feat(geometry): umeyama_similarity (rot+trasl+scala uniforme)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
AdrianoandClaude Sonnet 4.6 committed 2026-06-03 12:13:25 +02:00
1 parent 9189700f34
commit 77fb0f8fc0
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@@ -147,13 +147,13 @@ pose_3d:
cloud_params: cloud_params:
step: 2 step: 2
max_depth_mm: 1000 max_depth_mm: 1000
nuwa_size_mm: 5 nuwa_size_mm: 3
d435_size_mm: 5 d435_size_mm: 3
d435_scale_xy: 1 d435_scale_xy: 1
flip_nuwa: flip_nuwa:
- false - false
- false - true
- false - true
flip_d435: flip_d435:
- false - false
- false - false
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@@ -142,3 +142,41 @@ def quaternion_xyzw_to_rpy_deg(quat_xyzw) -> tuple[float, float, float]:
rpy_rad = R_to_euler_xyz(R) rpy_rad = R_to_euler_xyz(R)
rpy_deg = np.degrees(rpy_rad) rpy_deg = np.degrees(rpy_rad)
return float(rpy_deg[0]), float(rpy_deg[1]), float(rpy_deg[2]) return float(rpy_deg[0]), float(rpy_deg[1]), float(rpy_deg[2])
def umeyama_similarity(src: np.ndarray, dst: np.ndarray) -> tuple[float, np.ndarray, np.ndarray, float]:
"""Fit dst ≈ s·R·src + t (Umeyama 1991, con scala uniforme).
src, dst: (N,3) array di punti corrispondenti.
Ritorna (scale: float, R: (3,3), t: (3,), rmse: float in unità di dst).
Solleva ValueError se N<3 o il set è degenere (varianza nulla).
"""
src = np.asarray(src, dtype=np.float64).reshape(-1, 3)
dst = np.asarray(dst, dtype=np.float64).reshape(-1, 3)
if src.shape != dst.shape:
raise ValueError(f"shape mismatch: {src.shape} vs {dst.shape}")
n = src.shape[0]
if n < 3:
raise ValueError(f"servono almeno 3 punti, ricevuti {n}")
mu_src = src.mean(axis=0)
mu_dst = dst.mean(axis=0)
src_c = src - mu_src
dst_c = dst - mu_dst
var_src = (src_c ** 2).sum() / n
if var_src < 1e-12:
raise ValueError("punti src degeneri (varianza nulla)")
cov = (dst_c.T @ src_c) / n
U, D, Vt = np.linalg.svd(cov)
S = np.eye(3)
if np.linalg.det(U) * np.linalg.det(Vt) < 0:
S[2, 2] = -1.0 # vieta riflessioni
R = U @ S @ Vt
scale = float((D * np.diag(S)).sum() / var_src)
t = mu_dst - scale * (R @ mu_src)
pred = (scale * (R @ src.T)).T + t
rmse = float(np.sqrt(((pred - dst) ** 2).sum(axis=1).mean()))
return scale, R, t, rmse
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@@ -0,0 +1,49 @@
"""Unit test per umeyama_similarity (absolute orientation con scala)."""
from __future__ import annotations
import numpy as np
import pytest
from presa_mano.geometry import umeyama_similarity, rpy_deg_to_quaternion_xyzw, quat_xyzw_to_R
def _known_transform():
# scala 1.5, rotazione nota, traslazione nota
R = quat_xyzw_to_R(rpy_deg_to_quaternion_xyzw(10.0, -20.0, 35.0))
s = 1.5
t = np.array([0.3, -0.1, 0.2])
return s, R, t
def test_recovers_known_similarity():
s, R, t = _known_transform()
rng = np.random.default_rng(0)
src = rng.normal(size=(8, 3))
dst = (s * (R @ src.T)).T + t
s_hat, R_hat, t_hat, rmse = umeyama_similarity(src, dst)
assert abs(s_hat - s) < 1e-6
assert np.allclose(R_hat, R, atol=1e-6)
assert np.allclose(t_hat, t, atol=1e-6)
assert rmse < 1e-6
def test_forbids_reflection():
rng = np.random.default_rng(1)
src = rng.normal(size=(5, 3))
dst = rng.normal(size=(5, 3))
_, R_hat, _, _ = umeyama_similarity(src, dst)
assert np.linalg.det(R_hat) > 0
def test_raises_on_too_few_points():
with pytest.raises(ValueError):
umeyama_similarity(np.zeros((2, 3)), np.zeros((2, 3)))
def test_raises_on_degenerate_points():
src = np.ones((4, 3))
dst = np.ones((4, 3)) * 2.0
with pytest.raises(ValueError):
umeyama_similarity(src, dst)