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* LR-EDIT-DETAIL-DENOISE: AI Denoise works out of the box with a built-in denoiser Turning AI Denoise on no longer needs an ONNX model and a denoise-model.json. Without a model of the user's own, the engine runs a built-in pure-Rust denoiser (noise measured per tile, non-local means on the Bayer planes, edge-directed demosaic) through the same tiling, cache, queue, preview and export path as a model. Installing a model stays optional; Stop using returns to the built-in one, and the id `builtin` is reserved. The set-up prompt and its resume-after-install flow (model_setup.rs, PhotoState::NoModel) are removed. Tests updated for the new behaviour, with new tests for the built-in path; docs, trackers and locale catalogs updated. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: built-in denoiser cleans the colour planes together and adapts to the noise The built-in denoiser now measures the photo's noise once from the whole mosaic (the model prepares the photo before its tiles run) instead of per tile, stabilises the variance (generalised Anscombe), rotates the four Bayer planes with a Hadamard transform and runs a non-local-means filter whose patch distance spans all planes, so colour blotches are cleaned with the brightness. It cleans gently at low noise to keep fine detail, and harder, with a second pass that matches on the first pass's cleaner picture, as the noise grows. Cached pictures made by the first version are made again (builtin version 2). Adds an opt-in benchmark (tests/denoise_builtin_quality.rs, public CC0 raw plus noise of known level, scored against the original) and tests for the whole-photo noise estimate, strong noise, bad noise values and the strength ramp. On the Sony A7 III sample the result is 3.6, 7.0, 9.1 and 9.7 dB above the noisy picture at light, medium, heavy and extreme noise, against 2.9, 6.0, 6.5 and 5.8 dB for the first version. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * contributors: add esli1283 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: docs say how to run the built-in denoiser's quality benchmark Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: built-in denoiser cleans colour further, keeps more texture and leaves no isolated specks Colour-difference planes get a wider pass guided by the cleaned brightness plane, the first-pass threshold is lower (more texture kept), and cells with no matching patch lean on a looser average in heavy noise. Skips negligible weights for speed; bumps builtin::VERSION to 3. Benchmark adds a texture figure; on the public A7 III raw the gain over the noisy picture is +3.7 / +7.2 / +9.7 / +10.4 dB (was +3.6 / +7.0 / +9.1 / +9.7). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Windows: tests build paths one component at a time and doc_path has no unused variable On Windows `cargo xtask ci` failed before it reached any of the work under test: - doc_path.rs bound the gvfs path outside the cfg(not(windows)) block that uses it, an unused variable under -D warnings. - tests_import and the MCP headless discovery test joined "trip/day2" onto a temp folder, giving mixed separators, and compared them with the normalised paths the folder walk returns. They now join each component. Test and lint changes only. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: built-in denoiser filters with block-matching collaborative filtering, on the GPU The built-in denoiser's filter is now block matching with collaborative filtering (BM3D / CBM3D, written from the paper) instead of non-local means. On the public Sony A7 III benchmark with added noise it scores 0.25 to 0.6 dB higher at every noise level and keeps more texture at medium to extreme noise (light noise keeps slightly less: 0.58 against 0.62), as fast as before on the processor. docs/denoise.md records the comparison with non-local means and weighted nuclear norm minimisation (tried, not kept: about +0.03 texture for ten times the time) and what the tuning showed. - denoise-core: bm3d.rs (matching on the brightness plane, 2-D DCT plus Haar across the group, hard threshold then Wiener, hard threshold rising with the noise). Builtin::run_with takes the filter stage, so every other step is shared between devices. Tuning.bm3d selects it; non-local means stays as the fallback. builtin::VERSION is 4, so cached pictures are made again. - gpu: bm3d.rs and wgsl/bm3d_*.wgsl run the grouping, the filtering and the putting back on the graphics card, in the same order as the reference (the results agree to rounding: at most 0.1 noise deviation at a few tie blocks, 4e-6 on average, identical every run). Noise measurement, stabilising and the demosaic stay on the processor. FXC (DX12) needs the working arrays at module scope and no dynamically indexed vector: documented in docs/gpu-pipeline.md. - engine: the card is set up once per process for the first photo that may use it, checked against the processor on a check tile (in the filter's own domain: the demosaic's direction choice can flip a pixel on a tiny difference), timed, and used where it is faster. A tile it gets wrong runs on the processor and three stop it. Settings' Run on choice, device line and "Try the graphics card again" now work for the built-in denoiser. Its set-up marker lives in the models folder. - The benchmark takes LC_GPU=1, LC_NLM=1 and LC_B_* for sweeps. On an RTX 4080 SUPER a 256-cell tile takes 22 ms on the card against 408 ms on one processor thread, and the 1536 x 1024 benchmark crop 0.13 to 0.24 s against 1.0 to 2.1 s on four threads, with identical scores. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: the built-in denoiser measures the noise per colour plane and sets its strength from it The first noise estimator read a picture's texture as noise: it never reported less than about 0.003 at mid-grey whatever the real noise, so the denoiser always believed a photo was about as noisy as ISO 12800. The threshold curve was tuned on that over-estimate, and its levels (0.024 to 0.14) are far noisier than real Canon bodies produce (about 0.0025 at ISO 400 up to 0.038 above ISO 25600, measured on a private library; only aggregates are recorded in the docs). - estimate_noise: each colour plane is read on its own (they sit at different levels in a raw), a second-difference operator cancels flat and sloping signal, 12 x 12 blocks, the quietest 5 % at each brightness divided by the bias of that quantile of pure noise (0.67, measured), a constrained line fit. The first version stays as estimate_noise_v1 to compare with. On 30 public pictures with known added noise the 10th to 90th percentile of estimated / true deviation at mid-grey is 0.97 to 1.29 at the ISO 6400 level against 0.94 to 1.96. - bm3d::Params::lambda is a curve of the noise (1.2 at 0.0028 up to 3.5 at 0.14, straight against its logarithm) instead of two end values and a strength, and plan / filter take the noise level; the GPU path shares plan, so CPU and GPU agree as before. Fitted on clean low-ISO photos of a Canon EOS R and R6 Mark III with noise of their measured levels added: the lowest threshold within about a quarter of a decibel of the best at each level. - Result (PSNR, EOS R / R6 Mark III, 10 + 5 photos): ISO 25600 level 38.36 / 38.86 from 36.18 / 36.21, ISO 51200 level 33.83 / 34.45 from 28.42 / 28.78, ISO 6400 39.93 / 40.69 from 39.30 / 39.74, quiet photos no longer over-smoothed; the noise left in the result falls from 1.3 to 3.1 down to 0.73 to 0.99. - Tests: threshold curve, flat versus textured pictures, no-flat-area pictures, clipped / NaN mosaics; an opt-in accuracy harness on the public corpus (denoise_noise_estimate) with a calibration of the quantile bias; the benchmark takes LC_REAL, LC_BIN, LC_FULL, LC_EST and LC_B_LOFF. - builtin::VERSION is 5, so cached pictures are made again. docs/denoise.md has "How the noise is measured" and "Fitted on real cameras". Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: GPU workspace pool cannot miss a wake-up; benchmark path and parity date fixed Review findings (CodeRabbit) on the built-in denoiser pull request: - bm3d::Bm3dGpu::forget and nn::NetRunner::forget changed the workspace count without the free-list lock. A take() that had found no free workspace and read made == WORKSPACES, but had not gone to sleep yet, could miss the wake-up and wait for good on a slot that was already free. forget now changes the count under the free lock, in the same order as take(), then notifies. - A test for each runner holds the free lock and checks that forget waits for it; both fail on the old code and pass now. - docs/denoise.md: the benchmark command resolves the raw file from the repository root, since the test runs from the crate's folder. - docs/target-app-parity.md: Last updated matches its newest revision-history entry. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: doc comments for the functions this branch adds CodeRabbit's pre-merge docstring check counted 49.72 % of the functions this pull request touches as documented (threshold 80 %). Every function the branch adds, the built-in denoiser's block-matching and non-local-means filters, its noise estimator, the GPU runner and their tests, now says what it does or what the test proves. Older functions the branch only touched are left as they were. Comments only: no code line changes. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: make the GPU set-up marker's folder; fix the benchmark's default path The crash guard was lost when the models folder did not exist yet. The opt-in quality benchmark resolved its default raw file against crates/engine. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: enforce the cache limit without a models folder The built-in denoiser makes products when there is no models folder, but eviction returned early in that case, so the cache could outgrow its limit. It now applies the default limit. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * LR-EDIT-DETAIL-DENOISE: the cache-limit test needs no 20 GiB file off Unix The no-models-folder test now checks the limit itself on every platform and keeps the oversized sparse file for Unix only. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * S0002: review fixes for the built-in denoiser Tell the runner a photo's noise only when it could be measured, run prepare() after the work gate with a cancel check, reword the Settings hint for builds without a models folder, drop untranslated placeholder locale entries (they fall back to English) and restore the cs.json spacing; rustfmt. Co-Authored-By: Claude Code <noreply@anthropic.com> * S0002: fix review findings: command descriptions, stale gpu test, self-test noise The denoise.models.select and denoise.toggle descriptions now describe the built-in fallback. Drop our workspace-forget test, which read fields that upstream's Workspaces pool (#2631, same fix) replaced and so did not compile; upstream's own tests cover it. The built-in self-test is told a noise instead of measuring a 16-cell tile too small to measure. Co-Authored-By: Claude Code <noreply@anthropic.com> --------- Co-authored-by: esli1283 <esli.aaron@outlook.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Claude Code <noreply@anthropic.com> Co-authored-by: FredApps <FredApps@users.noreply.github.com>
lightcraft-denoise-core
L1 model metadata, bounded archive/cache formats and Bayer packing/tiling helpers.
No weights or inference backend. See the user workflow.
lightcraft-denoise re-exports these types for CPU/GPU users; the engine uses this
crate directly when inference is disabled. The default download catalog is empty.
Run cargo test -p lightcraft-denoise-core; optional catalog checks use --features rawnind-model.
The Bayer runner rejects non-finite source samples before inference and non-finite results after gain matching, highlight protection and tile blending. Finite negative and HDR source samples remain supported. These guards do not implement Raw Details or Super Resolution.