feat: apply work-plane filter at all three cloud sites

points_via_sam21, _points_via_bbox, and _object_cloud_cv (bbox branch)
now call apply_below_plane_filter on the CV-frame cloud before the
<10-points guard. Responses carry plane_applied + n_points_before_plane.
Without a saved plane the filter is a no-op (plane_applied=false).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src/presa_mano/api/grasp_routes.py

@@ -25,6 +25,7 @@ from ..grasp.visual_servo import (
 )
 from ..perception import ObjectDetector, filter_outliers, nuwa_to_cv_frame
 from ..perception.sam21_bridge import Sam21Fallback, points_via_sam21
+from ..perception.work_plane import apply_below_plane_filter, get_work_plane
 from .perception_routes import _bbox_to_roi
 from ..timing import Stopwatch
 from . import _deps
@@ -71,27 +72,32 @@ def _object_points_in_base(conf: float | None, class_name: str | None, sw: Stopw
 
     if cfg.get("grasp", {}).get("use_sam21", True):
         try:
-            pts_cv = points_via_sam21(nuwa, _deps.sam21(), bbox, sw)
+            pts_cv, plane_info = points_via_sam21(nuwa, _deps.sam21(), bbox, sw)
             with sw.step("to_base_frame"):
                 pts_base = transform_points(T_base_cam, pts_cv)
             meta["source"] = "sam21"
             meta["n_points"] = int(len(pts_base))
+            meta["plane_applied"] = plane_info["plane_applied"]
+            meta["n_points_before_plane"] = plane_info["n_points_before_plane"]
             return pts_base, meta
         except Sam21Fallback as e:
             # Logging happens inside points_via_sam21 with the right level.
             meta["sam21_fallback_reason"] = str(e)
 
-    pts_base = _points_via_bbox(nuwa, T_base_cam, bbox, sw)
+    pts_base, plane_info = _points_via_bbox(nuwa, T_base_cam, bbox, sw)
     meta["source"] = "bbox_roi"
     meta["n_points"] = int(len(pts_base))
+    meta["plane_applied"] = plane_info["plane_applied"]
+    meta["n_points_before_plane"] = plane_info["n_points_before_plane"]
     return pts_base, meta
 
 
 def _points_via_bbox(nuwa, T_base_cam: np.ndarray, bbox: tuple[int, int, int, int],
-                     sw: Stopwatch) -> np.ndarray:
-    """Legacy path: bbox → Nuwa ROI cloud → filter outliers → base frame.
+                     sw: Stopwatch) -> tuple[np.ndarray, dict]:
+    """Legacy path: bbox → Nuwa ROI cloud → outlier filter → plane filter → base frame.
 
-    Raises HTTPException(422) on <10 valid depth points (existing behaviour).
+    Raises HTTPException(422) on <10 valid depth points (after both outlier
+    filter and below-plane filter). Returns (pts_base, plane_info).
     """
     cfg = get_config()
     u_min, v_min, u_max, v_max = bbox
@@ -106,12 +112,17 @@ def _points_via_bbox(nuwa, T_base_cam: np.ndarray, bbox: tuple[int, int, int, in
         raise HTTPException(status_code=502, detail=f"Nuwa ROI pointcloud failed: {e}")
     with sw.step("filter_outliers"):
         cropped = filter_outliers(pc)
-    if len(cropped) < 10:
-        raise HTTPException(status_code=422, detail=f"too few valid depth points in bbox: {len(cropped)}")
+    pts_cv = nuwa_to_cv_frame(cropped[:, :3]) if len(cropped) else np.empty((0, 3), dtype=np.float64)
+    pts_cv, plane_info = apply_below_plane_filter(pts_cv, get_work_plane())
+    if len(pts_cv) < 10:
+        raise HTTPException(
+            status_code=422,
+            detail=f"too few valid depth points after plane filter: {len(pts_cv)}"
+                   f" (before plane: {plane_info['n_points_before_plane']})"
+        )
     with sw.step("to_base_frame"):
-        pts_cv = nuwa_to_cv_frame(cropped[:, :3])
         pts_base = transform_points(T_base_cam, pts_cv)
-    return pts_base
+    return pts_base, plane_info
 
 
 @router.post("/plan")

src/presa_mano/api/perception_routes.py

@@ -12,6 +12,7 @@ from ..config import get_config
 from ..geometry import transform_points
 from ..perception import ObjectDetector, filter_outliers, nuwa_to_cv_frame
 from ..perception.sam21_bridge import Sam21Fallback, points_via_sam21
+from ..perception.work_plane import apply_below_plane_filter, get_work_plane
 from ..timing import Stopwatch
 from . import _deps
 
@@ -110,6 +111,9 @@ def scan(req: ScanReq) -> dict[str, Any]:
     out["source"] = source
     if extra.get("sam21_fallback_reason"):
         out["sam21_fallback_reason"] = extra["sam21_fallback_reason"]
+    if "plane_applied" in extra:
+        out["plane_applied"] = extra["plane_applied"]
+        out["n_points_before_plane"] = extra["n_points_before_plane"]
     out["n_points"] = int(len(pts_cv))
     out["points_camera"] = pts_cv.tolist() if len(pts_cv) else []
 
@@ -153,6 +157,9 @@ def object_points(req: DetectReq) -> dict[str, Any]:
     }
     if extra.get("sam21_fallback_reason"):
         out["sam21_fallback_reason"] = extra["sam21_fallback_reason"]
+    if "plane_applied" in extra:
+        out["plane_applied"] = extra["plane_applied"]
+        out["n_points_before_plane"] = extra["n_points_before_plane"]
 
     T_base_cam = _load_calibration()
     if T_base_cam is not None and len(pts_cv) > 0:
@@ -177,7 +184,9 @@ def _object_cloud_cv(nuwa, bbox: tuple[int, int, int, int], max_points: int,
     extra: dict[str, Any] = {}
     if cfg.get("grasp", {}).get("use_sam21", True):
         try:
-            pts_cv = points_via_sam21(nuwa, _deps.sam21(), bbox, sw)
+            pts_cv, plane_info = points_via_sam21(nuwa, _deps.sam21(), bbox, sw)
+            extra["plane_applied"] = plane_info["plane_applied"]
+            extra["n_points_before_plane"] = plane_info["n_points_before_plane"]
             if len(pts_cv) > max_points:
                 idx = np.random.choice(len(pts_cv), max_points, replace=False)
                 pts_cv = pts_cv[idx]
@@ -198,10 +207,13 @@ def _object_cloud_cv(nuwa, bbox: tuple[int, int, int, int], max_points: int,
         raise HTTPException(status_code=502, detail=f"Nuwa pointcloud ROI failed: {e}")
     with sw.step("filter_outliers"):
         cropped = filter_outliers(pc)
-    if len(cropped) > max_points:
-        idx = np.random.choice(len(cropped), max_points, replace=False)
-        cropped = cropped[idx]
     pts_cv = nuwa_to_cv_frame(cropped[:, :3]) if len(cropped) else np.empty((0, 3), dtype=np.float64)
+    pts_cv, plane_info = apply_below_plane_filter(pts_cv, get_work_plane())
+    extra["plane_applied"] = plane_info["plane_applied"]
+    extra["n_points_before_plane"] = plane_info["n_points_before_plane"]
+    if len(pts_cv) > max_points:
+        idx = np.random.choice(len(pts_cv), max_points, replace=False)
+        pts_cv = pts_cv[idx]
     return pts_cv, "bbox_roi", extra