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offical_test.py
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offical_test.py
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# coding=utf-8
"""
if you get RT result with the type of 6DOF
you can use this function to draw gt img and result img
and also can compute official t_error and r_error
"""
import numpy as np
import sys
from matplotlib import pyplot as plt
import os
class kittiEvalOdom():
# ----------------------------------------------------------------------
# poses: N,4,4
# pose: 4,4
# ----------------------------------------------------------------------
def __init__(self, gt_dir, test_sequences):
self.lengths = [100, 200, 300, 400, 500, 600, 700, 800]
self.num_lengths = len(self.lengths)
self.gt_dir = gt_dir
self.eval_seqs = test_sequences
def loadPoses(self, file_name):
# ----------------------------------------------------------------------
# Each line in the file should follow one of the following structures
# (1) idx pose(3x4 matrix in terms of 12 numbers)
# (2) pose(3x4 matrix in terms of 12 numbers)
# ----------------------------------------------------------------------
f = open(file_name, 'r')
s = f.readlines()
f.close()
file_len = len(s)
poses = {}
for cnt, line in enumerate(s):
P = np.eye(4)
line_split = [float(i) for i in line.split(" ")]
withIdx = int(len(line_split) == 13)
for row in range(3):
for col in range(4):
P[row, col] = line_split[row * 4 + col + withIdx]
if withIdx:
frame_idx = line_split[0]
else:
frame_idx = cnt
poses[frame_idx] = P
return poses
def trajectoryDistances(self, poses):
# ----------------------------------------------------------------------
# poses: dictionary: [frame_idx: pose]
# 这里是为了得到相应帧到初始帧之间的距离 返回一个距离列表
# ----------------------------------------------------------------------
dist = [0]
sort_frame_idx = sorted(poses.keys())
for i in range(len(sort_frame_idx) - 1):
cur_frame_idx = sort_frame_idx[i]
next_frame_idx = sort_frame_idx[i + 1]
P1 = poses[cur_frame_idx]
P2 = poses[next_frame_idx]
dx = P1[0, 3] - P2[0, 3]
dy = P1[1, 3] - P2[1, 3]
dz = P1[2, 3] - P2[2, 3]
dist.append(dist[i] + np.sqrt(dx ** 2 + dy ** 2 + dz ** 2))
return dist
def rotationError(self, pose_error):
a = pose_error[0, 0]
b = pose_error[1, 1]
c = pose_error[2, 2]
d = 0.5 * (a + b + c - 1.0)
return np.arccos(max(min(d, 1.0), -1.0))
def translationError(self, pose_error):
dx = pose_error[0, 3]
dy = pose_error[1, 3]
dz = pose_error[2, 3]
return np.sqrt(dx ** 2 + dy ** 2 + dz ** 2)
def lastFrameFromSegmentLength(self, dist, first_frame, len_):
for i in range(first_frame, len(dist), 1):
if dist[i] > (dist[first_frame] + len_):
return i
return -1
def calcSequenceErrors(self, poses_gt, poses_result):
err = []
dist = self.trajectoryDistances(poses_gt)
self.step_size = 10
for first_frame in range(9, len(poses_gt), self.step_size):
for i in range(self.num_lengths):
len_ = self.lengths[i]
last_frame = self.lastFrameFromSegmentLength(dist, first_frame, len_)
# ----------------------------------------------------------------------
# Continue if sequence not long enough
# ----------------------------------------------------------------------
if last_frame == -1 or not (last_frame in poses_result.keys()) or not (
first_frame in poses_result.keys()):
continue
# ----------------------------------------------------------------------
# compute rotational and translational errors
# ----------------------------------------------------------------------
pose_delta_gt = np.dot(np.linalg.inv(poses_gt[first_frame]), poses_gt[last_frame])
pose_delta_result = np.dot(np.linalg.inv(poses_result[first_frame]), poses_result[last_frame])
pose_error = np.dot(np.linalg.inv(pose_delta_result), pose_delta_gt)
r_err = self.rotationError(pose_error)
t_err = self.translationError(pose_error)
# ----------------------------------------------------------------------
# compute speed
# ----------------------------------------------------------------------
num_frames = last_frame - first_frame + 1.0
speed = len_ / (0.1 * num_frames)
err.append([first_frame, r_err / len_, t_err / len_, len_, speed])
return err
def saveSequenceErrors(self, err, file_name):
fp = open(file_name, 'w')
for i in err:
line_to_write = " ".join([str(j) for j in i])
fp.writelines(line_to_write + "\n")
fp.close()
def computeOverallErr(self, seq_err):
t_err = 0
r_err = 0
seq_len = len(seq_err)
for item in seq_err:
r_err += item[1]
t_err += item[2]
ave_t_err = t_err / seq_len
ave_r_err = r_err / seq_len
return ave_t_err, ave_r_err
def plotPath(self, seq, poses_gt, poses_result):
plot_keys = ["Ground Truth", "Ours"]
fontsize_ = 20
plot_num = -1
poses_dict = {}
poses_dict["Ground Truth"] = poses_gt
poses_dict["Ours"] = poses_result
fig = plt.figure()
ax = plt.gca()
ax.set_aspect('equal')
for key in plot_keys:
pos_xz = []
# for pose in poses_dict[key]:
for frame_idx in sorted(poses_dict[key].keys()):
pose = poses_dict[key][frame_idx]
pos_xz.append([pose[0, 3], pose[2, 3]])
pos_xz = np.asarray(pos_xz)
plt.plot(pos_xz[:, 0], pos_xz[:, 1], label=key)
plt.legend(loc="upper right", prop={'size': fontsize_})
plt.xticks(fontsize=fontsize_)
plt.yticks(fontsize=fontsize_)
plt.xlabel('x (m)', fontsize=fontsize_)
plt.ylabel('z (m)', fontsize=fontsize_)
fig.set_size_inches(10, 10)
png_title = "sequence_{:02}".format(seq)
plt.savefig(self.plot_path_dir + "/" + png_title + ".png", bbox_inches='tight', pad_inches=0)
def eval_sum(self, result_dir, summary_dir, test_index, sequence):
error_dir = result_dir + "/errors"
self.plot_path_dir = result_dir + "/plot_path"
plot_error_dir = result_dir + "/plot_error"
if not os.path.exists(error_dir):
os.makedirs(error_dir)
if not os.path.exists(self.plot_path_dir):
os.makedirs(self.plot_path_dir)
if not os.path.exists(plot_error_dir):
os.makedirs(plot_error_dir)
ave_t_errs = []
ave_r_errs = []
for i in self.eval_seqs:
self.cur_seq = '{:02}'.format(i)
file_name = '{:02}.txt'.format(i)
poses_result = self.loadPoses(result_dir + "/" + file_name)
poses_gt = self.loadPoses(self.gt_dir + "/" + file_name)
self.result_file_name = result_dir + file_name
# ----------------------------------------------------------------------
# compute sequence errors
# ----------------------------------------------------------------------
seq_err = self.calcSequenceErrors(poses_gt, poses_result)
self.saveSequenceErrors(seq_err, error_dir + "/" + file_name)
# ----------------------------------------------------------------------
# compute overall error
# ----------------------------------------------------------------------
ave_t_err, ave_r_err = self.computeOverallErr(seq_err)
print("Sequence: " + str(i))
print("Average translational RMSE (%): ", ave_t_err * 100)
print("Average rotational error (deg/100m): ", ave_r_err / np.pi * 180 * 100)
ave_t_errs.append(ave_t_err)
ave_r_errs.append(ave_r_err)
# ----------------------------------------------------------------------
# Ploting (To-do)
# (1) plot trajectory
# (2) plot per segment error
# ----------------------------------------------------------------------
self.plotPath(i, poses_gt, poses_result)
print("-------------------- For Copying ------------------------------")
with open(summary_dir, 'a') as f:
for i in range(len(ave_t_errs)):
print("{0:.2f}".format(ave_t_errs[i] * 100))
print("{0:.2f}".format(ave_r_errs[i] / np.pi * 180 * 100))
t_value = "{0:.2f}".format(ave_t_errs[i] * 100)
r_value = "{0:.2f}".format(ave_r_errs[i] / np.pi * 180 * 100)
f.write('\n')
f.write('---------------- model{}//sequence{}---------------------------\n'.format(test_index, sequence))
f.write('t_error = {} , r_error = {}\n'.format(t_value, r_value))
f.write('---------------------- end --------------------------------\n'.format(test_index))
print("-------------------- For copying ------------------------------")