feat(perception): work_plane module with below-plane filter

Owns WorkPlane (with new offset_mm field), fit_plane_svd, disk-backed
get/set, and the apply_below_plane_filter helper. WorkPlane.normal lives
in OpenCV RGB-camera frame and is oriented toward the camera. The filter
keeps points where signed_distance >= -offset_mm/1000.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Adriano Dal PastroandClaude Opus 4.7 committed 2026-05-11 16:41:35 +02:00
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"""Work-plane fit, persistence, and below-plane filter.
The work plane is fitted from a user-drawn rectangle on the RGB image. The
fit uses SVD on the bbox depth cloud (after `nuwa_to_cv_frame`), so the
plane normal lives in OpenCV RGB-camera frame and is oriented toward the
camera (negative Z component in OpenCV convention).
The filter `apply_below_plane_filter` removes points more than `offset_mm`
below the plane: keep `(normal · X + offset) >= -offset_mm/1000`. A
positive `offset_mm` is permissive (preserves a buffer below the plane).
"""
from __future__ import annotations
import json
import logging
from dataclasses import asdict, dataclass
from pathlib import Path
import numpy as np
from ..config import data_dir
log = logging.getLogger(__name__)
class WorkPlaneError(RuntimeError):
"""Bad input to `fit_plane_svd` (too few points, degenerate cloud)."""
@dataclass
class WorkPlane:
"""Plane in CV camera frame. `normal · X + offset = 0`; `normal` is
unit-length and oriented toward the camera (negative Z in OpenCV)."""
normal: list[float]
offset: float
centroid: list[float]
n_inliers: int
fit_rms_mm: float
roi: list[int]
offset_mm: float
created_at: float
_WORK_PLANE: WorkPlane | None = None
_WORK_PLANE_LOADED = False
def _work_plane_path() -> Path:
return data_dir() / "work_plane.json"
def _save_work_plane_to_disk(wp: WorkPlane | None) -> None:
path = _work_plane_path()
try:
if wp is None:
if path.exists():
path.unlink()
return
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(asdict(wp), indent=2))
except Exception as e:
log.warning("failed to persist work plane: %s", e)
def _load_work_plane_from_disk() -> WorkPlane | None:
path = _work_plane_path()
try:
with open(path, "r") as f:
d = json.load(f)
d.setdefault("offset_mm", 5.0) # legacy files
return WorkPlane(**d)
except FileNotFoundError:
return None
except Exception as e:
log.warning("failed to load persisted work plane (%s)", e)
return None
def get_work_plane() -> WorkPlane | None:
global _WORK_PLANE, _WORK_PLANE_LOADED
if not _WORK_PLANE_LOADED:
_WORK_PLANE = _load_work_plane_from_disk()
_WORK_PLANE_LOADED = True
return _WORK_PLANE
def set_work_plane(wp: WorkPlane | None) -> None:
global _WORK_PLANE, _WORK_PLANE_LOADED
_WORK_PLANE = wp
_WORK_PLANE_LOADED = True
_save_work_plane_to_disk(wp)
def fit_plane_svd(points_xyz: np.ndarray
) -> tuple[np.ndarray, float, np.ndarray, float]:
"""Least-squares plane via SVD. Returns (normal, offset, centroid, rms_mm).
Plane equation: `normal · X + offset = 0`. Normal is oriented toward
the camera origin (so `signed_distance = normal · X + offset` is
positive for points on the camera side of the plane)."""
pts = np.asarray(points_xyz, dtype=np.float64)
if pts.ndim != 2 or pts.shape[1] < 3:
raise WorkPlaneError(f"unexpected points shape for plane fit: {pts.shape}")
xyz = pts[:, :3]
if len(xyz) < 10:
raise WorkPlaneError(f"too few points to fit plane: {len(xyz)}")
c = xyz.mean(axis=0)
centered = xyz - c
_, _, Vt = np.linalg.svd(centered, full_matrices=False)
normal = Vt[-1]
n = float(np.linalg.norm(normal))
if n < 1e-9:
raise WorkPlaneError("degenerate plane (zero normal)")
normal = normal / n
# Orient toward camera origin: signed distance of origin from plane must
# be positive, i.e. `-n·c > 0`, i.e. `n·c < 0`.
if float(normal @ c) > 0:
normal = -normal
offset = -float(normal @ c)
signed = centered @ normal
rms_mm = float(np.sqrt(np.mean(signed * signed)) * 1000.0)
return normal, offset, c, rms_mm
def apply_below_plane_filter(
pts_cv: np.ndarray,
wp: WorkPlane | None,
) -> tuple[np.ndarray, dict]:
"""Drop points more than `offset_mm` below the plane.
Returns `(filtered_pts, info)`. `info` always carries:
plane_applied (bool): true iff a plane was provided AND there were
points to filter
n_points_before_plane (int): len(pts_cv) on entry
"""
info = {"plane_applied": False,
"n_points_before_plane": int(len(pts_cv))}
if wp is None or len(pts_cv) == 0:
return pts_cv, info
n_vec = np.asarray(wp.normal, dtype=np.float64)
d_off = float(wp.offset)
offset_m = float(wp.offset_mm) / 1000.0
signed = pts_cv @ n_vec + d_off
keep = signed >= -offset_m
info["plane_applied"] = True
return pts_cv[keep], info
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"""Unit tests for perception.work_plane."""
from __future__ import annotations
import json
import tempfile
from pathlib import Path
from unittest.mock import patch
import numpy as np
import pytest
from presa_mano.perception.work_plane import (
WorkPlane,
WorkPlaneError,
apply_below_plane_filter,
fit_plane_svd,
_load_work_plane_from_disk,
_save_work_plane_to_disk,
_work_plane_path,
)
def _flat_plane_cloud(z: float = 1.0, n: int = 200, noise_m: float = 0.0):
"""Cloud sampled on the plane z=z (camera frame, OpenCV: camera looks +Z)."""
rng = np.random.default_rng(0)
xy = rng.uniform(-0.2, 0.2, size=(n, 2))
zs = np.full((n, 1), z) + rng.normal(0, noise_m, size=(n, 1))
return np.hstack([xy, zs])
def test_fit_plane_svd_horizontal_plane():
"""Plane at z=1.0, normal must point toward camera (negative Z)."""
pts = _flat_plane_cloud(z=1.0, n=200, noise_m=0.0)
normal, offset, centroid, rms_mm = fit_plane_svd(pts)
assert abs(normal[2]) > 0.99
assert normal[2] < 0
assert abs(offset - 1.0) < 1e-3
assert rms_mm < 1.0
def test_fit_plane_svd_raises_on_too_few_points():
with pytest.raises(WorkPlaneError):
fit_plane_svd(np.zeros((5, 3)))
def test_apply_below_plane_filter_noop_without_plane():
pts = _flat_plane_cloud(z=1.0)
out, info = apply_below_plane_filter(pts, None)
assert info["plane_applied"] is False
assert info["n_points_before_plane"] == len(pts)
assert out is pts
def test_apply_below_plane_filter_keeps_above_drops_below():
"""Plane at z=1.0, normal toward camera (-Z): points with z<1.0 are above."""
above = _flat_plane_cloud(z=0.95, n=100)
below = _flat_plane_cloud(z=1.10, n=100)
pts = np.vstack([above, below])
wp = WorkPlane(
normal=[0.0, 0.0, -1.0], offset=1.0,
centroid=[0.0, 0.0, 1.0],
n_inliers=100, fit_rms_mm=0.0,
roi=[0, 0, 10, 10],
offset_mm=0.0,
created_at=0.0,
)
out, info = apply_below_plane_filter(pts, wp)
assert info["plane_applied"] is True
assert info["n_points_before_plane"] == 200
assert len(out) == 100
assert np.all(out[:, 2] <= 1.0 + 1e-9)
def test_apply_below_plane_filter_offset_buffer_keeps_below():
"""offset_mm=50 keeps points up to 50mm below the plane."""
above = _flat_plane_cloud(z=0.95, n=50)
just_below = _flat_plane_cloud(z=1.03, n=50)
far_below = _flat_plane_cloud(z=1.20, n=50)
pts = np.vstack([above, just_below, far_below])
wp = WorkPlane(
normal=[0.0, 0.0, -1.0], offset=1.0,
centroid=[0.0, 0.0, 1.0],
n_inliers=50, fit_rms_mm=0.0,
roi=[0, 0, 10, 10],
offset_mm=50.0,
created_at=0.0,
)
out, info = apply_below_plane_filter(pts, wp)
assert info["plane_applied"] is True
assert len(out) == 100 # above (50) + just_below (50); far_below dropped
def test_apply_below_plane_filter_empty_input():
wp = WorkPlane(
normal=[0.0, 0.0, -1.0], offset=1.0,
centroid=[0.0, 0.0, 1.0],
n_inliers=10, fit_rms_mm=0.0,
roi=[0, 0, 10, 10],
offset_mm=5.0, created_at=0.0,
)
out, info = apply_below_plane_filter(np.empty((0, 3)), wp)
assert info["plane_applied"] is False # short-circuit: empty input never "ran"
assert info["n_points_before_plane"] == 0
assert len(out) == 0
def test_work_plane_disk_roundtrip(tmp_path, monkeypatch):
"""Save then load preserves all fields including offset_mm."""
monkeypatch.setenv("PRESA_MANO_DATA", str(tmp_path))
wp = WorkPlane(
normal=[0.0, 0.0, -1.0], offset=1.0,
centroid=[0.1, 0.2, 1.0],
n_inliers=42, fit_rms_mm=1.5,
roi=[10, 20, 100, 200],
offset_mm=7.5,
created_at=1234567890.0,
)
_save_work_plane_to_disk(wp)
loaded = _load_work_plane_from_disk()
assert loaded is not None
assert loaded.normal == wp.normal
assert loaded.offset == wp.offset
assert loaded.centroid == wp.centroid
assert loaded.n_inliers == wp.n_inliers
assert loaded.fit_rms_mm == wp.fit_rms_mm
assert loaded.roi == wp.roi
assert loaded.offset_mm == 7.5
assert loaded.created_at == wp.created_at
def test_work_plane_load_legacy_file_defaults_offset(tmp_path, monkeypatch):
"""A pre-existing work_plane.json without offset_mm gets the 5.0 default."""
monkeypatch.setenv("PRESA_MANO_DATA", str(tmp_path))
path = _work_plane_path()
legacy = {
"normal": [0.0, 0.0, -1.0], "offset": 1.0,
"centroid": [0.0, 0.0, 1.0],
"n_inliers": 10, "fit_rms_mm": 1.0,
"roi": [0, 0, 10, 10],
"created_at": 0.0,
}
path.write_text(json.dumps(legacy))
loaded = _load_work_plane_from_disk()
assert loaded is not None
assert loaded.offset_mm == 5.0