rembg with ONNX Runtime on CPU was chosen over BiRefNet: the latter
requires deform_conv2d which crashes on ROCm bfloat16 and runs at 40s
in float32. rembg delivers 0.23s per 1024x1024 image, no GPU deps,
and isnet-anime is trained specifically on anime images — exactly the
target domain.
CLI and session API both support single-image and batch (plural-first)
modes, reusing one model session across files.
- Support (word:weight), [word], ((nested)) syntax
- Support BREAK for conditioning chunking (.and() translation)
- Use CompelForSDXL (modern API, avoids deprecation)
- Add --raw flag to bypass weighting and fall back to plain encoding
- Update README with Prompt Syntax section and examples
- Add docs/comfyui-prompt-style.md with design doc
