Offer three denoise networks and a method to choose between them
AI Denoise's Apply switch becomes Method: Bilinear, Fast, Medium, Best, default Best, so an untouched raw writes nothing and develops through the mixture. `apply` is still read and never written: 0 is Bilinear, 1 keeps a network already chosen. - Best is the mixture of a flat and an edge expert with a learned gate; Medium and Fast are students distilled from it. 2.48 s, 0.79 s and 0.57 s for a 20 MP frame on TensorRT fp16. - Each network carries its own tile border (256 for the mixture, 192 for the students) through `dr_denoise::Shipped` and `TileNet::halo`. - The file is hashed once at open and each network keys its own cached result; Bilinear keeps the result in memory for the way back. - Each has an .a16w16 sibling for the Hexagon: 0.00 dB on the 6D gate, at most 0.11 dB with the noise scaled x0.5 to x4. - APK BUNDLED 19 -> 23; the PKGBUILD installs all three.
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@@ -124,12 +124,15 @@ package() {
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fi
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install -Dm644 "${_src}" "${pkgdir}/usr/share/darkroom/models/migan-512.onnx"
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# The learned demosaic and denoise (the project's own weights, GPL —
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# models/LICENCE.md). Same pointer check, same directory.
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_src="models/denoise/mosaic-1408.onnx"
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if [[ "$(stat -c%s "${_src}")" -lt 100000 ]]; then
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echo "error: the denoise model is an LFS pointer — run: git lfs pull" >&2
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return 1
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fi
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install -Dm644 "${_src}" "${pkgdir}/usr/share/darkroom/models/mosaic-1408.onnx"
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# The learned demosaic and denoise, one network per method (the project's
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# own weights, GPL — models/LICENCE.md). Same pointer check, same
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# directory.
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for _net in fast medium best; do
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_src="models/denoise/mosaic-${_net}-1408.onnx"
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if [[ "$(stat -c%s "${_src}")" -lt 100000 ]]; then
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echo "error: the ${_net} denoise model is an LFS pointer — run: git lfs pull" >&2
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return 1
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fi
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install -Dm644 "${_src}" "${pkgdir}/usr/share/darkroom/models/mosaic-${_net}-1408.onnx"
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done
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}
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