feat(scenegraph): add SceneGraphBuilder for pipeline-driven graph construction

Introduce SceneGraphBuilder + SceneGraphBuildConfig to decouple scene graph
construction from the verification notebook. The builder handles batch
inference, hash encoding, and object node creation internally.

- Add SceneGraphBuilder.build_from_room_views() as the main entry point
- Add SceneGraphBuildConfig for inference_batch_size and position strategy
- Add SceneGraphBuildArtifacts to carry cropped images and debug metadata
- Extend ObjectNode with optional detection metadata (label, confidence,
  bbox_xyxy, source_view_id, position_confidence)
- Add RoomView frozen dataclass as a structured view container
- Add flatten_room_views() utility to replace inline list comprehensions
- Refactor notebooks/verification.py to use the new builder API

BREAKING CHANGE: ObjectNode now accepts additional optional fields; direct
scene_graph.objects[obj_id] = ObjectNode(...) construction in the notebook
is replaced by builder.build_from_room_views(...).

mini-nav/simulator/__init__.py

@@ -5,10 +5,17 @@ from .habitat import (
 )
 from .image_save import save_object_image, save_room_view
 from .topdown import TopDownRenderStyle, TopDownSceneElements, render_topdown_scene_map
-from .views import RoomViewsByRoom, collect_room_views_by_room, collect_scene_images
+from .views import (
+    RoomView,
+    RoomViewsByRoom,
+    collect_room_views_by_room,
+    collect_scene_images,
+    flatten_room_views,
+)
 
 __all__ = [
     "HabitatSimulatorConfig",
+    "RoomView",
     "RoomViewsByRoom",
     "TopDownRenderStyle",
     "TopDownSceneElements",
@@ -16,6 +23,7 @@ __all__ = [
     "collect_room_views_by_room",
     "collect_scene_images",
     "create_habitat_simulator",
+    "flatten_room_views",
     "render_topdown_scene_map",
     "save_object_image",
     "save_room_view",

mini-nav/simulator/views.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from dataclasses import dataclass, field
 from importlib import import_module
 from pathlib import Path
 from typing import Any, Callable, Iterable, Sequence
@@ -11,6 +12,24 @@ RoomViewsByRoom = dict[str, list[Any]]
 ProgressTrack = Callable[[Iterable[Any], str], Iterable[Any]]
 
 
+@dataclass(frozen=True)
+class RoomView:
+    room_id: str
+    view_idx: int
+    rgb: Any = field(compare=False)
+    depth: Any | None = field(default=None, compare=False)
+    agent_position: np.ndarray | None = field(default=None, compare=False)
+    agent_rotation: Any | None = field(default=None, compare=False)
+
+
+def flatten_room_views(room_views_by_room: RoomViewsByRoom) -> list[RoomView]:
+    result: list[RoomView] = []
+    for room_id, views in room_views_by_room.items():
+        for idx, rgb in enumerate(views):
+            result.append(RoomView(room_id=room_id, view_idx=idx, rgb=rgb))
+    return result
+
+
 def collect_room_views_by_room(
     agent: Any,
     sim: Any,