Merge: touch selection and drag, from the gallery-selection branch

Verified before merge: fmt clean, clippy -D warnings clean, 563 dr-ui tests.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

# Conflicts:
#	docs/traceability.md

tools/export-seg-model.sh

@@ -1,14 +1,25 @@
 #!/usr/bin/env bash
-# Re-export the segmentation model that ships in core/dr-segment/models/.
+# Re-export the segmentation models that ship in models/ at the repository root.
 #
 # The .onnx is committed (D14), so this is not part of any build — it exists so
 # the committed artefact is reproducible rather than a binary someone once
-# produced and nobody can regenerate. Run it when bumping the model.
+# produced and nobody can regenerate. Run it when bumping a model.
 #
-#   ./tools/export-seg-model.sh
+#   ./tools/export-seg-model.sh                        # instance -> models/segment/
+#   ./tools/export-seg-model.sh yolo26s-sem-ade20k     # semantic -> models/scene/
 #
 # Requires `uv`. Everything else is fetched into a throwaway venv.
 #
+# ## The two models, and why they are both here
+#
+# `yolo26n-seg` is COCO instance segmentation: it separates *things*, so
+# clicking one of three people selects that person. `yolo26s-sem-ade20k` is
+# ADE20K semantic segmentation: it labels every pixel with one of 150 classes
+# including the *stuff* — sky, vegetation, water — that COCO has no word for,
+# but it merges same-class pixels into one region and so cannot tell those
+# three people apart. Neither substitutes for the other; the scene tab wants
+# the second and local adjustments want the first.
+#
 # ## Why these export flags
 #
 # `dynamic=False` is not a default we failed to change: **tract cannot parse
@@ -20,15 +31,44 @@
 # `imgsz` square rather than a rectangle matched to 3:2: one graph has to
 # serve portrait, landscape, square crops and panoramas. A landscape-shaped
 # graph trades letterbox waste on 3:2 for worse waste on everything else.
+#
+# ## Why the semantic export is truncated
+#
+# Ultralytics ends the `-sem-` graph with `Resize -> ArgMax -> Cast`, handing
+# back a `[1, 640, 640]` u8 label map. Two reasons that tail is cut here:
+#
+#  1. **Cost.** The Resize materialises 150 x 640 x 640 x f32 — *246 MB* — and
+#     ArgMax then reduces across the channel axis, which in NCHW strides
+#     409,600 elements per comparison. Measured on one machine it was roughly
+#     four fifths of total runtime, for work the app throws away.
+#  2. **Softness.** ArgMax destroys the per-class scores. The scene tab needs
+#     them: softmax over the 150 channels, summed within each photographic
+#     category, gives per-category weights that sum to 1 at every pixel — a
+#     partition of unity. Feathering those cannot double-grade a boundary,
+#     where feathering hard labels outward from two adjacent categories does.
+#
+# The upsample is not information: the graph's true spatial resolution is the
+# logit grid (80x80 at imgsz=640), and the app can resample from that itself.
 set -euo pipefail
 
 HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
 REPO="$(cd "${HERE}/.." && pwd)"
-OUT="${REPO}/core/dr-segment/models"
 
 MODEL="${1:-yolo26n-seg}"
 IMGSZ="${2:-640}"
-WORK="$(mktemp -d)"
+
+# Semantic models are the scene tab's; instance models are the selection path's.
+case "${MODEL}" in
+    *-sem-*|*-sem) OUT="${REPO}/models/scene"; SEMANTIC=1 ;;
+    *)             OUT="${REPO}/models/segment"; SEMANTIC=0 ;;
+esac
+
+# Not `mktemp -d`: the default TMPDIR is `/tmp`, which on most current Linux
+# distributions is a tmpfs — RAM, sized at half of physical memory. The venv
+# below pulls torch, several gigabytes of it, and installing that into RAM
+# either evicts the user's page cache or fails outright with ENOSPC on a
+# machine that has hundreds of gigabytes of actual disk free.
+WORK="$(mktemp -d -p "${TMPDIR:-/var/tmp}")"
 trap 'rm -rf "${WORK}"' EXIT
 
 echo "==> exporting ${MODEL} at imgsz=${IMGSZ} in ${WORK}"
@@ -36,12 +76,13 @@ cd "${WORK}"
 uv venv --python 3.12 venv
 VIRTUAL_ENV="${WORK}/venv" uv pip install ultralytics onnx onnxslim
 
-VIRTUAL_ENV="${WORK}/venv" "${WORK}/venv/bin/python" - "${MODEL}" "${IMGSZ}" <<'PY'
+VIRTUAL_ENV="${WORK}/venv" "${WORK}/venv/bin/python" - "${MODEL}" "${IMGSZ}" "${SEMANTIC}" <<'PY'
 import sys, json
+import onnx
+from onnx import helper
 from ultralytics import YOLO
 
-name = sys.argv[1]
-imgsz = int(sys.argv[2])
+name, imgsz, semantic = sys.argv[1], int(sys.argv[2]), sys.argv[3] == "1"
 m = YOLO(f"{name}.pt")
 path = m.export(format="onnx", opset=17, simplify=True, imgsz=imgsz, dynamic=False)
 print("ONNX:", path)
@@ -52,6 +93,25 @@ print("ONNX:", path)
 with open("classes.json", "w") as f:
     json.dump([m.names[i] for i in range(len(m.names))], f, indent=1)
 print("classes:", len(m.names))
+
+if semantic:
+    # Drop `Resize -> ArgMax -> Cast` and expose the classifier's logits. See
+    # the header for why. Matched by op type rather than by node name so a
+    # re-export under a different naming scheme still works, and asserted
+    # rather than assumed so an upstream graph change fails loudly here
+    # instead of silently shipping a differently-shaped model.
+    g = onnx.load(path).graph
+    tail = [n.op_type for n in g.node[-3:]]
+    assert tail == ["Resize", "ArgMax", "Cast"], f"unexpected graph tail: {tail}"
+    logits = g.node[-3].input[0]
+    del g.node[-3:]
+    del g.output[:]
+    g.output.extend([helper.make_tensor_value_info(logits, onnx.TensorProto.FLOAT, None)])
+    model = onnx.shape_inference.infer_shapes(helper.make_model(g, opset_imports=[helper.make_opsetid("", 17)]))
+    onnx.checker.check_model(model)
+    onnx.save(model, path)
+    shape = [d.dim_value for d in model.graph.output[0].type.tensor_type.shape.dim]
+    print("truncated to logits:", logits, shape)
 PY
 
 mkdir -p "${OUT}"
@@ -61,4 +121,4 @@ cp "${WORK}/classes.json" "${OUT}/${MODEL}.classes.json"
 echo "==> wrote:"
 ls -la "${OUT}"
 echo
-echo "Remember: these weights are AGPL-3.0 (see ${OUT}/LICENCE.md)."
+echo "Remember: these weights are AGPL-3.0 (see ${REPO}/models/LICENCE.md)."