 📝 Citation If you use AuthentiVision in your research or project, please cite our technical blog ```bibtex @online{authentivision2024, title={AuthentiVision: Finding Yourself in the Real World}, author={Haijian Wang and Zhangbei Ding and Yefan Niu and Xiaoming Zhang}, year={2024}, url={https://timelabhub.github.io/}, note={Medium blog post} }