4f31123b0c19a534e9d656fb10158a80869ccdf2
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Commits
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8df6000e4b |
Decode the scene model into per-category weights
The weights landed last commit with nothing to read them. This is the decoder, and the shape of it follows from one property worth stating before the code: the categories must partition the image. ## Why a partition, and not a mask per category The scene tab applies one grade to every pixel of a category — lift the sky, desaturate foliage — and both grades meet at the horizon. If each category carried an independent mask, feathering them outward would make the boundary band belong to both, so both grades would land there and every horizon would acquire a visible seam. Feathering has to *blend* there, not accumulate. So `marginalise` takes one softmax over all 150 channels and sums within each category. Grouping cannot change a total of one, so the listed categories plus the unlisted remainder sum to one at every pixel, by construction rather than by normalising afterwards. `parse_categories` refuses a descriptor that claims a class twice, because that is the one input that would quietly make the property untrue. ## The descriptor is data, and hand-written `models/scene/categories.txt` groups ADE20K's 150 classes into the eight a photographer would recognise. It is a file rather than a table in Rust for the reason `models/LICENCE.md` predicted — a vocabulary is model metadata — and it is line-oriented with comments rather than JSON like the `.classes.json` beside it, because that file is generated and this one is argued. Why `swimming pool` is water and not architecture belongs next to the line that says so. Classes are named, not indexed. An index is silently wrong after a re-export; a name is loudly wrong, and the loader refuses one the model does not have. ## Resolution, kept visible `Scene` holds the native 80×80 logit grid and resamples on demand rather than upsampling once at load. The coarseness is real — it is what the graph produces — and a type that hides it behind an early resize invites callers to expect detail that was never there. `rasterise` is where the letterbox inverse lives, once. `Letterbox` and `Window` become `pub(crate)` and `to_proto` generalises to `to_grid`, because both dense outputs this crate reads are an even fraction of the same letterboxed square and differ only in the divisor. ## Verified by looking, which is the only way this gets verified `examples/scene.rs` writes the photograph dimmed outside each category. A transposed axis or an off-by-one in the inverse produces perfectly plausible weights over slightly the wrong pixels, and no unit test catches that. On an indoor frame the person mask lands on the person, including the outstretched arm, and sky reads ~5% against a bright ceiling. It doubles as the benchmark, because every timing quoted while this model was chosen came off a laptop compiling other things and none of them belong in a document. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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0da8271836 |
Let the model say what a thing is and the watershed say where it ends
Local masking needs to know where an image's regions are. The watershed spike (S15 arm A) found the boundaries but had no idea what any of them enclosed; its coarse levels were geometric accidents. This adds the other half and the thing that joins them. `core/dr-segment` is where region reasoning now lives — the hierarchy moves out of `dr-gpu`, which keeps only the pixel passes that are genuinely shaders. The new crate is device-free and, without its default features, model-free too: 20 of its tests need neither an adapter nor 11 MB of weights. Arm B runs YOLO26n-seg through `ort`. D13 framed inference as a choice between `ort`'s C++ runtime and the pure-Rust dependency policy; that was a false choice. `ort`'s `alternative-backend` feature unlinks the C entirely and `ort-tract` supplies the API from tract, which is pure Rust. Measured before committing to it: zero unsupported operators, 420 ms for 640x640, and correct masks on bus.jpg. No NDK problem to solve, so D13's largest tolerated exception is not needed. Arm C is `prior.rs`, and it ships because the two arms fail in opposite directions. Instance membership re-weights the merge saddles, so region pairs the model believes share an object merge early and pairs straddling its edge merge late. No boundary moves — only the order in which they dissolve — which is how the result stays pixel-accurate at every level while its coarse levels become named things. Two things the spec assumed that turned out to be false, both recorded in models/LICENCE.md: there is no usable ADE20K-trained YOLO, so the shipped vocabulary is COCO's 80 subjects and *stuff* like sky and foliage must come from arm A; and tract cannot parse a dynamic-shape export, so the graph's input is fixed and tiling is the only route to more semantic resolution. Weights are AGPL-3.0, which GPLv3 §13 permits and which makes the combined work effectively AGPL. Deliberate, not accidental. They live in Git LFS, and a build script fails with an instruction rather than embedding a pointer file when the clone lacks them. |