- Add 18x24" to FRAME_SIZES in backend and frontend (frame_fit.js)
- Add 200 DPI option to frame_fit dialog (adequate for large-format prints)
- Add 18x24 portrait/landscape at 200 and 300 DPI to Canvas Size presets (size.js)
- New /api/print/prepare endpoint: chains AI upscale to target DPI then frame-fit
in one server-side call (avoids round-tripping a large upscaled image)
- New print_prepare.js module: "Prepare for Print" dialog with per-frame quality
assessment (current effective DPI, needed upscale factor, AI vs Lanczos note)
- Add "Prepare for Print..." to Image menu above "Fit to Frame..."
https://claude.ai/code/session_01WVDg7amsy1TTtxvpku7bcM
- upscale.py: add InstallStatus dataclass + ensure_ncnn_installed() async
function that downloads and extracts the NCNN binary for the current
platform (Linux/macOS/Windows), tracks progress (0-100%), and busts the
caps cache when done
- main.py: trigger ensure_ncnn_installed() as a background task on app
startup when no AI upscaler is detected
- print_tools.py: /upscale/available triggers install task when no AI
upscaler found; new GET /upscale/install-status endpoint for polling
- upscale.js: if no AI upscaler on open, poll install-status showing a
progress bar notification, then refresh caps and proceed when done
https://claude.ai/code/session_01B58MaJCU1R6KwBDJCp8AfN
Detection priority (probed once, cached):
1. Real-ESRGAN PyTorch + CUDA GPU → fastest, best quality
2. Real-ESRGAN PyTorch + Apple MPS → fast on Apple Silicon
3. Real-ESRGAN NCNN Vulkan binary → fast on any GPU via Vulkan (no CUDA needed)
4. Real-ESRGAN PyTorch CPU → works, slow (warned in UI)
5. Lanczos → always available, instant fallback
Backend:
- services/upscale.py: full capability probe (probe_upscale_capabilities),
implementations for PyTorch (CUDA/MPS/CPU auto-device) and NCNN binary,
upscale_sync() resolves method with fallback chain,
async upscale_image() runs in thread pool
- print_tools.py: /api/print/upscale uses new service; method="auto" by default;
GET /api/print/upscale/available returns full capability map with device info
and recommended_label; POST /api/print/upscale/refresh-caps busts cache
without restart (useful after installing NCNN binary into container)
Frontend:
- upscale.js: fetches capability map on first open; builds method selector showing
only available options; labels recommended method with ★; shows device info
(CUDA/MPS/CPU/NCNN) in dialog; maps display label back to method key on submit;
shows actual method used in success toast and undo history entry
Scripts:
- scripts/download_realesrgan.py: downloads NCNN Vulkan binary for current platform
(Linux/macOS/Windows) to /app/data/models/realesrgan/; makes executable;
run inside container or locally
https://claude.ai/code/session_01B58MaJCU1R6KwBDJCp8AfN
Backend — new /api/print/* router:
- POST /api/print/frame-fit: fit image to 4x6/5x7/8x10/11x14/16x20/20x24/24x36
and square sizes (4x4/8x8/12x12) at configurable DPI.
Three modes:
crop — center-crop to aspect ratio, Lanczos scale to print res (no AI)
extend — scale to fill one dimension, AI-inpaint the gap; mirror-fill fallback
smart — auto: extend if gap < 15% of frame dimension, else crop
Auto-detects orientation from image shape; respects explicit portrait/landscape.
- POST /api/print/upscale: Lanczos scale (always) or Real-ESRGAN (if installed)
- GET /api/print/frame-sizes: frame catalogue with pixel dimensions at 300dpi
- GET /api/print/upscale/available: reports whether Real-ESRGAN is installed
Frontend:
- modules/image/frame_fit.js: dialog with frame size, orientation, mode, DPI,
optional extend prompt; shows current image size; result as new layer option
- modules/image/upscale.js: dialog with scale factor (1.5–4×), method selector
(auto-hides AI option if Real-ESRGAN not available); result as new layer option
- config-menu.js: Fit to Frame... and Upscale... added under Image menu
https://claude.ai/code/session_01B58MaJCU1R6KwBDJCp8AfN
Claude