ROOT CAUSE: ImageCanvas referenced props that don't exist:
- activeTool, onSmartSelect, onColorSelect were used but never declared
- selectionMode checked for 'smart'/'color' but App passes advancedToolMode with 'smart-select'/'color-select'
Changes:
- Update mode checking to use advancedToolMode instead of selectionMode for smart/color select
- Replace onSmartSelect/onColorSelect calls with onAdvancedToolClick
- Fix useEffect dependency array to reference actual props
- Add missing state/refs: currentZoom, imageRef, baseScaleRef, isDrawingRef
- Add zoom control buttons to canvas UI
- Fix tool mode indicator to check advancedToolMode
- Add zoom support via prop (scales image around center)
- Fix selection interaction: clicking on selection transforms, clicking elsewhere creates new
- Use refs for state accessed in event handlers (fixes stale closure issue)
- Add smart select mode (clicks call onSmartSelect with image coordinates)
- Add color select mode placeholder
- Add pan mode with cursor feedback
- Add move mode for manipulating selections
- Use dashed blue selection style (more visible)
- forwardRef to expose canvas methods
- Redesign layout: left toolbar, center canvas, right sidebar
- Add vertical tool strip with keyboard shortcuts (V, R, E, F, W, B, G, Z, H)
- Collapsible sidebar panels: Tool Options, AI Edit, Quick Actions, Eyes, Layers, History
- Canvas now fills available space with checkerboard background
- Add zoom controls in status bar
- Add menu bar with New, Save, Reset
- Remove old multi-column layout
- Create unified Dockerfile with multi-stage build (Node + Python)
- FastAPI now serves React static files directly
- Remove frontend service and nginx dependency
- Simplify docker-compose to single service
- All routes work without proxy configuration
Frontend changes:
- Wire Smart Select and Color Select to canvas click handlers
- Add externalSelection prop to ImageCanvas for displaying AI-generated selections
- Add zoom controls (mouse wheel + buttons) to ImageCanvas
- Fix layer buttons (New Layer, Delete, Duplicate) with proper handlers
- Lift advancedToolMode state to App.jsx for coordination between components
- Add tool mode indicator overlay on canvas
Backend changes:
- Update smart-select endpoint to return JSON with polygon and bbox data
- Update color-select endpoint to return JSON with polygon and bbox data
- Add _mask_to_polygon helper function using OpenCV contour detection
- Add cv2 and base64 imports to tools.py
API changes:
- smartSelect and colorSelect now return { polygon, bbox, mask_base64 }
- Fix database path mismatch: download_sample_eyes.py now uses
ai_photo_edit.db instead of photoedit.db
- Add init_database.py script to initialize DB before eye import
- Add AUTO_DOWNLOAD_SAM=true environment variable (default: enabled)
- Update entrypoint.sh to:
1. Initialize database first
2. Auto-download SAM model (~375MB) on first startup
3. Then import eyes (now works since DB exists)
- Update path detection to work in both Docker and local environments
- Add torch, torchvision, segment-anything to requirements
- Create download_sam_model.py script to fetch SAM checkpoint
- Update tools.py to use local SAM with Replicate API fallback
- Add SAM model check to entrypoint.sh with helpful instructions
- Model persists in /app/data/models via Docker volume mount
- Create entrypoint.sh that auto-downloads sample eyes on first run
- Update Dockerfile to use entrypoint script
- Rewrite .env.example with step-by-step setup instructions
- Add detailed troubleshooting section
- Clarify which models work for inpainting vs text-to-image
- Implement SAM object selection via Replicate API
- Click on any object to select it with AI precision
- Falls back to flood-fill if Replicate API unavailable
- Update Dockerfile for rembg dependencies
- Add required system libraries (libsm6, libxext6, etc)
- Pre-download rembg model during build
- Create data directories for models and patches
Backend:
- Add /tools router with background removal, smart select, color select
- Add rembg dependency for AI background removal
- Add layer management API (list, flatten)
- Fix transparency preservation in blend_patch (veil collapse fix)
- Preserve alpha channel when reverting/resetting images
Frontend:
- Add AdvancedTools panel with background removal, smart select, color select
- Add Layers panel with drag-to-reorder, visibility toggle, flatten
- Add toolsApi for new backend endpoints
- Make right panel scrollable for additional controls
This adds "Photoshop light" capabilities:
- Remove background and create layer
- Smart object selection (click to select)
- Color selection with tolerance
- Layer system with compositing
Creates scripts/download_sample_eyes.py that:
- Downloads public domain classical sculpture images from Wikimedia
- Creates patch records in database
- Generates thumbnails
- Populates the Eye Catalog with starter content
Fixes:
- Remove scale limit to allow image to fill canvas
- Fix Lasso tool by using Polygon instead of Polyline
- Remove duplicate Clear Selection button
- Fix Undo/Redo dependencies with useCallback
New Features:
- Eye Catalog UI for browsing and applying saved eyes
- Upload new eyes to catalog
- Apply eyes to selected areas with feathering
- Delete eyes from catalog
- Make canvas use full viewport height for larger image display
- Add download button to export edited images
- Implement Undo/Redo with Ctrl+Z / Ctrl+Y keyboard shortcuts
- Add transform controls for selections (move, resize, rotate)
- Add warn on reload to prevent data loss
- Make project naming optional, auto-generate from filename
Added complete system for populating eye catalog with classical carved eyes:
Features:
- Eye import script (import_eyes.py) for batch/single eye imports
- Public domain source guide (museums: Met, Smithsonian, Getty, etc.)
- Seed catalog system for pre-populating database
- Organized by emotion (serene, fierce, wise, peaceful, etc.)
- Organized by style (Greek, Roman, Egyptian, Renaissance)
- Organized by side (left, right, both)
- Auto-generates thumbnails and metadata
- CNC-ready tagging system
Workflow:
1. Download classical sculpture photos from public domain museums
2. Crop eyes in any image editor
3. Run import script with metadata
4. Eyes saved to catalog with proper tags
5. Apply to colored photos (pure image compositing, no AI regeneration)
6. Convert result to grayscale for CNC carving
Documentation:
- PUBLIC_DOMAIN_EYE_SOURCES.md: Where to find carved eyes
- scripts/README.md: How to import eyes
- Includes recommended starting collection (10 essential eyes)
Benefits for wood carving:
- Build library from master sculptors (2000+ years of proven designs)
- Reusable across all projects
- Consistent emotional weight in carvings
- No AI regeneration - just intelligent copy/paste/blend
- Perfect for CNC workflow (colored preview → grayscale → carve)
The patch library system uses PIL/OpenCV for image compositing,
NOT AI regeneration, so it preserves exact carved geometry.
- Changed backend port from 8000 to 8101 (avoiding port conflict)
- Added REPLICATE_API_KEY to docker-compose environment variables
- Simplified Caddyfile - only need to reverse proxy frontend
- Frontend nginx internally handles routing API calls to backend
- Fixed nginx.conf to proxy all API routes (/patches, /generate, /health, /docs)
- Changed frontend port to 3080 in docker-compose.yml
- Added Caddyfile for Caddy2 reverse proxy configuration
- Supports both FQDN and IP:port configurations
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