def run(self):
coreg_data = self.coreg_data
view_obj = 1
trck_init, trck_id = self.tracker.GetTrackerInfo()
# print('CoordCoreg: event {}'.format(self.event.is_set()))
while not self.event.is_set():
try:
if not self.icp_queue.empty():
self.icp, self.m_icp = self.icp_queue.get_nowait()
if not self.object_at_target_queue.empty():
self.target_flag = self.object_at_target_queue.get_nowait()
# print(f"Set the coordinate")
coord_raw, markers_flag = self.tracker.TrackerCoordinates.GetCoordinates()
coord, m_img = corregistrate_object_dynamic(coreg_data, coord_raw, self.ref_mode_id, [self.icp, self.m_icp])
# XXX: This is not the best place to do the logic related to approaching the target when the
# debug tracker is in use. However, the trackers (including the debug trackers) operate in
# the tracker space where it is hard to make the tracker approach the target in the image space.
# Ideally, the transformation from the tracker space to the image space (the function
# corregistrate_object_dynamic above) would be encapsulated in a class together with the
# tracker, and then the whole class would be mocked when using the debug tracker. However,
# those abstractions do not currently exist and doing them would need a larger refactoring.
#
if self.tracker_id == const.DEBUGTRACKAPPROACH and self.target is not None:
if self.last_coord is None:
self.last_coord = np.array(coord)
else:
coord = self.last_coord + (self.target - self.last_coord) * 0.05
self.last_coord = coord
angles = [np.radians(coord[3]), np.radians(coord[4]), np.radians(coord[5])]
translate = coord[0:3]
m_img = tr.compose_matrix(angles=angles, translate=translate)
m_img_flip = m_img.copy()
m_img_flip[1, -1] = -m_img_flip[1, -1]
# self.pipeline.set_message(m_img_flip)
if self.icp:
m_img = bases.transform_icp(m_img, self.m_icp)
self.coord_queue.put_nowait([coord, [coord_raw, markers_flag], m_img, view_obj])
# print('CoordCoreg: put {}'.format(count))
# count += 1
if self.view_tracts:
self.coord_tracts_queue.put_nowait(m_img_flip)
if not self.icp_queue.empty():
self.icp_queue.task_done()
# The sleep has to be in both threads
sleep(self.sle)
except queue.Full:
pass
def OpenOtherFiles(self, group):
# Retreaving matrix from image data
self.matrix, scalar_range, self.filename = image_utils.img2memmap(
group)
hdr = group.header
# if group.affine.any():
# self.affine = group.affine
# Publisher.sendMessage('Update affine matrix',
# affine=self.affine, status=True)
hdr.set_data_dtype('int16')
dims = hdr.get_zooms()
dimsf = tuple([float(s) for s in dims])
wl = float((scalar_range[0] + scalar_range[1]) * 0.5)
ww = float((scalar_range[1] - scalar_range[0]))
self.Slice = sl.Slice()
self.Slice.matrix = self.matrix
self.Slice.matrix_filename = self.filename
self.Slice.spacing = dimsf
self.Slice.window_level = wl
self.Slice.window_width = ww
if group.affine.any():
# TODO: replace the inverse of the affine by the actual affine in the whole code
# remove scaling factor for non-unitary voxel dimensions
# self.affine = image_utils.world2invspace(affine=group.affine)
scale, shear, angs, trans, persp = tr.decompose_matrix(
group.affine)
self.affine = np.linalg.inv(
tr.compose_matrix(scale=None,
shear=shear,
angles=angs,
translate=trans,
perspective=persp))
# print("repos_img: {}".format(repos_img))
self.Slice.affine = self.affine
Publisher.sendMessage('Update affine matrix',
affine=self.affine,
status=True)
scalar_range = int(scalar_range[0]), int(scalar_range[1])
Publisher.sendMessage('Update threshold limits list',
threshold_range=scalar_range)
return self.matrix, self.filename
def world2invspace(affine=None):
"""
Normalize image pixel intensity for int16 gray scale values.
:param repos: list of translation and rotation [trans_x, trans_y, trans_z, rot_x, rot_y, rot_z] to reposition the
vtk object prior to applying the affine matrix transformation. Note: rotation given in degrees
:param user_matrix: affine matrix from image header, prefered QForm matrix
:return: vtk transform filter for repositioning the polydata and affine matrix to be used as SetUserMatrix in actor
"""
# remove scaling factor for non-unitary voxel dimensions
scale, shear, angs, trans, persp = tr.decompose_matrix(affine)
affine_noscale = tr.compose_matrix(scale=None,
shear=shear,
angles=angs,
translate=trans,
perspective=persp)
# repos_img = [0.] * 6
# repos_img[1] = -float(shape[1])
#
# repos_mat = np.identity(4)
# # translation
# repos_mat[:3, -1] = repos_img[:3]
# # rotation (in principle for invesalius space no rotation is needed)
# repos_mat[:3, :3] = tr.euler_matrix(*np.deg2rad(repos_img[3:]), axes='sxyz')[:3, :3]
# if repos:
# transx, transy, transz, rotx, roty, rotz = repos
# # create a transform that rotates the stl source
# transform = vtk.vtkTransform()
# transform.PostMultiply()
# transform.RotateX(rotx)
# transform.RotateY(roty)
# transform.RotateZ(rotz)
# transform.Translate(transx, transy, transz)
#
# transform_filt = vtk.vtkTransformPolyDataFilter()
# transform_filt.SetTransform(transform)
# transform_filt.Update()
# assuming vtk default transformation order is PreMultiply, the user matrix is set so:
# 1. Replace the object -> 2. Transform the object to desired position/orientation
# PreMultiplty: M = M*A where M is current transformation and A is applied transformation
# user_matrix = np.linalg.inv(user_matrix) @ repos_mat
return np.linalg.inv(affine_noscale)
def OpenOtherFiles(self, group):
# Retreaving matrix from image data
self.matrix, scalar_range, self.filename = image_utils.img2memmap(
group)
hdr = group.header
hdr.set_data_dtype('int16')
wl = float((scalar_range[0] + scalar_range[1]) * 0.5)
ww = float((scalar_range[1] - scalar_range[0]))
self.Slice = sl.Slice()
self.Slice.matrix = self.matrix
self.Slice.matrix_filename = self.filename
# even though the axes 0 and 2 are swapped when creating self.matrix
# the spacing should be kept the original, as it is modified somewhere later
# otherwise generate wrong results
# also need to convert to float because original get_zooms return numpy.float32
# which is unsupported by the plist for saving the project
self.Slice.spacing = tuple([float(s) for s in hdr.get_zooms()])
self.Slice.window_level = wl
self.Slice.window_width = ww
if group.affine.any():
# remove scaling factor for non-unitary voxel dimensions
scale, shear, angs, trans, persp = tr.decompose_matrix(
group.affine)
self.Slice.affine = np.linalg.inv(
tr.compose_matrix(scale=None,
shear=shear,
angles=angs,
translate=trans,
perspective=persp))
else:
self.Slice.affine = None
scalar_range = int(scalar_range[0]), int(scalar_range[1])
Publisher.sendMessage('Update threshold limits list',
threshold_range=scalar_range)
return self.matrix, self.filename
