8a11325b2f
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.
28 lines
456 B
TOML
28 lines
456 B
TOML
[build-system]
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requires = ["setuptools>=64"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "vnassets"
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version = "0.1.0"
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requires-python = ">=3.12"
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dependencies = [
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"torch",
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"diffusers",
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"transformers",
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"accelerate",
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"safetensors",
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"pillow",
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"pyyaml",
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"click",
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"compel",
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"rembg",
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"onnxruntime",
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]
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[tool.setuptools.packages.find]
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exclude = ["models*"]
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[project.scripts]
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vnasset = "vnassets.cli:main"
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