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update task error

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lorenzo 2019-07-25 12:11:15 +02:00
parent 46066cf7bc
commit 8d76e04283
2 changed files with 26 additions and 71 deletions
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4
monoloco/run.py
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@ -96,8 +96,8 @@ def cli():
def main(): def main():
args = cli() args = cli()
from .visuals.paper import gmm from .visuals.paper import paper
gmm() paper()
if args.command == 'predict': if args.command == 'predict':
if args.webcam: if args.webcam:
from .visuals.webcam import webcam from .visuals.webcam import webcam

93
monoloco/visuals/paper.py
View File

@ -1,65 +1,23 @@
# pylint: skip-file
import math import math
import os
import itertools import itertools
import numpy as np import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse from matplotlib.patches import Ellipse
from .printer import get_angle
def paper(): def paper():
"""Print paper figures""" """Print paper figures"""
method = True method = False
task_error = True task_error = True
# Pull figure # Pull figure
if method: if method:
fig_name = 'output_method.png'
z_max = 5
x_max = z_max * 25 / 30
z_1 = 2
z_2 = 4
x_1 = 1
x_2 = -2
std_1 = 0.75 std_1 = 0.75
std_2 = 1.5
angle_1 = get_angle(x_1, z_1)
angle_2 = get_angle(x_2, z_2)
(x_1_down, x_1_up), (z_1_down, z_1_up) = get_confidence(x_1, z_1, std_1)
(x_2_down, x_2_up), (z_2_down, z_2_up) = get_confidence(x_2, z_2, std_2)
#
# fig = plt.figure(0)
# ax = fig.add_subplot(1, 1, 1)
#
# ell_1 = Ellipse((x_1, z_1), width=std_1 * 2, height=0.3, angle=angle_1, color='b', fill=False)
#
# ell_2 = Ellipse((x_2, z_2), width=std_2 * 2, height=0.3, angle=angle_2, color='b', fill=False)
#
# ax.add_patch(ell_1)
# ax.add_patch(ell_2)
# plt.plot(x_1_down, z_1_down, marker='o', markersize=8, color='salmon')
# plt.plot(x_1, z_1, 'go', markersize=8)
# plt.plot(x_1_up, z_1_up, 'o', markersize=8, color='cornflowerblue')
#
# plt.plot(x_2_down, z_2_down, marker='o', markersize=8, color='salmon')
# plt.plot(x_2, z_2, 'go', markersize=8)
# plt.plot(x_2_up, z_2_up, 'bo', markersize=8, color='cornflowerblue')
#
# plt.plot([0, x_max], [0, z_max], 'k--')
# plt.plot([0, -x_max], [0, z_max], 'k--')
# plt.xticks([])
# plt.yticks([])
# plt.xlabel('X [m]')
# plt.ylabel('Z [m]')
# plt.show()
# plt.close()
fig = plt.figure(1) fig = plt.figure(1)
ax = fig.add_subplot(1, 1, 1) ax = fig.add_subplot(1, 1, 1)
@ -77,41 +35,37 @@ def paper():
plt.yticks([]) plt.yticks([])
plt.xlabel('X [m]') plt.xlabel('X [m]')
plt.ylabel('Z [m]') plt.ylabel('Z [m]')
# plt.savefig(os.path.join('docs', fig_name)) plt.savefig(os.path.join('docs', 'output_method.png'))
plt.show()
plt.close()
# Task error figure # Task error figure
if task_error: if task_error:
plt.figure(2) plt.figure(2)
fig_name = 'task_error.png'
xx = np.linspace(0, 40, 100) xx = np.linspace(0, 40, 100)
mm_male = 7 / 178 mu_men = 178
mm_female = 7 / 165 mu_women = 165
mm_young_male = mm_male + (178-164) / 178 mu_child_m = 164
mm_young_female = mm_female + (165-156) / 165 mu_child_w = 156
mm_gender = gmm() mm_gmm, mm_male, mm_female = gmm()
mm_young_male = mm_male + (mu_men - mu_child_m) / mu_men
mm_young_female = mm_female + (mu_women - mu_child_w) / mu_women
yy_male = target_error(xx, mm_male) yy_male = target_error(xx, mm_male)
yy_female = target_error(xx, mm_female) yy_female = target_error(xx, mm_female)
yy_young_male = target_error(xx, mm_young_male) yy_young_male = target_error(xx, mm_young_male)
yy_young_female = target_error(xx, mm_young_female) yy_young_female = target_error(xx, mm_young_female)
yy_gender = target_error(xx, mm_gender) yy_gender = target_error(xx, mm_gmm)
yy_gps = np.linspace(5., 5., xx.shape[0]) yy_gps = np.linspace(5., 5., xx.shape[0])
plt.grid(linewidth=0.3) plt.grid(linewidth=0.3)
plt.plot(xx, yy_gps, color='y', label='GPS') plt.plot(xx, yy_gps, color='y', label='GPS')
plt.plot(xx, yy_young_male, linestyle='dotted',linewidth=2.1, color='b', label='Adult/young male') plt.plot(xx, yy_young_male, linestyle='dotted', linewidth=2.1, color='b', label='Adult/young male')
plt.plot(xx, yy_young_female, linestyle='dotted',linewidth=2.1, color='darkorange', label='Adult/young female') plt.plot(xx, yy_young_female, linestyle='dotted', linewidth=2.1, color='darkorange', label='Adult/young female')
plt.plot(xx, yy_gender, '--', color='lightgreen', linewidth=2.8, label='Generic adult (task error)') plt.plot(xx, yy_gender, '--', color='lightgreen', linewidth=2.8, label='Generic adult (task error)')
plt.plot(xx, yy_female, '-.', linewidth=1.7, color='darkorange', label='Adult female') plt.plot(xx, yy_female, '-.', linewidth=1.7, color='darkorange', label='Adult female')
plt.plot(xx, yy_male, '-.', linewidth=1.7, color='b', label='Adult male') plt.plot(xx, yy_male, '-.', linewidth=1.7, color='b', label='Adult male')
plt.xlim(np.min(xx), np.max(xx)) plt.xlim(np.min(xx), np.max(xx))
plt.xlabel("Distance from the camera [m]") plt.xlabel("Distance from the camera [m]")
plt.ylabel("Localization error due to human height variation [m]") plt.ylabel("Localization error due to human height variation [m]")
plt.legend(loc=(0.01, 0.55)) # Location from 0 to 1 from lower left plt.legend(loc=(0.01, 0.55)) # Location from 0 to 1 from lower left
# plt.savefig(os.path.join(dir_out, fig_name)) plt.savefig(os.path.join('docs', 'task_error.png'))
plt.show()
plt.close()
def target_error(xx, mm): def target_error(xx, mm):
@ -119,16 +73,17 @@ def target_error(xx, mm):
def gmm(): def gmm():
dist_gmm, dist_men, dist_women = height_distributions() dist_gmm, dist_male, dist_female = height_distributions()
mu_gmm = np.mean(dist_gmm) mu_gmm = np.mean(dist_gmm)
mm_gmm = np.mean(np.abs(1 - mu_gmm / dist_gmm)) mm_gmm = np.mean(np.abs(1 - mu_gmm / dist_gmm))
mm_men = np.mean(np.abs(1 - np.mean(dist_men) / dist_men)) mm_male = np.mean(np.abs(1 - np.mean(dist_male) / dist_male))
mm_women = np.mean(np.abs(1 - np.mean(dist_women) / dist_women)) mm_female = np.mean(np.abs(1 - np.mean(dist_female) / dist_female))
print("Mean of GMM distribution: {:.4f}".format(mu_gmm)) print("Mean of GMM distribution: {:.4f}".format(mu_gmm))
print("coefficient for gmm: {:.4f}".format(mm_gmm)) print("coefficient for gmm: {:.4f}".format(mm_gmm))
print("coefficient for men: {:.4f}".format(mm_men)) print("coefficient for men: {:.4f}".format(mm_male))
print("coefficient for women: {:.4f}".format(mm_women)) print("coefficient for women: {:.4f}".format(mm_female))
return mm_gmm, mm_male, mm_female
def get_confidence(xx, zz, std): def get_confidence(xx, zz, std):
@ -146,8 +101,9 @@ def height_distributions():
std_men = 7 std_men = 7
mu_women = 165 mu_women = 165
std_women = 7 std_women = 7
dist_men = np.random.normal(mu_men, std_men, 10000000) dist_men = np.random.normal(mu_men, std_men, int(1e7))
dist_women = np.random.normal(mu_women, std_women, 10000000) dist_women = np.random.normal(mu_women, std_women, int(1e7))
dist_gmm = np.concatenate((dist_men, dist_women)) dist_gmm = np.concatenate((dist_men, dist_women))
return dist_gmm, dist_men, dist_women return dist_gmm, dist_men, dist_women
@ -187,4 +143,3 @@ def get_percentile(dist_gmm):
mu_d = np.mean(dist_d) mu_d = np.mean(dist_d)
mm_bi = (mu_d - perc_d) / mu_d mm_bi = (mu_d - perc_d) / mu_d
mad_d = np.mean(np.abs(dist_d - mu_d)) mad_d = np.mean(np.abs(dist_d - mu_d))