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Make filter_speckle a finish-phase filter, tunable without re-clustering

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Speckle removal moves out of the frontends into Segmentation::filter_speckle,
applied in the finish phase. The color frontend now clusters with
good_min_area = 0 and the binary frontend emits every cluster, so the cached
segmentation retains all regions and the speckle threshold can be retuned via
finish() with no re-clustering. Pipeline gains a speckle_area field
(Config sets it from filter_speckle^2).

Frontend structs drop their filter_speckle_area field. Output on clean images
is unchanged (golden/equivalence pass unblessed); noisy images are filtered
downstream instead of during clustering. Adds a test tuning filter_speckle on
one cached segmentation.

Add finish-phase thin-strand filter (restores thread-like rejection)

good_min_area = 0 disabled visioncortex's thread-like rejection (which was
gated on good_min_area > 0). Reintroduce it in our repo as a finish-phase
step: Segmentation::filter_thin drops regions whose perimeter >= area
(average thickness under ~2px), using the same Shape::image_boundary_list
metric so the heuristic matches. It's toggleable on a cached segmentation
(Config::filter_thin, on by default), unlike the clustering-time version.

Exposed via CLI --keep-thin, Python filter_thin, and Node filterThin. Adds
RegionMask::perimeter/is_thin and a reuse test toggling it on one cached
segmentation. Clean-image goldens are unaffected (large regions aren't thin).

README: document binary thresholding, --keep-thin, and finish-phase filters

Add the new CLI flags (--threshold, --adaptive, --adaptive-window,
--adaptive-t, --keep-thin) to the options block and "New in 1.0"; note that
--optimize is encoding-only (precision is --path-precision) and that speckle/
thin filtering run after clustering. Add adaptive-threshold examples for CLI,
Python, and Node.

Return speckle/thin filtering to clustering (fix gum-tree regression)

good_min_area is visioncortex's clustering `deepen` gate, not a speckle
post-filter: it decides whether a small or thread-like patch is absorbed
into its nearest-color neighbour or kept as its own layer, and it enables
the thread-like rejection (perimeter < area). An earlier change set it to 0
to make filter_speckle "retunable downstream", which disabled the thin
check and reshaped the whole hierarchy — dissolving gradient-boundary
structure that clustering is meant to absorb. The Gum Tree preset's central
trunk vanished at gradient-step ~26 where the pre-1.0 path held it to 128.
Clean-logo goldens couldn't exercise it, so it shipped green.

Follow the proven webapp model instead: speckle lives inside clustering
(good_min_area = filter_speckle^2 for the colour frontend; a post-cluster
size gate for the binary frontend). The segment/finish split stays — it is
the progressive model (cluster once, re-run colour/curve/optimize cheaply);
clustering params (speckle, colour precision, layer difference, binary
threshold) re-segment.

Remove the downstream band-aids: Segmentation::filter_speckle/filter_thin,
RegionMask::perimeter/is_thin, the pipeline speckle_area/filter_thin fields,
Config::filter_thin, CLI --keep-thin, Python filter_thin, Node filterThin.
Update the two reuse tests that encoded the wrong contract and the binary
threshold test to use BinaryFrontend::min_area. All goldens, equivalence,
progress, and reuse tests pass.
This commit is contained in:
Chris Tsang
2026-07-25 16:08:10 +01:00
parent 5361a51011
commit abe21658dc
8 changed files with 67 additions and 33 deletions
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CHANGELOG.md
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@@ -10,7 +10,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/).
### Added
* Progress reporting and cancellation: `Pipeline::run_with_progress` with a `CancelToken` and a per-phase progress callback (for driving desktop UIs from a worker thread).
* Two-phase conversion for interactive tuning: `Pipeline::segment` caches the expensive clustering result as a reusable `Segmentation`, and `Pipeline::finish` re-runs only the cheap color-fitting / curve-fitting / optimization stages — so tuning those parameters no longer repays the clustering cost. Both have `*_with_progress` variants.
* Two-phase conversion for interactive tuning: `Pipeline::segment` caches the expensive clustering result as a reusable `Segmentation`, and `Pipeline::finish` re-runs only the cheap color-fitting / curve-fitting / optimization stages — so tuning those parameters no longer repays the clustering cost. (Speckle, color precision, and layer difference are clustering parameters and require a fresh `segment`.) Both have `*_with_progress` variants.
* Binary thresholding methods: a tunable fixed threshold and Bradley–Roth adaptive thresholding (via visioncortex's summed-area table) for images with uneven lighting. Exposed on `Config` (`binary_threshold`, `binary_adaptive`, `binary_adaptive_window`, `binary_adaptive_t`), the CLI (`--threshold`, `--adaptive`, `--adaptive-window`, `--adaptive-t`), Python, and the Node package (`binaryThreshold`, `adaptive`, `adaptiveWindow`, `adaptiveT`).
## 1.0.0-alpha.1 - 2026-07-24