Introduce Pattern Template entity as a reusable rectangle layout that
Key Colors targets reference via pattern_template_id. This replaces
inline rectangle storage with a shared template system.
Backend:
- New PatternTemplate data model, store (JSON persistence), CRUD API
- KC targets now reference pattern_template_id instead of inline rectangles
- ProcessorManager resolves pattern template at KC processing start
- Picture source test endpoint supports capture_duration=0 for single frame
- Delete protection: 409 when template is referenced by a KC target
Frontend:
- Pattern Templates section in Key Colors sub-tab with card UI
- Visual canvas editor with drag-to-move, 8-point resize handles
- Background capture from any picture source for visual alignment
- Precise coordinate list synced bidirectionally with canvas
- Resizable editor container, viewport-constrained modal
- KC target editor uses pattern template dropdown instead of inline rects
- Localization (en/ru) for all new UI elements
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Introduce Picture Stream abstraction that separates the capture pipeline into
composable layers: raw streams (display + capture engine + FPS) and processed
streams (source stream + postprocessing template). Devices reference a picture
stream instead of managing individual capture settings.
- Add PictureStream and PostprocessingTemplate data models and stores
- Add CRUD API endpoints for picture streams and postprocessing templates
- Add stream chain resolution in ProcessorManager for start_processing
- Add picture stream test endpoint with postprocessing preview support
- Add Stream Settings modal with border_width and interpolation_mode controls
- Add stream test modal with capture preview and performance metrics
- Add full frontend: Picture Streams tab, Processing Templates tab, stream
selector on device cards, test buttons on stream cards
- Add localization keys for all new features (en, ru)
- Migrate existing devices to picture streams on startup
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This is a complete WLED ambient lighting controller that captures screen border pixels
and sends them to WLED devices for immersive ambient lighting effects.
## Server Features:
- FastAPI-based REST API with 17+ endpoints
- Real-time screen capture with multi-monitor support
- Advanced LED calibration system with visual GUI
- API key authentication with labeled tokens
- Per-device brightness control (0-100%)
- Configurable FPS (1-60), border width, and color correction
- Persistent device storage (JSON-based)
- Comprehensive Web UI with dark/light themes
- Docker support with docker-compose
- Windows monitor name detection via WMI (shows "LG ULTRAWIDE" etc.)
## Web UI Features:
- Device management (add, configure, remove WLED devices)
- Real-time status monitoring with FPS metrics
- Settings modal for device configuration
- Visual calibration GUI with edge testing
- Brightness slider per device
- Display selection with friendly monitor names
- Token-based authentication with login/logout
- Responsive button layout
## Calibration System:
- Support for any LED strip layout (clockwise/counterclockwise)
- 4 starting position options (corners)
- Per-edge LED count configuration
- Visual preview with starting position indicator
- Test buttons to light up individual edges
- Smart LED ordering based on start position and direction
## Home Assistant Integration:
- Custom HACS integration
- Switch entities for processing control
- Sensor entities for status and FPS
- Select entities for display selection
- Config flow for easy setup
- Auto-discovery of devices from server
## Technical Stack:
- Python 3.11+
- FastAPI + uvicorn
- mss (screen capture)
- httpx (async WLED client)
- Pydantic (validation)
- WMI (Windows monitor detection)
- Structlog (logging)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
