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update task error

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This commit is contained in:
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():
args = cli()
from .visuals.paper import gmm
gmm()
from .visuals.paper import paper
paper()
if args.command == 'predict':
if args.webcam:
from .visuals.webcam import webcam

93
monoloco/visuals/paper.py
View File

@ -1,65 +1,23 @@
# pylint: skip-file
import math
import os
import itertools
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
from .printer import get_angle
def paper():
"""Print paper figures"""
method = True
method = False
task_error = True
# Pull figure
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_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)
ax = fig.add_subplot(1, 1, 1)
@ -77,41 +35,37 @@ def paper():
plt.yticks([])
plt.xlabel('X [m]')
plt.ylabel('Z [m]')
# plt.savefig(os.path.join('docs', fig_name))
plt.show()
plt.close()
plt.savefig(os.path.join('docs', 'output_method.png'))
# Task error figure
if task_error:
plt.figure(2)
fig_name = 'task_error.png'
xx = np.linspace(0, 40, 100)
mm_male = 7 / 178
mm_female = 7 / 165
mm_young_male = mm_male + (178-164) / 178
mm_young_female = mm_female + (165-156) / 165
mm_gender = gmm()
mu_men = 178
mu_women = 165
mu_child_m = 164
mu_child_w = 156
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_female = target_error(xx, mm_female)
yy_young_male = target_error(xx, mm_young_male)
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])
plt.grid(linewidth=0.3)
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_female, linestyle='dotted',linewidth=2.1, color='darkorange', label='Adult/young female')
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_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_male, '-.', linewidth=1.7, color='b', label='Adult male')
plt.xlim(np.min(xx), np.max(xx))
plt.xlabel("Distance from the camera [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.savefig(os.path.join(dir_out, fig_name))
plt.show()
plt.close()
plt.savefig(os.path.join('docs', 'task_error.png'))
def target_error(xx, mm):
@ -119,16 +73,17 @@ def target_error(xx, mm):
def gmm():
dist_gmm, dist_men, dist_women = height_distributions()
dist_gmm, dist_male, dist_female = height_distributions()
mu_gmm = np.mean(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_women = np.mean(np.abs(1 - np.mean(dist_women) / dist_women))
mm_male = np.mean(np.abs(1 - np.mean(dist_male) / dist_male))
mm_female = np.mean(np.abs(1 - np.mean(dist_female) / dist_female))
print("Mean of GMM distribution: {:.4f}".format(mu_gmm))
print("coefficient for gmm: {:.4f}".format(mm_gmm))
print("coefficient for men: {:.4f}".format(mm_men))
print("coefficient for women: {:.4f}".format(mm_women))
print("coefficient for men: {:.4f}".format(mm_male))
print("coefficient for women: {:.4f}".format(mm_female))
return mm_gmm, mm_male, mm_female
def get_confidence(xx, zz, std):
@ -146,8 +101,9 @@ def height_distributions():
std_men = 7
mu_women = 165
std_women = 7
dist_men = np.random.normal(mu_men, std_men, 10000000)
dist_women = np.random.normal(mu_women, std_women, 10000000)
dist_men = np.random.normal(mu_men, std_men, int(1e7))
dist_women = np.random.normal(mu_women, std_women, int(1e7))
dist_gmm = np.concatenate((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)
mm_bi = (mu_d - perc_d) / mu_d
mad_d = np.mean(np.abs(dist_d - mu_d))