Сохраняемся

backend/main.py

@@ -22,7 +22,10 @@ from dataset_generator import (
     iter_generate_dataset,
     list_dataset_runs,
     load_dataset_run,
+    list_object_presets,
     load_object_points_from_obj_text,
+    load_preset_object_points,
+    OBJECT_PRESETS,
     load_scene_preview,
     resolve_output_dir,
 )
@@ -137,11 +140,18 @@ class DatasetLoadBody(BaseModel):
 
 class MlePrepareBody(BaseModel):
     seed: int = 42
-    sizeX: float = 40.0
-    sizeY: float = 60.0
+    sizeX: float | None = None
+    sizeY: float | None = None
     resX: int = 80
     resY: int = 120
     outputDir: str = "mle_runs"
+    reliefScalePct: float = 20.0
+    auvX: float | None = None
+    auvY: float | None = None
+    auvHeadingDeg: float | None = None
+    surveyLength: float | None = None
+    auvDepth: float | None = None
+    swathAngleDeg: float | None = None
     settings: dict[str, Any] | None = None
 
 
@@ -475,6 +485,11 @@ def generator_resolve_intersections(body: GeneratorResolveBody) -> dict[str, Any
         raise HTTPException(status_code=400, detail=str(exc)) from exc
 
 
+@app.get("/api/dataset/object-presets")
+def dataset_object_presets() -> list[dict[str, Any]]:
+    return list_object_presets()
+
+
 @app.post("/api/dataset/generate")
 async def dataset_generate(
     count: int = Form(5),
@@ -484,15 +499,36 @@ async def dataset_generate(
     objectScaleIsMax: bool = Form(False),
     beamCount: int = Form(45),
     lengthCount: int | None = Form(None),
-    model: UploadFile = File(...),
+    absentPct: float = Form(30.0),
+    nearlyHiddenPct: float = Form(20.0),
+    partialPct: float = Form(40.0),
+    visiblePct: float = Form(40.0),
+    modelPreset: str | None = Form(None),
+    model: UploadFile | None = File(None),
 ) -> StreamingResponse:
-    filename = (model.filename or "").strip()
-    if not filename.lower().endswith(".obj"):
-        raise HTTPException(status_code=400, detail="Upload a .obj 3D model file.")
+    preset = (modelPreset or "").strip().lower()
+    filename = ((model.filename if model else None) or "").strip()
+    object_kind: str | None = None
+    object_points: list[list[float]] | None = None
     try:
-        raw = await model.read()
-        text = raw.decode("utf-8", errors="ignore")
-        object_points = load_object_points_from_obj_text(text)
+        if preset:
+            if preset not in OBJECT_PRESETS:
+                known = ", ".join(sorted(OBJECT_PRESETS)) or "(none)"
+                raise ValueError(f"Unknown object preset '{preset}'. Known: {known}")
+            object_kind = preset
+            filename = str(OBJECT_PRESETS[preset]["filename"])
+            if preset != "pipe":
+                object_points, filename = load_preset_object_points(preset)
+        elif model is not None and filename:
+            if not filename.lower().endswith(".obj"):
+                raise ValueError("Upload a .obj 3D model file.")
+            raw = await model.read()
+            text = raw.decode("utf-8", errors="ignore")
+            object_points = load_object_points_from_obj_text(text)
+        else:
+            raise ValueError(
+                "Выберите предустановку объекта или загрузите файл модели .obj."
+            )
     except ValueError as exc:
         raise HTTPException(status_code=400, detail=str(exc)) from exc
 
@@ -504,10 +540,15 @@ async def dataset_generate(
                 output_dir=outputDir or "sonar_dataset",
                 object_points=object_points,
                 object_name=filename,
+                object_kind=object_kind,
                 object_scale=objectScale,
                 object_scale_is_max=objectScaleIsMax,
                 beam_count=beamCount,
                 length_count=lengthCount,
+                absent_pct=absentPct,
+                nearly_hidden_pct=nearlyHiddenPct,
+                partial_pct=partialPct,
+                visible_pct=visiblePct,
             ):
                 yield json.dumps(event, ensure_ascii=False) + "\n"
         except ValueError as exc:
@@ -802,6 +843,14 @@ def mle_spa() -> FileResponse:
 @app.post("/api/mle/prepare")
 def mle_prepare(body: MlePrepareBody) -> dict[str, Any]:
     try:
+        corridor = {
+            "auvX": body.auvX,
+            "auvY": body.auvY,
+            "headingDeg": body.auvHeadingDeg,
+            "surveyLength": body.surveyLength,
+            "auvDepth": body.auvDepth,
+            "swathAngleDeg": body.swathAngleDeg,
+        }
         result = prepare_mle_scene(
             seed=body.seed,
             size_x=body.sizeX,
@@ -810,6 +859,8 @@ def mle_prepare(body: MlePrepareBody) -> dict[str, Any]:
             res_y=body.resY,
             output_dir=body.outputDir or "mle_runs",
             settings=body.settings,
+            relief_scale_pct=body.reliefScalePct,
+            corridor=corridor,
         )
         if body.settings:
             try: