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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@@ -27,6 +27,33 @@ use dr_decode::RawImage;
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pub use noise::{NoiseModel, Source};
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pub use tile::{TileNet, HALO};
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/// TRACES: FR-DEV-3g
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/// A network the app ships in `models/denoise/`: its file, and the context
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/// it needs past a tile's kept centre (docs/dev/denoise.md §13).
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#[derive(Debug, Clone, Copy, PartialEq, Eq)]
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pub struct Shipped {
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pub file: &'static str,
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pub halo: usize,
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}
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/// The smallest student: 0.9 M parameters, 11 GMAC a megapixel.
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pub const FAST: Shipped = Shipped {
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file: "mosaic-fast-1408.onnx",
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halo: HALO,
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};
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/// A student of the mixture with the first release's shape: 3.2 M
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/// parameters, 48 GMAC a megapixel.
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pub const MEDIUM: Shipped = Shipped {
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file: "mosaic-medium-1408.onnx",
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halo: HALO,
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};
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/// The mixture: a flat expert, an edge expert and the gate that blends them.
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/// It reaches further than either, so it keeps a smaller centre of each tile.
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pub const BEST: Shipped = Shipped {
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file: "mosaic-best-1408.onnx",
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halo: 256,
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};
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#[derive(Debug, thiserror::Error)]
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pub enum DenoiseError {
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#[error("the network cannot take this photograph: {0}")]
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