Добавить имитаторы МЛЭ и ГБО с 3D-сценой, съёмкой рельефа и пресетами.

Вкладки позволяют готовить рельеф, двигать АНПА, накапливать поверхность по лучам и сохранять скриншоты окон; ГБО использует бортовые секторы 12–75° и чёрные зоны вне обзора.

Co-authored-by: Cursor <cursoragent@cursor.com>

backend/scene_generator.py

@@ -649,13 +649,87 @@ def export_ply(points: list[list[float]]) -> str:
     return header + body + ("\n" if points else "")
 
 
-def export_obj(points: list[list[float]], object_name: str = "cloud") -> str:
+def export_obj(
+    points: list[list[float]],
+    object_name: str = "cloud",
+    classes: list[int | float] | None = None,
+) -> str:
     safe_name = "".join(ch if ch.isalnum() or ch in "_-" else "_" for ch in (object_name or "cloud")) or "cloud"
-    lines = [f"# DotsToSurface point cloud ({len(points)} vertices)", f"o {safe_name}"]
-    for p in points:
-        lines.append(f"v {p[0]:.8f} {p[1]:.8f} {p[2]:.8f}")
+    if classes is None:
+        lines = [f"# DotsToSurface point cloud ({len(points)} vertices)", f"o {safe_name}"]
+        for p in points:
+            lines.append(f"v {p[0]:.8f} {p[1]:.8f} {p[2]:.8f}")
+        return "\n".join(lines) + "\n"
+
+    if len(classes) != len(points):
+        raise ValueError("classes length must match points length")
+
+    class_names = {0: "background", 1: "object"}
+    grouped: dict[int, list[list[float]]] = {}
+    for point, cls in zip(points, classes):
+        grouped.setdefault(int(cls), []).append(point)
+
+    lines = [
+        f"# DotsToSurface labeled point cloud ({len(points)} vertices)",
+        "# Classes: background=0, object=1",
+        f"o {safe_name}",
+    ]
+    for cls_id in sorted(grouped.keys()):
+        group_name = class_names.get(cls_id, f"class_{cls_id}")
+        lines.append(f"o {group_name}")
+        lines.append(f"# class {cls_id}")
+        for p in grouped[cls_id]:
+            lines.append(f"v {p[0]:.8f} {p[1]:.8f} {p[2]:.8f}")
     return "\n".join(lines) + "\n"
 
+
+def _class_from_obj_group(name: str) -> float | None:
+    key = (name or "").strip().lower()
+    if key == "background":
+        return 0.0
+    if key == "object":
+        return 1.0
+    if key.startswith("class_"):
+        try:
+            return float(key.split("_", 1)[1])
+        except (IndexError, ValueError):
+            return None
+    return None
+
+
+def parse_obj_labeled_points(text: str) -> list[list[float]]:
+    """Extract [x, y, z, class] from OBJ with class groups or ``# class N`` markers."""
+    labeled: list[list[float]] = []
+    current_class = 0.0
+    for raw in text.splitlines():
+        line = raw.strip()
+        if not line:
+            continue
+        lower = line.lower()
+        if lower.startswith("# class "):
+            try:
+                current_class = float(line.split()[-1])
+            except ValueError:
+                pass
+            continue
+        if lower.startswith("o "):
+            cls = _class_from_obj_group(line[2:])
+            if cls is not None:
+                current_class = cls
+            continue
+        if lower.startswith("v "):
+            parts = line.split()
+            if len(parts) < 4:
+                continue
+            try:
+                labeled.append(
+                    [float(parts[1]), float(parts[2]), float(parts[3]), current_class]
+                )
+            except ValueError:
+                continue
+    return labeled
+
+
 def parse_obj_points(text: str) -> list[list[float]]:
     """Extract vertex positions from Wavefront OBJ (ignores faces/materials)."""
     points: list[list[float]] = []