Wire integrated dashboard renderer (src/integrated_report.py)

Wire integrated dashboard renderer (pipeline.py)

Add integrated DFU dashboard + Fitzpatrick adjustment (English UI)

revert: remove post-processing, use raw model output — works best for majority of images

fix: iterative necrotic recovery (3x30px) — bridges gap to necrotic toes

feat: necrotic tissue recovery — dark regions adjacent to foot reclassified as ulcer

fix: shadow filtering + adaptive ITA trimming + increased periulcer dilation (60px) — reduces Fitzpatrick overestimation

fix: preserve dark necrotic tissue connected to foot, only remove isolated dark blobs

feat: postprocess segmentation — largest component + dark pixel exclusion + morphological cleanup

feat: lighting quality assessment for Fitzpatrick estimation

feat: lighting quality assessment for Fitzpatrick estimation

fix: use CPU-only PyTorch for faster build on cpu-basic

fix: update README to trigger clean rebuild

feat: PDF report + guided camera capture with foot silhouette

feat: PDF report + guided camera capture with foot silhouette

feat: add downloadable clinical report (PNG 300 DPI + JSON)

feat: add downloadable clinical report (PNG 300 DPI + JSON)

feat: upgrade pipeline UI — binary seg + multiclass + PWAT raw vs adjusted

feat: upgrade pipeline UI — binary seg + multiclass + PWAT raw vs adjusted

Update README.md

Fix: load 30 selected features from JSON instead of guessing from model

Add selected feature columns (30 of 63 after correlation filter)

Fix: extract feature names from XGBoost model to match training feature selection (30 vs 63)

Fix: lazy loading, disable TTA on CPU, error handling, remove double inference

Fix README with Gradio SDK metadata

Add WoundNetB7 segmentation checkpoint (311MB)

Add pipeline code, PWAT models, and Gradio app

initial commit