def get_old_to_new_pose_mat(self, old_pose, new_pose):
old_T_inv = self.pose_2d_to_mat_np(old_pose, inv=True)
new_T = self.pose_2d_to_mat_np(new_pose, inv=False)
mat = np.dot(new_T, old_T_inv)
#mat = new_T
mat_t = np_to_tensor(mat)
return mat_t
def get_old_to_new_pose_mat(self, old_pose, new_pose):
old_T_inv = self.pose_2d_to_mat_np(old_pose,
self.source_map_size_px,
inv=True)
new_T = self.pose_2d_to_mat_np(new_pose,
self.dest_map_size_px,
inv=False)
mat = np.dot(new_T, old_T_inv)
#mat = new_T
mat_t = np_to_tensor(mat, cuda=False)
return mat_t
def get_old_to_new_pose_matrices(self, old_pose, new_pose):
old_T_inv = self.poses_2d_to_mat_np(old_pose,
self.source_map_size_px,
inv=True)
new_T = self.poses_2d_to_mat_np(new_pose,
self.dest_map_size_px,
inv=False)
mat = np.matmul(new_T, old_T_inv)
#mat = new_T
mat_t = np_to_tensor(mat, insert_batch_dim=False, cuda=False)
return mat_t
def get_pytorch_to_img_mat(self, img_size, inv=False):
"""
Returns an affine transformation matrix that takes an image in coordinate range [-1,1] and turns it
into an image of coordinate range [W,H]
:param img_size: (W,H)
:return:
"""
# First move the image so that the origin is in the top-left corner
# (in pytorch, the origin is in the center of the image)
"""
t1 = np.asarray([
[1.0, 0, 1.0],
[0, 1.0, 1.0],
[0, 0, 1.0]
])
# Then scale the image up to the required size
scale_w = img_size[0] / 2
scale_h = img_size[1] / 2
t2 = np.asarray([
[scale_h, 0, 0],
[0, scale_w, 0],
[0, 0, 1]
])
"""
# First scale the image to pixel coordinates
scale_w = img_size[0] / 2
scale_h = img_size[1] / 2
t1 = np.asarray([[scale_h, 0, 0], [0, scale_w, 0], [0, 0, 1]])
# Then move it such that the corner is at the origin
t2 = np.asarray([[1.0, 0, scale_h], [0, 1.0, scale_w], [0, 0, 1.0]])
T = np.dot(t2, t1)
if inv:
T = np.linalg.inv(T)
T_t = np_to_tensor(T, cuda=False)
return T_t