Fix README with Gradio SDK metadata

README.md

@@ -1,3 +1,15 @@
+---
+title: WoundNetB7 DFU Analysis
+emoji: 🩺
+colorFrom: blue
+colorTo: red
+sdk: gradio
+sdk_version: "5.29.0"
+python_version: "3.11"
+app_file: app.py
+pinned: false
+---
+
 # WoundNetB7 — Automated DFU Assessment Pipeline
 
 End-to-end pipeline for Diabetic Foot Ulcer (DFU) analysis:
@@ -28,78 +40,14 @@ Input Image (DFU photograph)
               -> 18% max group gap reduction (p < 10^-27)
 ```
 
-## Quick Start
-
-```python
-from pipeline import WoundNetB7Pipeline
-
-pipe = WoundNetB7Pipeline("models/")
-result = pipe.analyze("path/to/dfu_image.png")
-print(result.summary())
-```
-
 ## Models
 
 | Component | Architecture | Metric | Value |
 |-----------|-------------|--------|-------|
 | Segmentation | EfficientNet-B7 + UNet + ASPP + CBAM + TAM | Ulcer Dice | 0.927 |
-| PWAT Item 3 | XGBoost + SMOTE | MAE / Adjacent | 0.87 / 74.9% |
 | PWAT Item 7 | XGBoost + SMOTE | MAE / Adjacent | 0.61 / 89.3% |
 | Fitzpatrick | ITA calibrated thresholds | Exact match | 86.9% |
 
-## Fitzpatrick/ITA Calibrated Thresholds
-
-| Type | ITA Range | Description |
-|------|-----------|-------------|
-| I | > 46.86 | Very Light |
-| II | 34.25 - 46.86 | Light |
-| III | 20.87 - 34.25 | Intermediate |
-| IV | 3.57 - 20.87 | Tan |
-| V | -28.38 - 3.57 | Brown |
-| VI | < -28.38 | Dark |
-
-## PWAT Debiasing Factors
-
-Darker skin tones tend to overestimate tissue severity (especially Item 8: Periulcer Skin).
-Correction factors reduce this bias:
-
-| Type | P3 | P4 | P5 | P6 | P7 | P8 |
-|------|-----|-----|-----|-----|-----|-----|
-| I-II | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
-| III | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -0.1 |
-| IV | -0.1 | -0.1 | 0.0 | 0.0 | 0.0 | -0.3 |
-| V | -0.2 | -0.2 | -0.1 | 0.0 | 0.0 | -0.6 |
-| VI | -0.3 | -0.3 | -0.2 | -0.1 | 0.0 | -0.9 |
-
-## Dataset
-
-- **Segmentation training**: 2,245 images (1,571 train / 336 val / 338 test)
-- **Multiclass validation**: 461 images with 5-class expert masks
-- **PWAT labels**: 1,321 images (920 expert GT + 401 AI consensus)
-- **Fitzpatrick calibration**: 61 images with expert skin type annotations
-
-## Deploy to Hugging Face
-
-```bash
-# Clone this repo to a HF Space
-git clone https://huggingface.co/spaces/YOUR_USER/woundnetb7
-# Copy models/ directory (or use git-lfs for large files)
-git lfs install
-git lfs track "*.pt" "*.pkl"
-git add . && git commit -m "Initial deployment"
-git push
-```
-
 ## License
 
 Research use only. Clinical deployment requires regulatory approval.
-
-## Citation
-
-```bibtex
-@article{marquez2026woundnetb7,
-  title={WoundNetB7: Automated PWAT Protocol using Topological AI for Diabetic Foot Ulcers},
-  author={M{\'a}rquez-Sandoval, Marcelo},
-  year={2026}
-}
-```