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| title: VREyeSAM | |
| emoji: ποΈ | |
| colorFrom: purple | |
| colorTo: pink | |
| sdk: docker | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # VREyeSAM: Non-Frontal Iris Segmentation | |
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| ## π― Overview | |
| VREyeSAM is a robust iris segmentation service for non-frontal iris images captured in virtual reality and augmented reality environments. | |
| ## π Quick Start | |
| 1. Upload a non-frontal iris image | |
| 2. Click "Segment Iris" | |
| 3. Download results | |
| ## π Features | |
| - **Fast Segmentation**: Real-time iris segmentation | |
| - **Binary Masks**: Precise iris region extraction | |
| - **Confidence Maps**: Uncertainty quantification | |
| - **Easy Download**: Save results with one click | |
| ## π Security | |
| This model is **fully protected**: | |
| - β Model weights cannot be downloaded | |
| - β Implementation details are hidden | |
| - β Only API endpoints are exposed | |
| - β Secure inference only | |
| ## π Performance | |
| - High accuracy on non-frontal iris images | |
| - Optimized for VR/AR capture scenarios | |
| - Fast inference on standard hardware | |
| --- | |
| ## Citation | |
| If you use VREyeSAM in your research: | |
| ```bibtex | |
| @article{sharma2025vreyesam, | |
| title={VREyeSAM: Virtual Reality Non-Frontal Iris Segmentation using Foundational Model with Uncertainty Weighted Loss}, | |
| author={Sharma, Geetanjali and Nagaich, Dev and Jaswal, Gaurav and Nigam, Aditya and Ramachandra, Raghavendra}, | |
| conference={IJCB}, | |
| year={2025} | |
| } | |
| ``` | |
| ## π₯ Authors | |
| - Geetanjali Sharma | |
| - Dev Nagaich | |
| - Gaurav Jaswal | |
| - Aditya Nigam | |
| - Raghavendra Ramachandra | |
| ## π§ Contact | |
| For inquiries: geetanjalisharma546@gmail.com | |
| ## π License | |
| MIT License - See LICENSE file | |
| --- | |
| **For full technical details and code, visit:** [GitHub Repository](https://github.com/GeetanjaliGTZ/VREyeSAM) | |