Add colleague setup guide and env template for Change-Detection-DEV repo.

Add Phase 4 reports: PDF export, browser report page, and notification bell.

Deploy DDA jobs API, hierarchy panel, and region locate on dev.

Fix Run Detection: use /api/dda/detect/from-library and deploy compare UI.

Fix dev Space startup: add missing DDA modules referenced by local_routes.

Raise library GeoTIFF upload limit to 5 GB on dev.

HF library: auto DDA on satdetect-dev, upload to persistent storage

Fix local library scan: DDA mode in run.py, path encoding, gitignore large tifs

Use local library_sources year folders instead of web upload library

Support 2GB GeoTIFF library uploads with streamed writes and progress UI

Phase 0 DDA: APP_MODE, image library API, GeoTIFF ingest, dev UI

Align production with no-login app and refresh deploy docs

Remove login; open detection page directly

Add run.py launcher (IDLE/double-click/terminal entry point)

Add WORKFLOW.md: project workflow and onboarding guide

Fix detection precision: gated fusion, strict registration, calibrated thresholds, preload model

Fix: rename models/ to cd_models/ to avoid shadowing app/models.py (SQLAlchemy User model)

Add SIFT+FLANN registration, Siamese U-Net, multi-scale detection, ExG vegetation, Hybrid AI mode, confidence maps

Improve building detection: fix tile size to 256, lower thresholds, add SSIM, smarter scoring

Fix: add einops dependency required by AdaptFormer custom code

Fix: add trust_remote_code=True for AdaptFormer custom model code

Production overhaul: pre-trained AdaptFormer model + detection quality improvements

Optimize notebook for CPU training: MobileNetV2 encoder, 15 epochs, batch 4

Fix notebook: use HuggingFace datasets CDN instead of flaky Google Drive links

Add Siamese U-Net training notebook and model inference integration

Clean visualization: subtle tint overlay, outline-only boxes, 30-region cap, high-contrast labels

Redesign detection pipeline: CVA, vegetation/shadow suppression, SNR fusion, multi-scale SSIM

Thinner, more precise detection lines and compact labels

Restore Method dropdown, Image Registration and Radiometric Normalization options

Force cache bust - bump APP_BUILD, CSS and JS versions

Remove method/model selection UI - use AI-Based Deep Learning by default

Revert to satellite change detection only - remove landslide, pothole, detection type menu

Pothole YOLO pipeline: single-image mode, modular detector, red box visualization

Add pothole detection as new menu type with separate engine and research plan

HF runtime fix: bind uvicorn to dynamic PORT env

UX: always land on detection-type menu after login

Fix detection-type menu navigation: switch mode and dashboard without reload loop

UX: show detection-type menu after auth then auto-redirect based on URL

HF: force writable hub cache (/tmp/hf)

HF: relax pip wheel-only; upgrade pip tools

HF: ensure pip uses binary wheels during build

HF: make Docker builds verbose; move APP_BUILD cache-bust before pip

UX: show detection-type menu after login before redirect

HF: bump APP_BUILD to force rebuild

UX: add choose detection type screen and redirect URLs

HF: bump APP_BUILD to force clean Docker rebuild

Add landslide detection menu, separate engine, and Uttarakhand integration plan

AI/Hybrid overhaul: bidirectional AI fusion, stronger hybrid sensitivity, keep large unclassified regions

AI rework: percentile+blur threshold + less aggressive cleanup; Hybrid lower threshold

Fix: fallback to Image Difference when AI/Hybrid mask is too sparse