| title: Selective Segmentation (MC Dropout) | |
| emoji: 🐾 | |
| colorFrom: indigo | |
| colorTo: yellow | |
| sdk: static | |
| app_file: index.html | |
| pinned: false | |
| license: mit | |
| short_description: Pet segmentation that abstains when unsure (in-browser) | |
| # Selective segmentation with MC Dropout | |
| U-Net (7.8M parameters) trained on Oxford-IIIT Pet to segment pet / background / border. | |
| MC Dropout (20 passes) measures per-pixel uncertainty and the model abstains on the most | |
| uncertain pixels: on the 3,669-image test set, pixel error drops from 8.13% to 2.18% at | |
| 80% coverage and selective mIoU rises from 0.777 to 0.882. Thresholds and the temperature | |
| were chosen on validation data only. Runs entirely in the browser with ONNX Runtime Web; | |
| dropout masks are drawn in JavaScript and fed to the exported graph. | |