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| title: XDL Colitis Demo | |
| emoji: 👁 | |
| colorFrom: pink | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: "6.5.1" | |
| app_file: app.py | |
| pinned: false | |
| # XDL Colitis Demo | |
| Simple Gradio demo for DenseNet-based colitis image classification with optional XDL overlays. | |
| ## Features | |
| - Batch inference only | |
| - Case selector: | |
| - Multiclass (4 Classes) | |
| - Crohn vs TB | |
| - Kolitis Ulseratif vs Infeksi | |
| - Folder upload support (`gr.File` directory upload) | |
| - Optional local folder-path input | |
| - Automatic device detection (`cuda` if available, else `cpu`) | |
| - Presentable summary card for key outputs (device, processed count, final class, mean confidence, etc.) | |
| - Final folder classification by majority vote of per-image top class | |
| - Mean confidence for the selected final class | |
| - Compact GradCAM + SmoothGrad overlays for classified images | |
| - Optional saving of compact XDL results to a local folder | |
| ## Run | |
| ```bash | |
| .venv/bin/python app.py | |
| ``` | |
| Then open the Gradio URL in your browser. | |
| ## Project Structure | |
| - `app.py`: minimal launcher | |
| - `src/ui.py`: batch-only Gradio UI | |
| - `src/inference.py`: model loading + inference + batch/XDL pipeline | |
| - `src/xdl.py`: DenseNet-specific XDL helper functions | |
| - `src/densenet.py`: model definition | |
| - `src/preprocessing.py`: inference transform | |
| ## Notes | |
| - Default model paths: | |
| - `models/multiclass.pth` (Multiclass) | |
| - `models/crohn_tb.pth` (Crohn vs TB) | |
| - `models/ku_infeksi.pth` (Kolitis Ulseratif vs Infeksi) | |
| - You can override model paths with env vars: | |
| - `MODEL_PATH_MULTICLASS` | |
| - `MODEL_PATH_CROHN_TB` | |
| - `MODEL_PATH_KU_INFEKSI` | |
| - If model loading fails, the UI returns a clear error instead of silently using random weights. | |