feat(perception): partition_by_plane returns accepted + excluded sets

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Adriano Dal PastroandClaude Opus 4.7 committed 2026-05-13 10:00:09 +02:00
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@@ -122,25 +122,35 @@ def fit_plane_svd(points_xyz: np.ndarray
return normal, offset, c, rms_mm return normal, offset, c, rms_mm
def apply_below_plane_filter( def partition_by_plane(
pts_cv: np.ndarray, pts_cv: np.ndarray,
wp: WorkPlane | None, wp: WorkPlane | None,
) -> tuple[np.ndarray, dict]: ) -> tuple[np.ndarray, np.ndarray, dict]:
"""Drop points more than `offset_mm` below the plane. """Split points into (accepted_above_plane, excluded_below_plane).
Returns `(filtered_pts, info)`. `info` always carries: Same threshold as `apply_below_plane_filter`: keep iff
plane_applied (bool): true iff a plane was provided AND there were `signed >= -offset_mm/1000`. When `wp is None` or `pts_cv` is empty,
points to filter `excluded` is empty and `plane_applied=False`.
n_points_before_plane (int): len(pts_cv) on entry
""" """
info = {"plane_applied": False, info = {"plane_applied": False,
"n_points_before_plane": int(len(pts_cv))} "n_points_before_plane": int(len(pts_cv))}
empty = np.empty((0, 3), dtype=pts_cv.dtype if pts_cv.size else np.float64)
if wp is None or len(pts_cv) == 0: if wp is None or len(pts_cv) == 0:
return pts_cv, info return pts_cv, empty, info
n_vec = np.asarray(wp.normal, dtype=np.float64) n_vec = np.asarray(wp.normal, dtype=np.float64)
d_off = float(wp.offset) d_off = float(wp.offset)
offset_m = float(wp.offset_mm) / 1000.0 offset_m = float(wp.offset_mm) / 1000.0
signed = pts_cv @ n_vec + d_off signed = pts_cv @ n_vec + d_off
keep = signed >= -offset_m keep = signed >= -offset_m
info["plane_applied"] = True info["plane_applied"] = True
return pts_cv[keep], info return pts_cv[keep], pts_cv[~keep], info
def apply_below_plane_filter(
pts_cv: np.ndarray,
wp: WorkPlane | None,
) -> tuple[np.ndarray, dict]:
"""Thin wrapper around partition_by_plane that drops the excluded set.
Kept for backwards compatibility with existing callers."""
accepted, _excluded, info = partition_by_plane(pts_cv, wp)
return accepted, info
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@@ -0,0 +1,76 @@
"""Unit tests for partition_by_plane."""
from __future__ import annotations
import numpy as np
import pytest
from presa_mano.perception.work_plane import WorkPlane, partition_by_plane
def _wp(offset_mm: float = 0.0) -> WorkPlane:
"""Work surface at z=0.5m in OpenCV camera frame (camera at origin
looking +Z). Normal=[0,0,-1] points toward the camera — same convention
as fit_plane_svd. Plane equation: -z + 0.5 = 0."""
return WorkPlane(
normal=[0.0, 0.0, -1.0],
offset=0.5,
centroid=[0.0, 0.0, 0.5],
n_inliers=100,
fit_rms_mm=0.5,
roi=[0, 0, 100, 100],
offset_mm=offset_mm,
created_at=0.0,
)
def test_partition_no_plane_returns_all_accepted():
pts = np.array([[0.0, 0.0, 1.0], [1.0, 2.0, 3.0]])
accepted, excluded, info = partition_by_plane(pts, None)
assert np.array_equal(accepted, pts)
assert excluded.shape == (0, 3)
assert info == {"plane_applied": False, "n_points_before_plane": 2}
def test_partition_empty_input():
pts = np.empty((0, 3), dtype=np.float64)
accepted, excluded, info = partition_by_plane(pts, _wp())
assert accepted.shape == (0, 3)
assert excluded.shape == (0, 3)
assert info["plane_applied"] is False
assert info["n_points_before_plane"] == 0
def test_partition_splits_by_offset():
"""Plane at z=0.5, normal=-Z, offset_mm=5.
Camera-side ("above") is z<0.5. Filter keeps points up to offset_mm
*below* the plane (i.e. z<=0.505) and excludes farther-than-offset
points (z>0.505)."""
pts = np.array([
[0.0, 0.0, 0.40], # 100mm above → accepted
[0.0, 0.0, 0.50], # on plane → accepted (boundary)
[0.0, 0.0, 0.504], # 4mm below → accepted (within offset 5mm)
[0.0, 0.0, 0.510], # 10mm below → excluded
[0.0, 0.0, 1.000], # 500mm below → excluded
])
accepted, excluded, info = partition_by_plane(pts, _wp(offset_mm=5.0))
assert accepted.shape[0] == 3
assert excluded.shape[0] == 2
assert info["plane_applied"] is True
assert info["n_points_before_plane"] == 5
# partition: nessuna sovrapposizione
union = np.vstack([accepted, excluded])
assert sorted(union[:, 2].tolist()) == sorted(pts[:, 2].tolist())
def test_partition_consistent_with_apply_below_plane_filter():
"""`accepted` di partition_by_plane deve essere bit-identico a quello
ritornato da apply_below_plane_filter (l'API legacy non deve cambiare)."""
from presa_mano.perception.work_plane import apply_below_plane_filter
rng = np.random.default_rng(42)
pts = rng.normal(scale=0.1, size=(200, 3))
wp = _wp(offset_mm=10.0)
accepted_new, _excluded, _info = partition_by_plane(pts, wp)
accepted_legacy, info_legacy = apply_below_plane_filter(pts, wp)
np.testing.assert_array_equal(accepted_new, accepted_legacy)
assert info_legacy["n_points_before_plane"] == 200