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diff --git a/opensfm/exif.py b/opensfm/exif.py
--- a/opensfm/exif.py
+++ b/opensfm/exif.py
@@ -509,7 +509,7 @@ class EXIF:
)
)
- if np.all(ypr) is not None:
+ if np.all(ypr != None):
ypr = np.radians(ypr)
# Convert YPR --> OPK
diff --git a/opensfm/transformations.py b/opensfm/transformations.py
--- a/opensfm/transformations.py
+++ b/opensfm/transformations.py
@@ -232,7 +232,7 @@ def translation_from_matrix(matrix: numpy.ndarray) -> numpy.ndarray:
True
"""
- return numpy.array(matrix, copy=False)[:3, 3].copy()
+ return numpy.asarray(matrix)[:3, 3].copy()
def reflection_matrix(point: numpy.ndarray, normal: numpy.ndarray) -> numpy.ndarray:
@@ -275,7 +275,7 @@ def reflection_from_matrix(
True
"""
- M = numpy.array(matrix, dtype=numpy.float64, copy=False)
+ M = numpy.asarray(matrix, dtype=numpy.float64)
# normal: unit eigenvector corresponding to eigenvalue -1
w, V = numpy.linalg.eig(M[:3, :3])
i = numpy.where(abs(numpy.real(w) + 1.0) < 1e-8)[0]
@@ -339,7 +339,7 @@ def rotation_matrix(
M[:3, :3] = R
if point is not None:
# rotation not around origin
- point = numpy.array(point[:3], dtype=numpy.float64, copy=False)
+ point = numpy.asarray(point[:3], dtype=numpy.float64)
M[:3, 3] = point - numpy.dot(R, point)
return M
@@ -359,7 +359,7 @@ def rotation_from_matrix(
True
"""
- R = numpy.array(matrix, dtype=numpy.float64, copy=False)
+ R = numpy.asarray(matrix, dtype=numpy.float64)
R33 = R[:3, :3]
# direction: unit eigenvector of R33 corresponding to eigenvalue of 1
w, W = numpy.linalg.eig(R33.T)
@@ -444,7 +444,7 @@ def scale_from_matrix(
True
"""
- M = numpy.array(matrix, dtype=numpy.float64, copy=False)
+ M = numpy.asarray(matrix, dtype=numpy.float64)
M33 = M[:3, :3]
factor = numpy.trace(M33) - 2.0
try:
@@ -505,11 +505,11 @@ def projection_matrix(
"""
M = numpy.identity(4)
- point = numpy.array(point[:3], dtype=numpy.float64, copy=False)
+ point = numpy.asarray(point[:3], dtype=numpy.float64)
normal = unit_vector(normal[:3])
if perspective is not None:
# perspective projection
- perspective = numpy.array(perspective[:3], dtype=numpy.float64, copy=False)
+ perspective = numpy.asarray(perspective[:3], dtype=numpy.float64)
M[0, 0] = M[1, 1] = M[2, 2] = numpy.dot(perspective - point, normal)
M[:3, :3] -= numpy.outer(perspective, normal)
if pseudo:
@@ -522,7 +522,7 @@ def projection_matrix(
M[3, 3] = numpy.dot(perspective, normal)
elif direction is not None:
# parallel projection
- direction = numpy.array(direction[:3], dtype=numpy.float64, copy=False)
+ direction = numpy.asarray(direction[:3], dtype=numpy.float64)
scale = numpy.dot(direction, normal)
M[:3, :3] -= numpy.outer(direction, normal) / scale
M[:3, 3] = direction * (numpy.dot(point, normal) / scale)
@@ -569,7 +569,7 @@ def projection_from_matrix(
True
"""
- M = numpy.array(matrix, dtype=numpy.float64, copy=False)
+ M = numpy.asarray(matrix, dtype=numpy.float64)
M33 = M[:3, :3]
w, V = numpy.linalg.eig(M)
i = numpy.where(abs(numpy.real(w) - 1.0) < 1e-8)[0]
@@ -726,7 +726,7 @@ def shear_from_matrix(
True
"""
- M = numpy.array(matrix, dtype=numpy.float64, copy=False)
+ M = numpy.asarray(matrix, dtype=numpy.float64)
M33 = M[:3, :3]
# normal: cross independent eigenvectors corresponding to the eigenvalue 1
w, V = numpy.linalg.eig(M33)
@@ -790,7 +790,7 @@ def decompose_matrix(
True
"""
- M = numpy.array(matrix, dtype=numpy.float64, copy=True).T
+ M = numpy.asarray(matrix, dtype=numpy.float64, copy=True).T
if abs(M[3, 3]) < _EPS:
raise ValueError("M[3, 3] is zero")
M /= M[3, 3]
@@ -982,8 +982,8 @@ def affine_matrix_from_points(
More examples in superimposition_matrix()
"""
- v0 = numpy.array(v0, dtype=numpy.float64, copy=True)
- v1 = numpy.array(v1, dtype=numpy.float64, copy=True)
+ v0 = numpy.asarray(v0, dtype=numpy.float64, copy=True)
+ v1 = numpy.asarray(v1, dtype=numpy.float64, copy=True)
ndims = v0.shape[0]
if ndims < 2 or v0.shape[1] < ndims or v0.shape != v1.shape:
@@ -1099,8 +1099,8 @@ def superimposition_matrix(
True
"""
- v0 = numpy.array(v0, dtype=numpy.float64, copy=False)[:3]
- v1 = numpy.array(v1, dtype=numpy.float64, copy=False)[:3]
+ v0 = numpy.asarray(v0, dtype=numpy.float64)[:3]
+ v1 = numpy.asarray(v1, dtype=numpy.float64)[:3]
return affine_matrix_from_points(v0, v1, shear=False, scale=scale, usesvd=usesvd)
@@ -1198,7 +1198,7 @@ def euler_from_matrix(
j = _NEXT_AXIS[i + parity]
k = _NEXT_AXIS[i - parity + 1]
- M = numpy.array(matrix, dtype=numpy.float64, copy=False)[:3, :3]
+ M = numpy.asarray(matrix, dtype=numpy.float64)[:3, :3]
if repetition:
sy = math.sqrt(M[i, j] * M[i, j] + M[i, k] * M[i, k])
if sy > _EPS:
@@ -1329,7 +1329,7 @@ def quaternion_matrix(quaternion: numpy.ndarray) -> numpy.ndarray:
True
"""
- q = numpy.array(quaternion, dtype=numpy.float64, copy=True)
+ q = numpy.asarray(quaternion, dtype=numpy.float64, copy=True)
n = numpy.dot(q, q)
if n < _EPS:
return numpy.identity(4)
@@ -1379,7 +1379,7 @@ def quaternion_from_matrix(
True
"""
- M = numpy.array(matrix, dtype=numpy.float64, copy=False)[:4, :4]
+ M = numpy.asarray(matrix, dtype=numpy.float64)[:4, :4]
if isprecise:
q = numpy.empty((4,))
t = numpy.trace(M)
@@ -1460,7 +1460,7 @@ def quaternion_conjugate(quaternion: numpy.ndarray) -> numpy.ndarray:
True
"""
- q = numpy.array(quaternion, dtype=numpy.float64, copy=True)
+ q = numpy.asarray(quaternion, dtype=numpy.float64, copy=True)
numpy.negative(q[1:], q[1:])
return q
@@ -1474,7 +1474,7 @@ def quaternion_inverse(quaternion: numpy.ndarray) -> numpy.ndarray:
True
"""
- q = numpy.array(quaternion, dtype=numpy.float64, copy=True)
+ q = numpy.asarray(quaternion, dtype=numpy.float64, copy=True)
numpy.negative(q[1:], q[1:])
return q / numpy.dot(q, q)
@@ -1496,7 +1496,7 @@ def quaternion_imag(quaternion: numpy.ndarray) -> numpy.ndarray:
array([ 0., 1., 2.])
"""
- return numpy.array(quaternion[1:4], dtype=numpy.float64, copy=True)
+ return numpy.asarray(quaternion[1:4], dtype=numpy.float64, copy=True)
def quaternion_slerp(
@@ -1654,7 +1654,7 @@ def vector_norm(
1.0
"""
- data = numpy.array(data, dtype=numpy.float64, copy=True)
+ data = numpy.asarray(data, dtype=numpy.float64, copy=True)
if out is None:
if data.ndim == 1:
return math.sqrt(numpy.dot(data, data))
@@ -1697,13 +1697,13 @@ def unit_vector(
"""
if out is None:
- data = numpy.array(data, dtype=numpy.float64, copy=True)
+ data = numpy.asarray(data, dtype=numpy.float64, copy=True)
if data.ndim == 1:
data /= math.sqrt(numpy.dot(data, data))
return data
else:
if out is not data:
- out[:] = numpy.array(data, copy=False)
+ out[:] = numpy.asarray(data)
data = out
length = numpy.atleast_1d(numpy.sum(data * data, axis))
numpy.sqrt(length, length)
@@ -1777,8 +1777,8 @@ def angle_between_vectors(
True
"""
- v0 = numpy.array(v0, dtype=numpy.float64, copy=False)
- v1 = numpy.array(v1, dtype=numpy.float64, copy=False)
+ v0 = numpy.asarray(v0, dtype=numpy.float64)
+ v1 = numpy.asarray(v1, dtype=numpy.float64)
dot = numpy.sum(v0 * v1, axis=axis)
dot /= vector_norm(v0, axis=axis) * vector_norm(v1, axis=axis)
dot = numpy.clip(dot, -1.0, 1.0)
@@ -1826,9 +1826,9 @@ def is_same_transform(matrix0: numpy.ndarray, matrix1: numpy.ndarray) -> numpy.n
False
"""
- matrix0 = numpy.array(matrix0, dtype=numpy.float64, copy=True)
+ matrix0 = numpy.asarray(matrix0, dtype=numpy.float64, copy=True)
matrix0 /= matrix0[3, 3]
- matrix1 = numpy.array(matrix1, dtype=numpy.float64, copy=True)
+ matrix1 = numpy.asarray(matrix1, dtype=numpy.float64, copy=True)
matrix1 /= matrix1[3, 3]
return numpy.allclose(matrix0, matrix1)
@@ -1874,3 +1874,4 @@ if __name__ == "__main__":
numpy.set_printoptions(suppress=True, precision=5)
doctest.testmod()
+
|
