def run(config):
print("refine rough registration of fragments.")
o3d.utility.set_verbosity_level(o3d.utility.VerbosityLevel.Debug)
ply_file_names = get_file_list(
join(config["path_dataset"], config["folder_fragment"]), ".ply")
make_posegraph_for_refined_scene(ply_file_names, config)
optimize_posegraph_for_refined_scene(config["path_dataset"], config)
path_dataset = config['path_dataset']
n_fragments = len(ply_file_names)
# Save to trajectory
poses = []
pose_graph_fragment = o3d.io.read_pose_graph(
join(path_dataset, config["template_refined_posegraph_optimized"]))
for fragment_id in range(len(pose_graph_fragment.nodes)):
pose_graph_rgbd = o3d.io.read_pose_graph(
join(path_dataset,
config["template_fragment_posegraph_optimized"] % fragment_id))
for frame_id in range(len(pose_graph_rgbd.nodes)):
frame_id_abs = fragment_id * \
config['n_frames_per_fragment'] + frame_id
pose = np.dot(pose_graph_fragment.nodes[fragment_id].pose,
pose_graph_rgbd.nodes[frame_id].pose)
poses.append(pose)
traj_name = join(path_dataset, config["template_global_traj"])
write_poses_to_log(traj_name, poses)
def run(config):
print("refine rough registration of fragments.")
o3d.utility.set_verbosity_level(o3d.utility.VerbosityLevel.Debug)
ply_file_names = get_file_list(
join(config["path_dataset"], config["folder_fragment"]), ".ply")
make_posegraph_for_refined_scene(ply_file_names, config)
optimize_posegraph_for_refined_scene(config["path_dataset"], config)
json_response = None
try:
json_response = raw_response.json()
except Exception as e:
print("file [%s] error: " % file_name, e)
if (json_response["success"]):
return json_response["result"]
else:
print("file [%s] failed, message: %s, request_id: %s: " % (file_name, json_response["message"]["global"], json_response["request_id"]))
if __name__ == "__main__":
executor = concurrent.futures.ThreadPoolExecutor(max_workers=50)
file_list = file.get_file_list(data_dir)
# list conprehension
futures = {executor.submit(send_request, data_dir + "/" + file_name): file_name for file_name in file_list}
for future in concurrent.futures.as_completed(futures):
file_name = futures[future]
try:
data = future.result()
except Exception as exc:
print('%r generated an exception: %s' % (file_name, exc))
else:
with open(file_name + ".feature", "w") as f:
f.write(str(data["feature"])[1: -1])
f.close
def run(config):
print("slac non-rigid optimisation.")
o3d.utility.set_verbosity_level(o3d.utility.VerbosityLevel.Debug)
path_dataset = config['path_dataset']
ply_file_names = get_file_list(
join(config["path_dataset"], config["folder_fragment"]), ".ply")
if (len(ply_file_names) == 0):
raise RuntimeError(
"No fragment found in {}, please make sure the reconstruction_system has finished running on the dataset."
.format(join(config["path_dataset"], config["folder_fragment"])))
pose_graph_fragment = o3d.io.read_pose_graph(
join(path_dataset, config["template_refined_posegraph_optimized"]))
# SLAC optimizer parameters.
slac_params = o3d.t.pipelines.slac.slac_optimizer_params(
max_iterations=config["max_iterations"],
voxel_size=config["voxel_size"],
distance_threshold=config["distance_threshold"],
fitness_threshold=config["fitness_threshold"],
regularizer_weight=config["regularizer_weight"],
device=o3d.core.Device(str(config["device"])),
slac_folder=path_dataset + config["folder_slac"])
# SLAC debug option.
debug_option = o3d.t.pipelines.slac.slac_debug_option(False, 0)
# Run the system.
pose_graph_updated = o3d.pipelines.registration.PoseGraph()
# rigid optimization method.
if (config["method"] == "rigid"):
pose_graph_updated = o3d.t.pipelines.slac.run_rigid_optimizer_for_fragments(
ply_file_names, pose_graph_fragment, slac_params, debug_option)
elif (config["method"] == "slac"):
pose_graph_updated, ctrl_grid = o3d.t.pipelines.slac.run_slac_optimizer_for_fragments(
ply_file_names, pose_graph_fragment, slac_params, debug_option)
hashmap = ctrl_grid.get_hashmap()
active_buf_indices = hashmap.get_active_buf_indices().to(
o3d.core.Dtype.Int64)
key_tensor = hashmap.get_key_tensor()[active_buf_indices]
key_tensor.save(
join(slac_params.get_subfolder_name(), "ctr_grid_keys.npy"))
value_tensor = hashmap.get_value_tensor()[active_buf_indices]
value_tensor.save(
join(slac_params.get_subfolder_name(), "ctr_grid_values.npy"))
else:
raise RuntimeError(
"Requested optimization method {}, is not implemented. Implemented methods includes slac and rigid."
.format(config["method"]))
# Write updated pose graph.
o3d.io.write_pose_graph(
join(slac_params.get_subfolder_name(),
config["template_optimized_posegraph_slac"]), pose_graph_updated)
# Write trajectory for slac-integrate stage.
fragment_folder = join(path_dataset, config["folder_fragment"])
params = []
for i in range(len(pose_graph_updated.nodes)):
fragment_pose_graph = o3d.io.read_pose_graph(
join(fragment_folder, "fragment_optimized_%03d.json" % i))
for node in fragment_pose_graph.nodes:
pose = np.dot(pose_graph_updated.nodes[i].pose, node.pose)
param = o3d.camera.PinholeCameraParameters()
param.extrinsic = np.linalg.inv(pose)
params.append(param)
trajectory = o3d.camera.PinholeCameraTrajectory()
trajectory.parameters = params
o3d.io.write_pinhole_camera_trajectory(
slac_params.get_subfolder_name() + "/optimized_trajectory_" +
str(config["method"]) + ".log", trajectory)
