def stats_to_latex_table(traj_ref, segments, idx, table):
"""Associate segments of an object trajectory as given by a DATMO system
with the object's reference trajectory
:traj_ref: Reference trajectory
:segments: All the segments of the robot trajectory
:table: Latex table that the statistics get added to
"""
whole = trajectory.merge(segments)
traj_ref, traj_est = sync.associate_trajectories(traj_ref,
whole,
max_diff=0.01)
data = (traj_ref, traj_est)
ape_metric = metrics.APE(metrics.PoseRelation.translation_part)
ape_metric.process_data(data)
ape_statistics = ape_metric.get_all_statistics()
# print(traj_est.get_infos())
table.add_row((
idx + 1,
round(ape_statistics["rmse"], 3),
round(ape_statistics["mean"], 3),
round(ape_statistics["median"], 3),
round(ape_statistics["std"], 3),
round(ape_statistics["min"], 3),
round(ape_statistics["max"], 3),
round(ape_statistics["sse"], 3),
))
table.add_hline
def vx_vys(axarr, color, b, traj_ref, segments, method):
whole = trajectory.merge(segments)
for i, segment in enumerate(segments):
plot.linear_vel(axarr[0:2], segment, '-', color, method, 1,
b.timestamps[0])
tracking.angular_vel(axarr[2], segment, '-', color, method, 1,
b.timestamps[0])
def associate_segments_common_frame(traj, tracks, distance):
"""Associate segments of an object trajectory as given by a DATMO system
with the object's reference trajectory
:traj: Reference trajectory
:tracks: All the tracks that got produced by the DATMO system
:localization: The trajectory of the self-localization
:returns: segments: The tracks that match to the reference trajectory
:returns: traj_ref: The part of the reference trajectory that matches with
tracks
"""
matches = []
for tr in tracks: # Find the best matching tracks to the object trajectory
traj_ref, traj_est = sync.associate_trajectories(traj,
tr,
max_diff=0.1)
# print("calculating APE for track of length", len(tr.timestamps))
data = (traj_ref, traj_est)
ape_metric = metrics.APE(metrics.PoseRelation.translation_part)
ape_metric.process_data(data)
ape_statistics = ape_metric.get_all_statistics()
# print(ape_statistics)
mismatch = ape_statistics['mean']
# print(mismatch)
tuple = [
traj_est, mismatch,
traj_est.get_infos()['t_start (s)'], traj_ref
]
matches.append(tuple)
matches.sort(key=lambda x: x[2])
segments_track = [] #The parts of the trajectory are added to this list
segments_refer = [
] #The parts of the reference trajectory are added to this list
for m in matches:
if m[1] < distance: # if the mismatch is smaller than 1
# print(m[1],distance)
# print(m[0].get_statistics()['v_avg (m/s)'])
segments_track.append(m[0])
segments_refer.append(m[3])
# print(m[0].get_infos()['t_start (s)'],m[0].get_infos()["path length (m)"])
# print(m[0].get_statistics()['v_avg (m/s)'])
if len(segments_track) == 0:
print("No matching segments")
traj_ref = trajectory.merge(segments_refer)
# print(traj_ref.length)
return segments_track, traj_ref
def run(args):
import os
import sys
import numpy as np
import evo.core.lie_algebra as lie
from evo.core import trajectory
from evo.core.trajectory import PoseTrajectory3D
from evo.tools import file_interface, log
from evo.tools.settings import SETTINGS
log.configure_logging(verbose=args.verbose,
silent=args.silent,
debug=args.debug,
local_logfile=args.logfile)
if args.debug:
import pprint
logger.debug(
"main_parser config:\n" +
pprint.pformat({arg: getattr(args, arg)
for arg in vars(args)}) + "\n")
logger.debug(SEP)
trajectories, ref_traj = load_trajectories(args)
if args.merge:
if args.subcommand == "kitti":
die("Can't merge KITTI files.")
if len(trajectories) == 0:
die("No trajectories to merge (excluding --ref).")
trajectories = {
"merged_trajectory": trajectory.merge(trajectories.values())
}
if args.transform_left or args.transform_right:
tf_type = "left" if args.transform_left else "right"
tf_path = args.transform_left \
if args.transform_left else args.transform_right
transform = file_interface.load_transform_json(tf_path)
logger.debug(SEP)
if not lie.is_se3(transform):
logger.warning("Not a valid SE(3) transformation!")
if args.invert_transform:
transform = lie.se3_inverse(transform)
logger.debug("Applying a {}-multiplicative transformation:\n{}".format(
tf_type, transform))
for traj in trajectories.values():
traj.transform(transform,
right_mul=args.transform_right,
propagate=args.propagate_transform)
if args.t_offset:
logger.debug(SEP)
for name, traj in trajectories.items():
if type(traj) is trajectory.PosePath3D:
die("{} doesn't have timestamps - can't add time offset.".
format(name))
logger.info("Adding time offset to {}: {} (s)".format(
name, args.t_offset))
traj.timestamps += args.t_offset
if args.n_to_align != -1 and not (args.align or args.correct_scale):
die("--n_to_align is useless without --align or/and --correct_scale")
if args.sync or args.align or args.correct_scale or args.align_origin:
from evo.core import sync
if not args.ref:
logger.debug(SEP)
die("Can't align or sync without a reference! (--ref) *grunt*")
for name, traj in trajectories.items():
if args.subcommand == "kitti":
ref_traj_tmp = ref_traj
else:
logger.debug(SEP)
ref_traj_tmp, trajectories[name] = sync.associate_trajectories(
ref_traj,
traj,
max_diff=args.t_max_diff,
first_name="reference",
snd_name=name)
if args.align or args.correct_scale:
logger.debug(SEP)
logger.debug("Aligning {} to reference.".format(name))
trajectories[name] = trajectory.align_trajectory(
trajectories[name],
ref_traj_tmp,
correct_scale=args.correct_scale,
correct_only_scale=args.correct_scale and not args.align,
n=args.n_to_align)
if args.align_origin:
logger.debug(SEP)
logger.debug("Aligning {}'s origin to reference.".format(name))
trajectories[name] = trajectory.align_trajectory_origin(
trajectories[name], ref_traj_tmp)
print_compact_name = not args.subcommand == "bag"
for name, traj in trajectories.items():
print_traj_info(name, traj, args.verbose, args.full_check,
print_compact_name)
if args.ref:
print_traj_info(args.ref, ref_traj, args.verbose, args.full_check,
print_compact_name)
if args.plot or args.save_plot or args.serialize_plot:
import numpy as np
from evo.tools import plot
import matplotlib.pyplot as plt
import matplotlib.cm as cm
plot_collection = plot.PlotCollection("evo_traj - trajectory plot")
fig_xyz, axarr_xyz = plt.subplots(3,
sharex="col",
figsize=tuple(SETTINGS.plot_figsize))
fig_rpy, axarr_rpy = plt.subplots(3,
sharex="col",
figsize=tuple(SETTINGS.plot_figsize))
fig_traj = plt.figure(figsize=tuple(SETTINGS.plot_figsize))
plot_mode = plot.PlotMode[args.plot_mode]
ax_traj = plot.prepare_axis(fig_traj, plot_mode)
if args.ref:
short_traj_name = os.path.splitext(os.path.basename(args.ref))[0]
if SETTINGS.plot_usetex:
short_traj_name = short_traj_name.replace("_", "\\_")
plot.traj(ax_traj,
plot_mode,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha)
plot.draw_coordinate_axes(ax_traj, ref_traj, plot_mode,
SETTINGS.plot_axis_marker_scale)
plot.traj_xyz(axarr_xyz,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha)
plot.traj_rpy(axarr_rpy,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha)
if args.ros_map_yaml:
plot.ros_map(ax_traj, args.ros_map_yaml, plot_mode)
cmap_colors = None
if SETTINGS.plot_multi_cmap.lower() != "none":
cmap = getattr(cm, SETTINGS.plot_multi_cmap)
cmap_colors = iter(cmap(np.linspace(0, 1, len(trajectories))))
for name, traj in trajectories.items():
if cmap_colors is None:
color = next(ax_traj._get_lines.prop_cycler)['color']
else:
color = next(cmap_colors)
if print_compact_name:
short_traj_name = os.path.splitext(os.path.basename(name))[0]
else:
short_traj_name = name
if SETTINGS.plot_usetex:
short_traj_name = short_traj_name.replace("_", "\\_")
plot.traj(ax_traj,
plot_mode,
traj,
SETTINGS.plot_trajectory_linestyle,
color,
short_traj_name,
alpha=SETTINGS.plot_trajectory_alpha)
plot.draw_coordinate_axes(ax_traj, traj, plot_mode,
SETTINGS.plot_axis_marker_scale)
if args.ref and isinstance(ref_traj, trajectory.PoseTrajectory3D):
start_time = ref_traj.timestamps[0]
else:
start_time = None
plot.traj_xyz(axarr_xyz,
traj,
SETTINGS.plot_trajectory_linestyle,
color,
short_traj_name,
alpha=SETTINGS.plot_trajectory_alpha,
start_timestamp=start_time)
plot.traj_rpy(axarr_rpy,
traj,
SETTINGS.plot_trajectory_linestyle,
color,
short_traj_name,
alpha=SETTINGS.plot_trajectory_alpha,
start_timestamp=start_time)
if not SETTINGS.plot_usetex:
fig_rpy.text(0.,
0.005,
"euler_angle_sequence: {}".format(
SETTINGS.euler_angle_sequence),
fontsize=6)
plot_collection.add_figure("trajectories", fig_traj)
plot_collection.add_figure("xyz_view", fig_xyz)
plot_collection.add_figure("rpy_view", fig_rpy)
if args.plot:
plot_collection.show()
if args.save_plot:
logger.info(SEP)
plot_collection.export(args.save_plot,
confirm_overwrite=not args.no_warnings)
if args.serialize_plot:
logger.info(SEP)
plot_collection.serialize(args.serialize_plot,
confirm_overwrite=not args.no_warnings)
if args.save_as_tum:
logger.info(SEP)
for name, traj in trajectories.items():
dest = os.path.splitext(os.path.basename(name))[0] + ".tum"
file_interface.write_tum_trajectory_file(
dest, traj, confirm_overwrite=not args.no_warnings)
if args.ref:
dest = os.path.splitext(os.path.basename(args.ref))[0] + ".tum"
file_interface.write_tum_trajectory_file(
dest, ref_traj, confirm_overwrite=not args.no_warnings)
if args.save_as_kitti:
logger.info(SEP)
for name, traj in trajectories.items():
dest = os.path.splitext(os.path.basename(name))[0] + ".kitti"
file_interface.write_kitti_poses_file(
dest, traj, confirm_overwrite=not args.no_warnings)
if args.ref:
dest = os.path.splitext(os.path.basename(args.ref))[0] + ".kitti"
file_interface.write_kitti_poses_file(
dest, ref_traj, confirm_overwrite=not args.no_warnings)
if args.save_as_bag:
import datetime
import rosbag
dest_bag_path = str(
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")) + ".bag"
logger.info(SEP)
logger.info("Saving trajectories to " + dest_bag_path + "...")
bag = rosbag.Bag(dest_bag_path, 'w')
try:
for name, traj in trajectories.items():
dest_topic = os.path.splitext(os.path.basename(name))[0]
frame_id = traj.meta[
"frame_id"] if "frame_id" in traj.meta else ""
file_interface.write_bag_trajectory(bag, traj, dest_topic,
frame_id)
if args.ref:
dest_topic = os.path.splitext(os.path.basename(args.ref))[0]
frame_id = ref_traj.meta[
"frame_id"] if "frame_id" in ref_traj.meta else ""
file_interface.write_bag_trajectory(bag, ref_traj, dest_topic,
frame_id)
finally:
bag.close()
def run(args):
import os
import sys
import numpy as np
import evo.core.lie_algebra as lie
from evo.core import trajectory
from evo.core.trajectory import PoseTrajectory3D
from evo.tools import file_interface, log
from evo.tools.settings import SETTINGS
log.configure_logging(verbose=args.verbose,
silent=args.silent,
debug=args.debug)
if args.debug:
import pprint
logger.debug(
"main_parser config:\n" +
pprint.pformat({arg: getattr(args, arg)
for arg in vars(args)}) + "\n")
logger.debug(SEP)
trajectories, ref_traj = load_trajectories(args)
if args.merge:
if args.subcommand == "kitti":
die("Can't merge KITTI files.")
if len(trajectories) == 0:
die("No trajectories to merge (excluding --ref).")
trajectories = {
"merged_trajectory": trajectory.merge(trajectories.values())
}
if args.transform_left or args.transform_right:
tf_type = "left" if args.transform_left else "right"
tf_path = args.transform_left \
if args.transform_left else args.transform_right
transform = file_interface.load_transform_json(tf_path)
logger.debug(SEP)
if not lie.is_se3(transform):
logger.warning("Not a valid SE(3) transformation!")
if args.invert_transform:
transform = lie.se3_inverse(transform)
logger.debug("Applying a {}-multiplicative transformation:\n{}".format(
tf_type, transform))
for traj in trajectories.values():
traj.transform(transform, right_mul=args.transform_right)
if args.t_offset:
logger.debug(SEP)
for name, traj in trajectories.items():
if type(traj) is trajectory.PosePath3D:
die("{} doesn't have timestamps - can't add time offset.".
format(name))
logger.info("Adding time offset to {}: {} (s)".format(
name, args.t_offset))
traj.timestamps += args.t_offset
if args.sync or args.align or args.correct_scale:
from evo.core import sync
if not args.ref:
logger.debug(SEP)
die("Can't align or sync without a reference! (--ref) *grunt*")
for name, traj in trajectories.items():
if args.subcommand == "kitti":
ref_traj_tmp = ref_traj
else:
logger.debug(SEP)
ref_traj_tmp, trajectories[name] = sync.associate_trajectories(
ref_traj,
traj,
max_diff=args.t_max_diff,
first_name="reference",
snd_name=name)
if args.align or args.correct_scale:
logger.debug(SEP)
logger.debug("Aligning {} to reference.".format(name))
trajectories[name] = trajectory.align_trajectory(
trajectories[name],
ref_traj_tmp,
correct_scale=args.correct_scale,
correct_only_scale=args.correct_scale and not args.align,
n=args.n_to_align)
for name, traj in trajectories.items():
print_traj_info(name, traj, args.verbose, args.full_check)
if args.ref:
print_traj_info(args.ref, ref_traj, args.verbose, args.full_check)
if args.plot or args.save_plot or args.serialize_plot:
from evo.tools.plot import PlotMode
plot_mode = PlotMode.xyz if not args.plot_mode else PlotMode[
args.plot_mode]
import numpy as np
from evo.tools import plot
import matplotlib.pyplot as plt
import matplotlib.cm as cm
plot_collection = plot.PlotCollection("evo_traj - trajectory plot")
fig_xyz, axarr_xyz = plt.subplots(3,
sharex="col",
figsize=tuple(SETTINGS.plot_figsize))
fig_rpy, axarr_rpy = plt.subplots(3,
sharex="col",
figsize=tuple(SETTINGS.plot_figsize))
fig_traj = plt.figure(figsize=tuple(SETTINGS.plot_figsize))
ax_traj = plot.prepare_axis(fig_traj, plot_mode)
pltstart = 0
pltend = traj.num_poses
if args.plotstart:
pltstart = args.plotstart
if args.plotend != -1:
pltend = args.plotend
if args.ref:
short_traj_name = os.path.splitext(os.path.basename(args.ref))[0]
if SETTINGS.plot_usetex:
short_traj_name = short_traj_name.replace("_", "\\_")
plot.traj(ax_traj,
plot_mode,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha,
start=pltstart,
end=pltend)
plot.traj_xyz(axarr_xyz,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha,
start=pltstart,
end=pltend)
plot.traj_rpy(axarr_rpy,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha,
start=pltstart,
end=pltend)
cmap_colors = None
if SETTINGS.plot_multi_cmap.lower() != "none":
cmap = getattr(cm, SETTINGS.plot_multi_cmap)
cmap_colors = iter(cmap(np.linspace(0, 1, len(trajectories))))
fig_3 = plt.figure(figsize=tuple(SETTINGS.plot_figsize))
#plot_mode = plot.PlotMode.xz
ax = plot.prepare_axis(fig_3, plot_mode)
fig_3.axes.append(ax)
for name, traj in trajectories.items():
num = traj.positions_xyz.shape[0]
if pltstart >= num:
print(name, "plotstart > len!", num)
pltstart = 0
if pltend != -1 and (pltend > num or pltend < pltstart):
print(name, "plotend > len!", num)
pltend = traj.num_poses
pltstart = int(pltstart)
pltend = int(pltend)
if cmap_colors is None:
color = next(ax_traj._get_lines.prop_cycler)['color']
else:
color = next(cmap_colors)
short_traj_name = os.path.splitext(os.path.basename(name))[0]
if SETTINGS.plot_usetex:
short_traj_name = short_traj_name.replace("_", "\\_")
plot.traj(ax_traj,
plot_mode,
traj,
'-',
color,
short_traj_name,
start=pltstart,
end=pltend)
if args.ref and isinstance(ref_traj, trajectory.PoseTrajectory3D):
start_time = ref_traj.timestamps[0]
else:
start_time = None
plot.traj_xyz(axarr_xyz,
traj,
'-',
color,
short_traj_name,
start_timestamp=start_time,
start=pltstart,
end=pltend)
plot.traj_rpy(axarr_rpy,
traj,
'-',
color,
short_traj_name,
start_timestamp=start_time,
start=pltstart,
end=pltend)
speeds = [
trajectory.calc_speed(traj.positions_xyz[i],
traj.positions_xyz[i + 1],
traj.timestamps[i],
traj.timestamps[i + 1])
for i in range(pltstart, pltend - 1)
]
speeds.append(0)
#plot.traj(ax, plot_mode, traj, '--', 'gray', 'reference')
plot.traj_colormap(ax,
traj,
speeds,
plot_mode,
min_map=min(speeds),
max_map=max(max(speeds), 10),
title="speed mapped onto trajectory",
start=pltstart,
end=pltend)
plot_collection.add_figure("trajectories", fig_traj)
plot_collection.add_figure("xyz_view", fig_xyz)
plot_collection.add_figure("rpy_view", fig_rpy)
plot_collection.add_figure("traj (speed)", fig_3)
if args.plot:
plot_collection.show()
if args.save_plot:
logger.info(SEP)
plot_collection.export(args.save_plot,
confirm_overwrite=not args.no_warnings)
if args.serialize_plot:
logger.info(SEP)
plot_collection.serialize(args.serialize_plot,
confirm_overwrite=not args.no_warnings)
if args.save_as_tum:
logger.info(SEP)
for name, traj in trajectories.items():
dest = os.path.splitext(os.path.basename(name))[0] + ".tum"
file_interface.write_tum_trajectory_file(
dest, traj, confirm_overwrite=not args.no_warnings)
if args.ref:
dest = os.path.splitext(os.path.basename(args.ref))[0] + ".tum"
file_interface.write_tum_trajectory_file(
dest, ref_traj, confirm_overwrite=not args.no_warnings)
if args.save_as_kitti:
logger.info(SEP)
for name, traj in trajectories.items():
dest = os.path.splitext(os.path.basename(name))[0] + ".kitti"
file_interface.write_kitti_poses_file(
dest, traj, confirm_overwrite=not args.no_warnings)
if args.ref:
dest = os.path.splitext(os.path.basename(args.ref))[0] + ".kitti"
file_interface.write_kitti_poses_file(
dest, ref_traj, confirm_overwrite=not args.no_warnings)
if args.save_as_bag:
import datetime
import rosbag
dest_bag_path = str(
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")) + ".bag"
logger.info(SEP)
logger.info("Saving trajectories to " + dest_bag_path + "...")
bag = rosbag.Bag(dest_bag_path, 'w')
try:
for name, traj in trajectories.items():
dest_topic = os.path.splitext(os.path.basename(name))[0]
frame_id = traj.meta[
"frame_id"] if "frame_id" in traj.meta else ""
file_interface.write_bag_trajectory(bag, traj, dest_topic,
frame_id)
if args.ref:
dest_topic = os.path.splitext(os.path.basename(args.ref))[0]
frame_id = ref_traj.meta[
"frame_id"] if "frame_id" in ref_traj.meta else ""
file_interface.write_bag_trajectory(bag, ref_traj, dest_topic,
frame_id)
finally:
bag.close()
def associate_segments(traj, tracks):
"""Associate segments of an object trajectory as given by a DATMO system
with the object's reference trajectory
:traj: Reference trajectory
:tracks: All the tracks that got produced by the DATMO system
:localization: The trajectory of the self-localization
:returns: segments: The tracks that match to the reference trajectory
:returns: traj_ref: The part of the reference trajectory that matches with
tracks
"""
matches = []
for tr in tracks: # Find the best matching tracks to the object trajectory
traj_ref, traj_est = sync.associate_trajectories(traj,
tr,
max_diff=0.01)
traj_est, rot, tra, _ = trajectory.align_trajectory(
traj_est, traj_ref, correct_scale=False, return_parameters=True)
# print("calculating APE for track of length", len(tr.timestamps))
data = (traj_ref, traj_est)
ape_metric = metrics.APE(metrics.PoseRelation.translation_part)
ape_metric.process_data(data)
ape_statistics = ape_metric.get_all_statistics()
tra_dif = (tra - loc_tra)
# print(tra)
abs_tra_dif = abs((tra - loc_tra)[0]) + abs((tra - loc_tra)[1])
translation = abs(tra[0]) + abs(tra[1])
rot_dif = (rot - loc_rot)
abs_rot_dif = 0
for i in range(0, len(rot_dif)): abs_rot_dif += abs(rot_dif[i][0])+ abs(rot_dif[i][1]) +\
abs(rot_dif[i][2])
# print(abs_tra_dif,abs_rot_dif)
mismatch = abs_tra_dif + abs_rot_dif
tuple = [traj_est, mismatch, traj_est.get_infos()['t_start (s)']]
matches.append(tuple)
matches.sort(key=lambda x: x[2])
segments = [] #The parts of the trajectory are added to this list
for m in matches:
# print(m[1])
if m[1] < 0.1: # if the mismatch is smaller than 1
# print(m[0].get_statistics()['v_avg (m/s)'])
segments.append(m[0])
# print(m[0].get_infos()['t_start (s)'],m[0].get_infos()["path length (m)"])
# print(m[0].get_statistics()['v_avg (m/s)'])
if len(segments) == 0:
print("No matching segments")
whole = trajectory.merge(segments)
traj_ref, traj_est = sync.associate_trajectories(traj,
whole,
max_diff=0.01)
traj_est, rot, tra, _ = trajectory.align_trajectory(traj_est,
traj_ref,
correct_scale=False,
return_parameters=True)
# print(traj_est.get_infos())
return segments, traj_ref, translation
def run(args):
import sys
import numpy as np
import evo.core.lie_algebra as lie
from evo.core import trajectory
from evo.core.trajectory import PoseTrajectory3D
from evo.tools import file_interface, log
log.configure_logging(verbose=args.verbose,
silent=args.silent,
debug=args.debug,
local_logfile=args.logfile)
if args.debug:
import pprint
logger.debug(
"main_parser config:\n" +
pprint.pformat({arg: getattr(args, arg)
for arg in vars(args)}) + "\n")
logger.debug(SEP)
trajectories, ref_traj = load_trajectories(args)
if args.merge:
if args.subcommand == "kitti":
die("Can't merge KITTI files.")
if len(trajectories) == 0:
die("No trajectories to merge (excluding --ref).")
trajectories = {
"merged_trajectory": trajectory.merge(trajectories.values())
}
if args.t_offset:
logger.debug(SEP)
for name, traj in trajectories.items():
if type(traj) is trajectory.PosePath3D:
die("{} doesn't have timestamps - can't add time offset.".
format(name))
logger.info("Adding time offset to {}: {} (s)".format(
name, args.t_offset))
traj.timestamps += args.t_offset
if args.n_to_align != -1 and not (args.align or args.correct_scale):
die("--n_to_align is useless without --align or/and --correct_scale")
# TODO: this is fugly, but is a quick solution for remembering each synced
# reference when plotting pose correspondences later...
synced = (args.subcommand == "kitti" and ref_traj) or any(
(args.sync, args.align, args.correct_scale, args.align_origin))
synced_refs = {}
if synced:
from evo.core import sync
if not args.ref:
logger.debug(SEP)
die("Can't align or sync without a reference! (--ref) *grunt*")
for name, traj in trajectories.items():
if args.subcommand == "kitti":
ref_traj_tmp = ref_traj
else:
logger.debug(SEP)
ref_traj_tmp, trajectories[name] = sync.associate_trajectories(
ref_traj,
traj,
max_diff=args.t_max_diff,
first_name="reference",
snd_name=name)
if args.align or args.correct_scale:
logger.debug(SEP)
logger.debug("Aligning {} to reference.".format(name))
trajectories[name].align(ref_traj_tmp,
correct_scale=args.correct_scale,
correct_only_scale=args.correct_scale
and not args.align,
n=args.n_to_align)
if args.align_origin:
logger.debug(SEP)
logger.debug("Aligning {}'s origin to reference.".format(name))
trajectories[name].align_origin(ref_traj_tmp)
if SETTINGS.plot_pose_correspondences:
synced_refs[name] = ref_traj_tmp
if args.transform_left or args.transform_right:
tf_type = "left" if args.transform_left else "right"
tf_path = args.transform_left \
if args.transform_left else args.transform_right
transform = file_interface.load_transform_json(tf_path)
logger.debug(SEP)
if not lie.is_se3(transform):
logger.warning("Not a valid SE(3) transformation!")
if args.invert_transform:
transform = lie.se3_inverse(transform)
logger.debug("Applying a {}-multiplicative transformation:\n{}".format(
tf_type, transform))
for traj in trajectories.values():
traj.transform(transform,
right_mul=args.transform_right,
propagate=args.propagate_transform)
for name, traj in trajectories.items():
print_traj_info(to_compact_name(name, args), traj, args.verbose,
args.full_check)
if args.ref:
print_traj_info(to_compact_name(args.ref, args), ref_traj,
args.verbose, args.full_check)
if args.plot or args.save_plot or args.serialize_plot:
import numpy as np
from evo.tools import plot
import matplotlib.pyplot as plt
import matplotlib.cm as cm
plot_collection = plot.PlotCollection("evo_traj - trajectory plot")
fig_xyz, axarr_xyz = plt.subplots(3,
sharex="col",
figsize=tuple(SETTINGS.plot_figsize))
fig_rpy, axarr_rpy = plt.subplots(3,
sharex="col",
figsize=tuple(SETTINGS.plot_figsize))
fig_traj = plt.figure(figsize=tuple(SETTINGS.plot_figsize))
plot_mode = plot.PlotMode[args.plot_mode]
ax_traj = plot.prepare_axis(fig_traj, plot_mode)
# for x-axis alignment starting from 0 with --plot_relative_time
start_time = None
if args.ref:
if isinstance(ref_traj, trajectory.PoseTrajectory3D) \
and args.plot_relative_time:
start_time = ref_traj.timestamps[0]
short_traj_name = to_compact_name(args.ref, args,
SETTINGS.plot_usetex)
plot.traj(ax_traj,
plot_mode,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha)
plot.draw_coordinate_axes(
ax_traj, ref_traj, plot_mode,
SETTINGS.plot_reference_axis_marker_scale)
plot.traj_xyz(axarr_xyz,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha,
start_timestamp=start_time)
plot.traj_rpy(axarr_rpy,
ref_traj,
style=SETTINGS.plot_reference_linestyle,
color=SETTINGS.plot_reference_color,
label=short_traj_name,
alpha=SETTINGS.plot_reference_alpha,
start_timestamp=start_time)
if args.ros_map_yaml:
plot.ros_map(ax_traj, args.ros_map_yaml, plot_mode)
cmap_colors = None
if SETTINGS.plot_multi_cmap.lower() != "none":
cmap = getattr(cm, SETTINGS.plot_multi_cmap)
cmap_colors = iter(cmap(np.linspace(0, 1, len(trajectories))))
for name, traj in trajectories.items():
if cmap_colors is None:
color = next(ax_traj._get_lines.prop_cycler)['color']
else:
color = next(cmap_colors)
short_traj_name = to_compact_name(name, args, SETTINGS.plot_usetex)
plot.traj(ax_traj,
plot_mode,
traj,
SETTINGS.plot_trajectory_linestyle,
color,
short_traj_name,
alpha=SETTINGS.plot_trajectory_alpha)
plot.draw_coordinate_axes(ax_traj, traj, plot_mode,
SETTINGS.plot_axis_marker_scale)
if ref_traj and synced and SETTINGS.plot_pose_correspondences:
plot.draw_correspondence_edges(
ax_traj,
traj,
synced_refs[name],
plot_mode,
color=color,
style=SETTINGS.plot_pose_correspondences_linestyle,
alpha=SETTINGS.plot_trajectory_alpha)
plot.traj_xyz(axarr_xyz,
traj,
SETTINGS.plot_trajectory_linestyle,
color,
short_traj_name,
alpha=SETTINGS.plot_trajectory_alpha,
start_timestamp=start_time)
plot.traj_rpy(axarr_rpy,
traj,
SETTINGS.plot_trajectory_linestyle,
color,
short_traj_name,
alpha=SETTINGS.plot_trajectory_alpha,
start_timestamp=start_time)
if not SETTINGS.plot_usetex:
fig_rpy.text(0.,
0.005,
"euler_angle_sequence: {}".format(
SETTINGS.euler_angle_sequence),
fontsize=6)
plot_collection.add_figure("trajectories", fig_traj)
plot_collection.add_figure("xyz_view", fig_xyz)
plot_collection.add_figure("rpy_view", fig_rpy)
if args.plot:
plot_collection.show()
if args.save_plot:
logger.info(SEP)
plot_collection.export(args.save_plot,
confirm_overwrite=not args.no_warnings)
if args.serialize_plot:
logger.info(SEP)
plot_collection.serialize(args.serialize_plot,
confirm_overwrite=not args.no_warnings)
if args.save_as_tum:
logger.info(SEP)
for name, traj in trajectories.items():
dest = to_filestem(name, args) + ".tum"
file_interface.write_tum_trajectory_file(
dest, traj, confirm_overwrite=not args.no_warnings)
if args.ref:
dest = to_filestem(args.ref, args) + ".tum"
file_interface.write_tum_trajectory_file(
dest, ref_traj, confirm_overwrite=not args.no_warnings)
if args.save_as_kitti:
logger.info(SEP)
for name, traj in trajectories.items():
dest = to_filestem(name, args) + ".kitti"
file_interface.write_kitti_poses_file(
dest, traj, confirm_overwrite=not args.no_warnings)
if args.ref:
dest = to_filestem(args.ref, args) + ".kitti"
file_interface.write_kitti_poses_file(
dest, ref_traj, confirm_overwrite=not args.no_warnings)
if args.save_as_bag or args.save_as_bag2:
from rosbags.rosbag1 import Writer as Rosbag1Writer
from rosbags.rosbag2 import Writer as Rosbag2Writer
writers = []
if args.save_as_bag:
dest_bag_path = str(
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")) + ".bag"
writers.append(Rosbag1Writer(dest_bag_path))
if args.save_as_bag2:
dest_bag_path = str(
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S"))
writers.append(Rosbag2Writer(dest_bag_path))
for writer in writers:
logger.info(SEP)
logger.info("Saving trajectories to " + str(writer.path) + "...")
try:
writer.open()
for name, traj in trajectories.items():
dest_topic = to_topic_name(name, args)
frame_id = traj.meta[
"frame_id"] if "frame_id" in traj.meta else ""
file_interface.write_bag_trajectory(
writer, traj, dest_topic, frame_id)
if args.ref:
dest_topic = to_topic_name(args.ref, args)
frame_id = ref_traj.meta[
"frame_id"] if "frame_id" in ref_traj.meta else ""
file_interface.write_bag_trajectory(
writer, ref_traj, dest_topic, frame_id)
finally:
writer.close()
if args.save_table:
from evo.tools import pandas_bridge
logger.debug(SEP)
df = pandas_bridge.trajectories_stats_to_df(trajectories)
pandas_bridge.save_df_as_table(df,
args.save_table,
confirm_overwrite=not args.no_warnings)
