def test_fitting_vector_dimension(self):
with self.assertRaises(Exception):
listA = [[0, 0], [1, 0], [0, 1]]
listB = [[0, 0, 0], [1, 0, 0], [0, 1, 0]]
psf.point_sets_fitting(listA, listB)
with self.assertRaises(Exception):
listA = [[0, 0, 0], [1, 0, 0], [0, 1, 0]]
listB = [[0, 0], [1, 0], [0, 1]]
psf.point_sets_fitting(listA, listB)
def test_fitting_translation(self):
setA = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0,
2]]).transpose()
expectedTransformation = compose([10, 2, 5], np.eye(3, 3), np.ones(3))
setB = expectedTransformation @ psf.to_homogeneous_repr(setA)
expectedError = 0
transformation, err = psf.point_sets_fitting(setA, setB[0:3, :])
np.testing.assert_array_almost_equal(expectedTransformation,
transformation,
decimal=5)
self.assertAlmostEqual(expectedError, err, delta=0.0001)
def test_fitting_identity(self):
set_a = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0,
2]]).transpose()
set_b = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0,
2]]).transpose()
expected_error = 0
expected_transformation = np.eye(4, 4)
transformation, err = psf.point_sets_fitting(set_a, set_b)
np.testing.assert_array_almost_equal(expected_transformation,
transformation,
decimal=5)
self.assertAlmostEqual(expected_error, err, delta=0.0001)
def test_fitting_noisefree_10P(self):
for k in range(1000):
setA = np.random.rand(3, 10)
trans = np.random.rand(1, 3)
expTr = compose(
trans[0, :],
euler2mat(np.random.rand(), np.random.rand(),
np.random.rand()), np.ones(3))
setB = expTr @ psf.to_homogeneous_repr(setA)
expError = 0
transformation, err = psf.point_sets_fitting(setA, setB[0:3, :])
np.testing.assert_array_almost_equal(expTr,
transformation,
decimal=5)
self.assertAlmostEqual(expError, err, delta=0.0001)
def test_fitting_too_few_points(self):
with self.assertRaises(Exception):
listA = [[0, 0, 0], [1, 0, 0]]
listB = [[0, 0, 0], [1, 0, 0]]
psf.point_sets_fitting(listA, listB)
def test_fitting_differen_set_lengths(self):
with self.assertRaises(Exception):
listA = [[0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 2]]
listB = [[0, 0, 0], [1, 0, 0], [0, 1, 0]]
psf.point_sets_fitting(listA, listB)
if __name__ == '__main__':
obj_path_name = utility.return_obj_path(
"C:/Users/user/Desktop/Mesh/InofitLab")
target = pywavefront.Wavefront(obj_path_name[0][1], collect_faces=True)
target_vertices = numpy.array(target.vertices, dtype='f').transpose()
for template_path in obj_path_name:
template = pywavefront.Wavefront(template_path[1], collect_faces=True)
template_vertices = numpy.array(template.vertices,
dtype='f').transpose()
faces = numpy.array(template.mesh_list[0].faces).transpose()
rigid_transformation, error = point_sets_fitting.point_sets_fitting(
template_vertices, target_vertices)
trainsformation_result = rigid_transformation[
0:3, 0:3] @ template_vertices + rigid_transformation[0:3,
3].reshape(
-1, 1)
print("Original fitting Error of {0} = {1}".format(
template_path[0],
utility.calculate_fitting_error(template_vertices,
target_vertices)))
print("Transformed fitting Error {0}= {1}\n".format(
template_path[0],
utility.calculate_fitting_error(trainsformation_result,
target_vertices)))