-
Notifications
You must be signed in to change notification settings - Fork 3
/
Copy pathutils.py
executable file
·133 lines (109 loc) · 3.42 KB
/
utils.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
#######################################################################################
# This is a utility library for common methods
# Author: Ashish Rao M
# email: [email protected]
#######################################################################################
import numpy as np
import matplotlib.pyplot as plt
from scipy import ndimage
from mpl_toolkits.mplot3d import Axes3D
from tqdm import tqdm
import os
import cv2
def read_data(path):
'''
Function to read data from the file containing events
Parameters:
-----------
path: <string>
The location of data to be read from
Return:
-------
events: <list>
A list of events read from the file
'''
file = open(path, "r")
print('Reading events from file ')
events = [list(map(float,line.split())) for line in file]
start_time = events[0][0]
file.close()
print('Events have been read!')
events = np.array(events, dtype=np.float_)
events[: , 0] = events[:, 0] - start_time
return events
def create_new_event_file(filename):
'''
This function creates a new file. That's all!
'''
f= open(filename,"w+")
return f
def append_to_event_file(file, event):
'''
This function is as useless as the earlier function. I don't know what i was thinking
'''
file.write(event)
def convert_to_xyz_and_store(filename, depth_map_matrix):
'''
Convert the depth map values to xyz file and store in the current directory
Parameters:
-----------
filename: <string>
Name of the file to be saved
depth_map_matrix: <np.array>
Matrix containing depth values at all position of the image
'''
f = open(filename,"w+")
for x in tqdm(range(depth_map_matrix.shape[0])):
for y in range(depth_map_matrix.shape[1]):
f.write("{}\t{}\t{}\n".format(x, y, depth_map_matrix[x][y]))
num_lines = sum([1 for line in f])
f.close()
print('finished preparing {}. The file has {} lines'.format(filename, num_lines))
def plot_dictionary(data, title, xlimits, xlabel, ylabel, type='default'):
'''
Plot the values of a dictionary
Parameters:
-----------
data: <dict>
The dictionary to be plotted
title: <string>
Yeah you know what this means. why are you even reading this
xlimits: <list>
The start and stop values on the x axis
xlabel: <string>
Seriously?
ylabel: <string>
Seriously? Seriously?
type: <string>
To make different types of plots. Currently only stem and linear interpolation have been implemented
'''
lists = sorted(data.items()) # sorted by key, return a list of tuples
x, y = zip(*lists)
plt.title(title)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xlim(xlimits)
plt.ylim(min(y) - 1 , max(y) + 1)
if type=='stem':
plt.stem(x, y)
else:
plt.plot(x, y)
plt.savefig('plots/' + title + '.png')
plt.show()
def make_video(image_folder):
'''
Make video from images.
Parameters:
----------
image_folder: <string>
directory of the folder containing the images
'''
video_name = 'event_simulation.avi'
images = [img for img in os.listdir(image_folder) if img.endswith(".png")]
frame = cv2.imread(os.path.join(image_folder, images[0]))
height, width, _ = frame.shape
video = cv2.VideoWriter(video_name, 0, 30, (width,height))
for image in images:
video.write(cv2.imread(os.path.join(image_folder, image)))
cv2.destroyAllWindows()
video.release()