def import_points_from_pcd_file(filename, name_prefix="", select_ob=True):
"""
Import 3D coordinates of vertices from a PointCloud (.pcd) file.
"name_prefix" : see documentation of "object_name_from_filename()"
"select_ob" : select the imported pointcloud object
Note: currently, colors are not yet supported.
"""
# Import point cloud
verts, colors, found_alpha = dataset_tools.load_3D_points_from_pcd_file(
filename, use_alpha=True)
ob, is_new_ob = create_mesh(
object_name_from_filename(filename, name_prefix), verts)
# Mark object as a pointcloud
ob["is_pointcloud"] = True
# Mark object as a colored pointcloud, if applicable
ob["pointcloud_has_rgba"] = (colors != None)
if ob["pointcloud_has_rgba"]:
if is_new_ob: # only change transparency in this case
ob.show_transparent = found_alpha # render alpha channel
# Open mesh for editing vertex custom data
bm = bmesh.new()
bm.from_mesh(ob.data)
# Create custom data layers, for the vertex color
r = bm.verts.layers.float.new('r')
g = bm.verts.layers.float.new('g')
b = bm.verts.layers.float.new('b')
a = bm.verts.layers.float.new('a')
# Color vertices
for vert, color in zip(bm.verts, colors / 255.):
vert[b], vert[g], vert[r] = color[0:3]
vert[a] = color[3]
# Save colors
bm.to_mesh(ob.data)
del bm
if select_ob:
# Select the generated object
if bpy.context.mode != "OBJECT":
bpy.ops.object.mode_set() # switch to object mode
bpy.ops.object.select_all(action="DESELECT")
ob.select = True
bpy.context.scene.objects.active = ob
def scene_3D_points(r=1.0, filename="scene_3D_points.pcd"):
"""
Load 3D coordinates of points from a PointCloud .pcd-file given by filename "filename".
Use "r" as geometry scaling factor.
The points are assumed to be confined in a cube with edges of length 2.
"""
points = dataset_tools.load_3D_points_from_pcd_file(filename)[0] # only load verts, not colors
points *= r
points = np.concatenate((points, np.ones((len(points), 1))), axis=1) # to homogeneous coordinates
return points
def scene_3D_points(r=1., filename="scene_3D_points.pcd"):
"""
Load 3D coordinates of points from a PointCloud .pcd-file given by filename "filename".
Use "r" as geometry scaling factor.
The points are assumed to be confined in a cube with edges of length 2.
"""
points = dataset_tools.load_3D_points_from_pcd_file(filename)[0] # only load verts, not colors
points *= r
points = np.concatenate((points, np.ones((len(points), 1))), axis=1) # to homogeneous coordinates
return points
def import_points_from_pcd_file(filename, name_prefix="", select_ob=True):
"""
Import 3D coordinates of vertices from a PointCloud (.pcd) file.
"name_prefix" : see documentation of "object_name_from_filename()"
"select_ob" : select the imported pointcloud object
Note: currently, colors are not yet supported.
"""
# Import point cloud
verts, colors, found_alpha = dataset_tools.load_3D_points_from_pcd_file(filename, use_alpha=True)
ob, is_new_ob = create_mesh(object_name_from_filename(filename, name_prefix), verts)
# Mark object as a pointcloud
ob["is_pointcloud"] = True
# Mark object as a colored pointcloud, if applicable
ob["pointcloud_has_rgba"] = (colors != None)
if ob["pointcloud_has_rgba"]:
if is_new_ob: # only change transparency in this case
ob.show_transparent = found_alpha # render alpha channel
# Open mesh for editing vertex custom data
bm = bmesh.new()
bm.from_mesh(ob.data)
# Create custom data layers, for the vertex color
r = bm.verts.layers.float.new('r')
g = bm.verts.layers.float.new('g')
b = bm.verts.layers.float.new('b')
a = bm.verts.layers.float.new('a')
# Color vertices
for vert, color in zip(bm.verts, colors / 255.):
vert[b], vert[g], vert[r] = color[0:3]
vert[a] = color[3]
# Save colors
bm.to_mesh(ob.data)
del bm
if select_ob:
# Select the generated object
if bpy.context.mode != "OBJECT": bpy.ops.object.mode_set() # switch to object mode
bpy.ops.object.select_all(action="DESELECT")
ob.select = True
bpy.context.scene.objects.active = ob
def main():
traj_to_file, traj_from_file, traj_input_files, map_input_files, at_frame, offset_time = parse_cmd_args(
)
print("Calculating transformation...")
cam_trajectory_from = dataset_tools.load_cam_trajectory_TUM(traj_from_file)
cam_trajectory_to = dataset_tools.load_cam_trajectory_TUM(traj_to_file)
transformation = dataset_tools.transform_between_cam_trajectories(
cam_trajectory_from,
cam_trajectory_to,
at_frame=at_frame,
offset_time=offset_time)
print("Results:")
delta_quaternion, delta_scale, delta_location = transformation
print("delta_quaternion:")
print("\t %s" % delta_quaternion)
print("delta_scale:")
print("\t %s" % delta_scale)
print("delta_location:")
print("\t %s" % delta_location)
print()
for traj_input_file in traj_input_files:
print('Transforming traj "%s"...' % traj_input_file)
dataset_tools.save_cam_trajectory_TUM(
"%s-trfm%s" % tuple(os.path.splitext(traj_input_file)),
dataset_tools.transformed_cam_trajectory(
dataset_tools.load_cam_trajectory_TUM(traj_input_file),
transformation))
for map_input_file in map_input_files:
print('Transforming map "%s"...' % map_input_file)
points, colors, _ = dataset_tools.load_3D_points_from_pcd_file(
map_input_file, use_alpha=True)
dataset_tools.save_3D_points_to_pcd_file(
"%s-trfm%s" % tuple(os.path.splitext(map_input_file)),
dataset_tools.transformed_points(points, transformation), colors)
print("Done.")
def main():
traj_to_file, traj_from_file, traj_input_files, map_input_files, at_frame, offset_time = parse_cmd_args()
print "Calculating transformation..."
cam_trajectory_from = dataset_tools.load_cam_trajectory_TUM(traj_from_file)
cam_trajectory_to = dataset_tools.load_cam_trajectory_TUM(traj_to_file)
transformation = dataset_tools.transform_between_cam_trajectories(
cam_trajectory_from, cam_trajectory_to, at_frame=at_frame, offset_time=offset_time )
print "Results:"
delta_quaternion, delta_scale, delta_location = transformation
print "delta_quaternion:"
print "\t %s" % delta_quaternion
print "delta_scale:"
print "\t %s" % delta_scale
print "delta_location:"
print "\t %s" % delta_location
print
for traj_input_file in traj_input_files:
print 'Transforming traj "%s"...' % traj_input_file
dataset_tools.save_cam_trajectory_TUM(
"%s-trfm%s" % tuple(os.path.splitext(traj_input_file)),
dataset_tools.transformed_cam_trajectory(
dataset_tools.load_cam_trajectory_TUM(traj_input_file),
transformation ) )
for map_input_file in map_input_files:
print 'Transforming map "%s"...' % map_input_file
points, colors, _ = dataset_tools.load_3D_points_from_pcd_file(map_input_file, use_alpha=True)
dataset_tools.save_3D_points_to_pcd_file(
"%s-trfm%s" % tuple(os.path.splitext(map_input_file)),
dataset_tools.transformed_points(points, transformation),
colors )
print "Done."
