The WebGPU execution provider has no PReLU kernel. The model is 34 convolutions
with a PReLU after every one of them, so an export that took the GPU path was
split 33 times: each activation came off the chip to be activated on the
processor and went straight back, a 64-channel map in both directions, per tile.
A machine with a good graphics chip was not exporting any faster for having it.
PReLU(x) is exactly Relu(x) - slope * Relu(-x), and Relu, Neg, Mul and Sub the
provider does implement, so scripts/realesr-gpu.py writes the 33 activations out
as those four and drops the slopes nobody reads any more. The model file is the
output of that script, not the file as published.
One 256x256 tile through the model before and after, on a WebGPU session: the
runtime no longer reports nodes left off the preferred provider (it did, once,
before) and the processor path answers bit for bit what it answered before. The
warning itself cannot be switched off from here - env.logLevel is read when the
runtime module initialises, before any of this runs - so the graph was fixed
rather than the lines hidden.
The server still never sees a photo, so the model has to run in the page.
Real-ESRGAN x4v3 ships as a 4.9MB ONNX in public/models and is loaded
lazily on the first export that actually needs it; the wasm runtime is
copied next to CanvasKit at build time and stays lazily fetched, cached
for 30 days. Vite is told onnxruntime-web is external-wasm so no 28MB
asset lands in the bundle.
UNCHANGED keeps the old path and the tier cap; 2K/4K/custom upscale only
when the request is larger than the photo being edited, otherwise they
resize down. Guests keep UNCHANGED and 2K. Tiling is 256px with an 8px
overlap, so memory follows the target size rather than four times it.
`docker/` now holds the whole web build — frontend (Vite + React + CanvasKit),
backend (Fastify + SQLite) and the compose file — so the folder can be moved to
another machine and run without the React Native project:
cd docker && cp .env.example .env && docker compose up -d --build
Only `${WEB_PORT:-8090}` is published; nginx serves the SPA and proxies /api to
the `api` container over Docker's DNS. Photos never reach the server.
The shared render code is vendored into `docker/frontend/shared/` and aliased to
a CanvasKit shim, so the app's own frameUtils/toneShader/jpegDpi run unchanged.
Fix the all-black render on GPU surfaces: `MakeWebGLCanvasSurface` creates a
separate WebGL context per call, and a texture from one context cannot be
sampled by a surface on another — so any pass that drew a snapshot onto a second
surface (output sharpen, screen sharpen, polaroid/wallframe cards) came out
solid black, while the raster fallback was correct. Use one shared
GrDirectContext + MakeRenderTarget instead.
Verified in headless Chromium against the running stack: 12MP JPEG in, preview
mean=120.5 sd=60.5, export 2048x1536 mean=107.2 sd=62.1, JFIF density 300/300,
EXIF present, no console errors; health/signup/login/me/recipes all 2xx through
the nginx proxy.