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6D representation of rotations.

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Summary: Conversion to/from the 6D representation of rotation from the paper http://arxiv.org/abs/1812.07035 ; based on David’s implementation.

Reviewed By: davnov134

Differential Revision: D22234397

fbshipit-source-id: 9e25ee93da7e3a2f2068cbe362cb5edc88649ce0
This commit is contained in:
Roman Shapovalov
2020-07-08 03:59:51 -07:00
committed by Facebook GitHub Bot
parent ce3da64917
commit 2f3cd98725
4 changed files with 81 additions and 7 deletions
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33
tests/test_rotation_conversions.py
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@@ -6,16 +6,19 @@ import math
import unittest
import torch
from common_testing import TestCaseMixin
from pytorch3d.transforms.rotation_conversions import (
euler_angles_to_matrix,
matrix_to_euler_angles,
matrix_to_quaternion,
matrix_to_rotation_6d,
quaternion_apply,
quaternion_multiply,
quaternion_to_matrix,
random_quaternions,
random_rotation,
random_rotations,
rotation_6d_to_matrix,
)
@@ -48,7 +51,7 @@ class TestRandomRotation(unittest.TestCase):
self.assertLess(chisquare_statistic, 12, (counts, chisquare_statistic, k))
class TestRotationConversion(unittest.TestCase):
class TestRotationConversion(TestCaseMixin, unittest.TestCase):
def setUp(self) -> None:
super().setUp()
torch.manual_seed(1)
@@ -154,3 +157,31 @@ class TestRotationConversion(unittest.TestCase):
[p, q] = torch.autograd.grad(transform1.sum(), [points, quaternions])
self.assertTrue(torch.isfinite(p).all())
self.assertTrue(torch.isfinite(q).all())
def test_6d(self):
"""Converting to 6d and back"""
r = random_rotations(13, dtype=torch.float64)
# 6D representation is not unique,
# but we implement it by taking the first two rows of the matrix
r6d = matrix_to_rotation_6d(r)
self.assertClose(r6d, r[:, :2, :].reshape(-1, 6))
# going to 6D and back should not change the matrix
r_hat = rotation_6d_to_matrix(r6d)
self.assertClose(r_hat, r)
# moving the second row R2 in the span of (R1, R2) should not matter
r6d[:, 3:] += 2 * r6d[:, :3]
r6d[:, :3] *= 3.0
r_hat = rotation_6d_to_matrix(r6d)
self.assertClose(r_hat, r)
# check that we map anything to a valid rotation
r6d = torch.rand(13, 6)
r6d[:4, :] *= 3.0
r6d[4:8, :] -= 0.5
r = rotation_6d_to_matrix(r6d)
self.assertClose(
torch.matmul(r, r.permute(0, 2, 1)), torch.eye(3).expand_as(r), atol=1e-6
)