- Add _vulkan_available(): checks /dev/dri/renderD* on Linux, assumes
true on macOS/Windows; set REALESRGAN_NCNN=force to override
- Add _test_ncnn_binary(): test-runs the binary after install and checks
stderr for "no vulkan" — marks skipped if Vulkan init fails at runtime
- ensure_ncnn_installed() now returns early with state=skipped when no
Vulkan detected, avoiding a wasted ~30MB download on CPU-only servers
- Recommend PyTorch CPU when available on headless (AI quality, slow but
works); Lanczos as final fallback
- Frontend: handle state=skipped immediately (no polling needed), show
brief informational toast; show "Headless server" note in dialog
https://claude.ai/code/session_01B58MaJCU1R6KwBDJCp8AfN
- 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
Claude