Image Upscaler

Use the bundled Python scripts to run Upscayl's Vulkan-based NCNN engine locally. Download models only when selected. Preserve the source aspect ratio by default and never overwrite an input file.

Workflow

1. Inspect the input path, file type, dimensions, and available disk space.
2. Inspect the image visually and recommend one profile. If the choice materially affects the result, give the user a compact choice with the advantage, disadvantage, and additional download size. Do not block if the user does not choose; use default.
3. Choose a profile:
   • default: balanced and conservative; use when content is mixed or uncertain. Model download: about 32 MB.
   • fast: smallest and fastest; weaker fine-detail reconstruction. Model download: about 2.5 MB.
   • photo: natural photographic texture; less crisp on text and architecture. Model download: about 32 MB.
   • portrait: use for compressed, noisy, or rough natural portraits that benefit from smoother rendering. It avoids face replacement but can remove fine skin texture. Use default for already-clean AI portraits and sharp studio headshots. Model download: about 32 MB, shared with photo.
   • digital-art: clean anime, illustration, and icon edges; may oversimplify photographic texture. Model download: about 8.6 MB.
   • sharp: strongest apparent edge detail; may exaggerate noise, halos, skin, or text artifacts. Model download: about 32 MB.
4. If the selected runtime or model is not cached, explain the download and disk cost, then run setup. Read platforms.md for compatibility and cache sizes.
5. Run the upscaler or compressor. Prefer PNG for maximum upscale quality; use JPEG for strict file-size targets.
6. Verify that the output exists, has the requested dimensions, and keeps the source ratio. Report the selected profile, output path, dimensions, and file size.