Motore v2: run_graph con recipe_dir/calibrazione/overlay, /validate, test (#46)

Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>

src/vision/runner.py

@@ -9,6 +9,7 @@ from __future__ import annotations
 import math
 import os
 import subprocess
+import tempfile
 import time
 from dataclasses import dataclass, field
 from functools import lru_cache
@@ -18,6 +19,9 @@ from typing import Any
 import numpy as np
 from visionsuite.core.image import Image
 from visionsuite.task import Task
+from visionsuite.task.graph import RecipeError  # #46: errori di ricetta v2
+from visionsuite.task.registry import load_tools
+from visionsuite.task.session import Session
 
 _SUBMODULE = Path(__file__).resolve().parents[2] / "vendor" / "visionsuite"
 
@@ -49,6 +53,10 @@ class RunOutcome:
     # Kept apart from `failures`: the tool did not raise, it just produced a
     # number the caller must not measure a part by. Value is the reason.
     invalid_outputs: dict[str, str] = field(default_factory=dict)
+    # #46: contorni di tutti gli strumenti (px immagine, con tool_id) e esito
+    # del TaskReport (informativo: il verdetto quote lo dà il backend).
+    overlay: list[dict] = field(default_factory=list)
+    outcome: str | None = None
 
 
 @lru_cache(maxsize=1)
@@ -97,12 +105,46 @@ def engine_version() -> str:
     return _engine_version_from_git()
 
 
+def _scale_calibration(calibration: dict | None):
+    """Dict {"mm_per_px"|"px_per_mm"} -> ScaleCalibration (gli strumenti di
+    quota convertono con `in_millimetres`, che non accetta un dict)."""
+    if calibration is None:
+        return None
+    from visionsuite.calibration import ScaleCalibration
+
+    if not isinstance(calibration, dict) or not (
+        calibration.get("mm_per_px") or calibration.get("px_per_mm")
+    ):
+        raise GraphBuildError(
+            "calibration must be {'mm_per_px': float} or {'px_per_mm': float}"
+        )
+    key = "mm_per_px" if calibration.get("mm_per_px") else "px_per_mm"
+    return ScaleCalibration(**{key: float(calibration[key])})
+
+
+def _open_session(graph: dict, recipe_dir: Any, calibration: dict | None,
+                  workdir: str) -> Session:
+    """Costruisce la Session v2; RecipeError e grafo malformato -> GraphBuildError."""
+    cal = _scale_calibration(calibration)
+    try:
+        return Session.from_dict(
+            graph, Path(recipe_dir) if recipe_dir else Path(workdir), cal,
+        )
+    except RecipeError as exc:
+        raise GraphBuildError(f"malformed graph: {exc}") from exc
+    except (KeyError, TypeError, AttributeError, ValueError) as exc:
+        raise GraphBuildError(
+            f"malformed graph: {type(exc).__name__}: {exc}"
+        ) from exc
+
+
 def run_graph(
     image: Any,
     graph: dict,
     calibration: dict | None = None,
+    recipe_dir: Any = None,
 ) -> RunOutcome:
-    """Run a serialised vs-task graph against one image.
+    """Run a serialised vs-task v2 graph against one image.
 
     A tool that fails does not stop the others - on a crooked piece an edge may
     simply not be there, and the other quotes are still wanted. Failures come
@@ -112,33 +154,35 @@ def run_graph(
     wrapped into the `visionsuite.core.image.Image` that vs-measure's tools
     actually read via `.pixels`; an `Image` passed in is used as-is.
 
-    Two phases, on purpose: building the task from `graph` can fail on
-    nothing but the caller's input (a bad schema version, a tool with no
-    "kind", a graph that is not a dict at all) - that is `GraphBuildError`,
-    a 422 for the worker. Once the task exists, `task.run()` is the engine's
-    own business; an exception from there is not the caller's mistake, and
-    the worker must not call it one.
+    `recipe_dir` is the folder of the recipe's files (meta.dxf, meta.models,
+    ...); without it an empty temporary folder is used, so a recipe that needs
+    a file fails as a malformed graph instead of reading from the CWD.
+
+    Two phases, on purpose: building the session can fail on nothing but the
+    caller's input (a bad schema version, a tool with no "kind", a missing
+    file) - that is `GraphBuildError`, a 422 for the worker. Once it exists,
+    running is the engine's own business; an exception from there is not the
+    caller's mistake, and the worker must not call it one.
     """
-    try:
-        task = Task.from_dict(graph)
-    except (KeyError, TypeError, AttributeError, ValueError) as exc:
-        raise GraphBuildError(
-            f"malformed graph: {type(exc).__name__}: {exc}"
-        ) from exc
-
-    wrapped_image = image if isinstance(image, Image) else Image(pixels=np.asarray(image))
-    context: dict[str, Any] = {"image": wrapped_image}
-    if calibration is not None:
-        context["calibration"] = calibration
-
-    started = time.monotonic()
-    report = task.run(context=context)
-    elapsed_ms = int((time.monotonic() - started) * 1000)
+    load_tools()  # #46: registra gli strumenti degli entry point di vs-tools
+    with tempfile.TemporaryDirectory() as empty_dir:
+        session = _open_session(graph, recipe_dir, calibration, empty_dir)
+        wrapped_image = (
+            image if isinstance(image, Image) else Image(pixels=np.asarray(image))
+        )
+        started = time.monotonic()
+        report = session.run(wrapped_image)
+        elapsed_ms = int((time.monotonic() - started) * 1000)
 
     outputs: dict[str, float] = {}
     failures: list[ToolFailure] = []
     invalid_outputs: dict[str, str] = {}
+    overlay: list[dict] = []
     for result in report:
+        # #46: overlay di ogni strumento, con il tool_id di chi lo ha prodotto
+        for item in result.overlay or []:
+            if isinstance(item, dict):
+                overlay.append({**item, "tool_id": result.tool_id})
         if not result.ok:
             failures.append(ToolFailure(
                 tool_id=result.tool_id,
@@ -164,4 +208,55 @@ def run_graph(
         engine_version=engine_version(),
         duration_ms=elapsed_ms,
         invalid_outputs=invalid_outputs,
+        overlay=overlay,
+        outcome=report.outcome,
     )
+
+
+def _is_number(value: Any) -> bool:
+    return isinstance(value, (int, float)) and not isinstance(value, bool)
+
+
+def validate_graph(
+    graph: dict, recipe_dir: Any = None
+) -> tuple[bool, list[str], list[dict]]:
+    """Validate a v2 recipe without an image: (ok, errors, numeric outputs).
+
+    Not a draft: a missing meta file is an error. `outputs` lists the numeric
+    outputs the tools declare (OUT properties with a numeric default, plus the
+    `values` of dimension tools), with quantity/unit when declared.
+    """
+    load_tools()
+    if not isinstance(graph, dict):
+        return False, ["graph must be a JSON object"], []
+    try:
+        task = Task.from_dict(
+            graph, recipe_dir=Path(recipe_dir) if recipe_dir else None
+        )
+    except RecipeError as exc:
+        return False, list(exc.errors), []
+    except (KeyError, TypeError, AttributeError, ValueError) as exc:
+        return False, [f"{type(exc).__name__}: {exc}"], []
+
+    outputs: list[dict] = []
+    for tool in task.tools:
+        value_quantities = getattr(tool, "value_quantities", None) or {}
+        values = tuple(getattr(tool, "values", ()) or ())
+        for prop in tool.outputs():
+            if not (_is_number(prop.default) or prop.name in values):
+                continue
+            quantity = value_quantities.get(prop.name, getattr(tool, "quantity", None))
+            if not isinstance(quantity, str):
+                quantity = None
+            unit = None
+            if quantity == "length":
+                nominal_unit = getattr(tool, "nominal_unit", None)
+                unit = nominal_unit if isinstance(nominal_unit, str) else None
+            elif quantity == "angle":
+                unit = "deg"
+            outputs.append({
+                "key": f"{tool.id}.{prop.name}",
+                "quantity": quantity,
+                "unit": unit,
+            })
+    return True, [], outputs

src/vision/tests/test_runner.py

@@ -34,14 +34,16 @@ def a_disc(radius: int = 60, size: int = 400) -> np.ndarray:
 def a_circle_graph() -> dict:
     """A two-tool graph, built with vs-task's own API."""
     from visionsuite.task import Task
-    from visionsuite.task.tools import DetectCircleTool, DiameterTool
+    from visionsuite.tools.detect import DetectCircle
+    from visionsuite.tools.dimensions import Diameter
 
     task = Task(name="prova")
-    found = task.add(DetectCircleTool(name="disco"))
+    found = task.add(DetectCircle(name="disco"))
     found.center_row, found.center_col, found.radius = 200.0, 200.0, 60.0
     found.scan_size = 30.0
 
-    quota = task.add(DiameterTool(name="diametro"))
+    quota = task.add(Diameter(name="diametro"))
+    quota.nominal_unit = "px"  # #46: v2, senza calibrazione la quota resta in px
     quota.link("circle", found, "circle")
     return task.to_dict()
 
@@ -63,7 +65,7 @@ def test_a_broken_tool_does_not_sink_the_others():
     graph = a_circle_graph()
     graph["tools"].append(
         {"id": "ghost", "kind": "DetectCircle", "name": "assente",
-         "properties": {"center_row": 5.0, "center_col": 5.0, "radius": 900.0}}
+         "values": {"center_row": 5.0, "center_col": 5.0, "radius": 900.0}}
     )
 
     outcome = run_graph(a_disc(), graph)
@@ -81,14 +83,21 @@ class _FakeResult:
         self.ok = ok
         self.outputs = outputs or {}
         self.error = error
+        self.overlay = []  # #46: v2, ogni risultato porta l'overlay
+
+
+class _FakeReport(list):
+    """#46: run_graph ora legge `.outcome` dal report di Session.run."""
+
+    outcome = "pass"
 
 
 def test_a_nan_output_is_dropped_not_measured(monkeypatch):
     """vs-measure emits NaN on an empty slice (caliper.py:112 per the
     revisione) - a NaN must not become a quote's value (#16)."""
-    def fake_run(self, context=None):
-        return [_FakeResult("t1", "diametro", True, outputs={"diameter": float("nan")})]
-    monkeypatch.setattr(runner.Task, "run", fake_run)
+    def fake_run(self, image, tag=None):
+        return _FakeReport([_FakeResult("t1", "diametro", True, outputs={"diameter": float("nan")})])
+    monkeypatch.setattr(runner.Session, "run", fake_run)
 
     outcome = run_graph(a_disc(), a_circle_graph())
 
@@ -97,9 +106,9 @@ def test_a_nan_output_is_dropped_not_measured(monkeypatch):
 
 
 def test_an_infinite_output_is_dropped_not_measured(monkeypatch):
-    def fake_run(self, context=None):
-        return [_FakeResult("t1", "diametro", True, outputs={"diameter": float("inf")})]
-    monkeypatch.setattr(runner.Task, "run", fake_run)
+    def fake_run(self, image, tag=None):
+        return _FakeReport([_FakeResult("t1", "diametro", True, outputs={"diameter": float("inf")})])
+    monkeypatch.setattr(runner.Session, "run", fake_run)
 
     outcome = run_graph(a_disc(), a_circle_graph())
 
@@ -109,9 +118,9 @@ def test_an_infinite_output_is_dropped_not_measured(monkeypatch):
 
 def test_a_bool_output_is_not_treated_as_a_measurable_number(monkeypatch):
     """bool is a subclass of int - a flag output must not become a quote."""
-    def fake_run(self, context=None):
-        return [_FakeResult("t1", "flag", True, outputs={"present": True})]
-    monkeypatch.setattr(runner.Task, "run", fake_run)
+    def fake_run(self, image, tag=None):
+        return _FakeReport([_FakeResult("t1", "flag", True, outputs={"present": True})])
+    monkeypatch.setattr(runner.Session, "run", fake_run)
 
     outcome = run_graph(a_disc(), a_circle_graph())
 
@@ -155,3 +164,127 @@ def test_engine_version_raises_rather_than_inventing_one(monkeypatch):
             engine_version()
     finally:
         runner._engine_version_from_git.cache_clear()
+
+
+# ---------------------------------------------------------------------------
+# #46: ricette v2 complete - overlay, calibrazione, recipe_dir con DXF.
+# ---------------------------------------------------------------------------
+
+import hashlib
+import shutil
+from pathlib import Path
+
+import cv2
+
+_VS = Path(__file__).resolve().parents[3] / "vendor" / "visionsuite"
+_SAMPLE_DXF = _VS / "packages" / "vs-dxf" / "tests" / "fixtures" / "sample.dxf"
+# Il disegno di prova: rettangolo 200x100 mm con foro r=10 mm.
+_PX_PER_MM = 4.0
+
+
+def _dxf_scene() -> np.ndarray:
+    """Il pezzo del disegno rasterizzato a 4 px/mm, margine 60 mm."""
+    margin = 60.0
+    w = int((200.0 + 2 * margin) * _PX_PER_MM)
+    h = int((100.0 + 2 * margin) * _PX_PER_MM)
+    img = np.full((h, w), 255, dtype=np.uint8)
+    cx, cy = w // 2, h // 2
+    hw, hh = 200.0 * _PX_PER_MM / 2, 100.0 * _PX_PER_MM / 2
+    cv2.rectangle(img, (int(cx - hw), int(cy - hh)), (int(cx + hw), int(cy + hh)), 0, -1)
+    cv2.circle(img, (cx, cy), int(10.0 * _PX_PER_MM), 255, -1)
+    return img
+
+
+def _dxf_recipe() -> dict:
+    """CompareDxf con ancora a due punti, collegati a due DetectPointScan.
+
+    Le due scansioni trovano i bordi sinistro e destro del pezzo una riga
+    sopra il lato in basso: origine del disegno = angolo in basso a sinistra,
+    direzione a -> b = asse x del disegno.
+    """
+    h, w = _dxf_scene().shape
+    cx, cy = w // 2, h // 2
+    hw, hh = 200.0 * _PX_PER_MM / 2, 100.0 * _PX_PER_MM / 2
+    row = cy + hh - 1.0
+
+    def scan(tid: str, col: float) -> dict:
+        return {"id": tid, "name": tid, "kind": "DetectPointScan",
+                "values": {"start_row": row, "start_col": col - 30.0,
+                           "end_row": row, "end_col": col + 30.0,
+                           "width": 5.0, "select": "first"},
+                "links": {}}
+
+    return {
+        "schema_version": 2,
+        "name": "dxf",
+        "meta": {"dxf": {"disegno": {  # sha256 obbligatorio in meta (v2)
+            "path": "disegno.dxf",
+            "sha256": hashlib.sha256(_SAMPLE_DXF.read_bytes()).hexdigest()}}},
+        "tools": [
+            scan("t-a", cx - hw),
+            scan("t-b", cx + hw),
+            {"id": "t-dxf", "name": "confronto", "kind": "CompareDxf",
+             "values": {"dxf": "disegno", "mm_per_px": 1.0 / _PX_PER_MM,
+                        "anchor": "two_points",
+                        "band_plus": 8.0, "band_minus": 8.0},
+             "links": {"point_a": {"tool": "t-a", "property": "point"},
+                       "point_b": {"tool": "t-b", "property": "point"}}},
+        ],
+    }
+
+
+def test_a_circle_recipe_returns_overlay_and_outcome():
+    outcome = run_graph(a_disc(), a_circle_graph())
+
+    assert outcome.outcome in ("pass", "warning", "fail")
+    assert outcome.overlay, "DetectCircle must draw something"
+    assert all("tool_id" in item for item in outcome.overlay)
+
+
+def test_calibration_dict_gives_mm_quotes():
+    graph = a_circle_graph()
+    for tool in graph["tools"]:
+        if tool["kind"] == "Diameter":
+            tool["values"]["nominal_unit"] = "mm"
+
+    outcome = run_graph(a_disc(), graph, calibration={"mm_per_px": 0.5})
+
+    assert outcome.failures == []
+    diameter = next(v for k, v in outcome.outputs.items() if k.endswith(".value"))
+    assert diameter == pytest.approx(60.0, abs=2.0)  # 120 px * 0.5 mm/px
+
+
+def test_compare_dxf_two_points_with_recipe_dir(tmp_path):
+    shutil.copy(_SAMPLE_DXF, tmp_path / "disegno.dxf")
+
+    outcome = run_graph(_dxf_scene(), _dxf_recipe(), recipe_dir=tmp_path)
+
+    assert outcome.failures == []
+    assert outcome.outputs["t-dxf.n_points"] > 1000
+    assert outcome.outputs["t-dxf.points_in_pct"] > 95.0
+    roles = {item.get("role") for item in outcome.overlay}
+    assert {"reference", "found"} <= roles
+    assert "t-dxf" in {item["tool_id"] for item in outcome.overlay}
+
+
+def test_missing_meta_file_is_a_graph_build_error(tmp_path):
+    with pytest.raises(runner.GraphBuildError):
+        run_graph(_dxf_scene(), _dxf_recipe(), recipe_dir=tmp_path)
+
+
+def test_validate_lists_numeric_outputs(tmp_path):
+    shutil.copy(_SAMPLE_DXF, tmp_path / "disegno.dxf")
+    graph = _dxf_recipe()
+
+    ok, errors, outputs = runner.validate_graph(graph, tmp_path)
+
+    assert ok, errors
+    keys = {o["key"] for o in outputs}
+    assert {"t-dxf.points_in_pct", "t-dxf.n_points"} <= keys
+    assert all(set(o) == {"key", "quantity", "unit"} for o in outputs)
+
+
+def test_validate_reports_a_missing_file(tmp_path):
+    ok, errors, outputs = runner.validate_graph(_dxf_recipe(), tmp_path)
+
+    assert not ok and errors and outputs == []