A newer version of the Gradio SDK is available: 6.14.0
metadata
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 — DFU Analysis Pipeline
Complete pipeline for Diabetic Foot Ulcer analysis:
- Binary segmentation (ulcer detection, Dice: 0.927)
- Multiclass segmentation (background / foot / perilesion / ulcer)
- Fitzpatrick/ITA skin type estimation (86.9% accuracy)
- PWAT scores with Fitzpatrick debiasing (46.6% group gap reduction)
Features
- Guided camera capture with foot silhouette overlay for healthcare workers
- PDF clinical report downloadable with all results
- JSON output for system integration
Model
EfficientNet-B7 + ASPP + CBAM + CoordAttention + TAM (Topological Attention Module)
Trained with Combo Loss + Small Object Focal Loss. 6-fold TTA at inference.