The Textile Anti-Counterfeiting Identification System is an iOS app for verifying textile authenticity. It uses YOLOv5 with CoreML for accurate detection of real or fake trademarks, swiftly confirming product authenticity and helping reduce counterfeit distribution.
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Intuitive UI Design: Streamlined interface for easy camera scanning and product info retrieval.
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Custom-Trained YOLOv5 Model Integration: Integrates a custom-trained YOLOv5 model into our iOS app for real-time product recognition, utilizing Swift along with CoreML and Vision frameworks for enhanced detection accuracy.
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QR Code Capabilities: Advanced QR code scanning and decoding to guide model selection and enhance anti-counterfeiting measures.
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Firebase Authentication: Robust user login/logout system for data security and privacy.
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Informative Product Pages: Detailed and categorized product information to user preferences for a personalized experience.
- Machine Learning & Image Processing:
- YOLOv5: Custom-trained for product recognition.
- CoreML and Vision Frameworks: For image recognition in iOS.
- Logo & QR Code Processing:
- AVFoundation Framework: For QR code and Logo scanning.
- Doris Wen - FCU IECS
This project is licensed under the MIT License - see the LICENSE.md file for details
Contributions are always welcome!
See contributing.md
for ways to get started.
This project is used by the following companies: