-
Notifications
You must be signed in to change notification settings - Fork 11
/
logarithmic.py
188 lines (125 loc) · 5.1 KB
/
logarithmic.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
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
#####################################################################
# Example : logarithmic transform on an image from an attached web camera
# Author : Toby Breckon, [email protected]
# Copyright (c) 2015 School of Engineering & Computing Science,
# Copyright (c) 2019 Dept Computer Science,
# Durham University, UK
# License : LGPL - http://www.gnu.org/licenses/lgpl.html
#####################################################################
import cv2
import sys
import argparse
import math
#####################################################################
keep_processing = True
# parse command line arguments for camera ID or video file
parser = argparse.ArgumentParser(
description='Perform ' +
sys.argv[0] +
' example operation on incoming camera/video image')
parser.add_argument(
"-c",
"--camera_to_use",
type=int,
help="specify camera to use",
default=0)
parser.add_argument(
"-r",
"--rescale",
type=float,
help="rescale image by this factor",
default=1.0)
parser.add_argument(
'video_file',
metavar='video_file',
type=str,
nargs='?',
help='specify optional video file')
args = parser.parse_args()
#####################################################################
# this function is called as a call-back everytime the trackbar is moved
# (here we just do nothing)
def nothing(x):
pass
#####################################################################
# logarithmic transform
# image - greyscale image
# c - scaling constant
# sigma - "gradient" co-efficient of logarithmic function
def logarithmic_transform(image, c, sigma):
for i in range(0, image.shape[1]): # image width
for j in range(0, image.shape[0]): # image height
# compute logarithmic transform
image[j, i] = int(c * math.log(1 +
((math.exp(sigma) - 1) * image[j, i])))
return image
#####################################################################
# define video capture object
try:
# to use a non-buffered camera stream (via a separate thread)
if not (args.video_file):
import camera_stream
cap = camera_stream.CameraVideoStream(use_tapi=False)
else:
cap = cv2.VideoCapture() # not needed for video files
except BaseException:
# if not then just use OpenCV default
print("INFO: camera_stream class not found - camera input may be buffered")
cap = cv2.VideoCapture()
# define display window name
window_name = "Live Camera Input" # window name
window_name2 = "Logarithmic Transform" # window name
# if command line arguments are provided try to read video_file
# otherwise default to capture from attached H/W camera
if (((args.video_file) and (cap.open(str(args.video_file))))
or (cap.open(args.camera_to_use))):
# create window by name (as resizable)
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.namedWindow(window_name2, cv2.WINDOW_NORMAL)
# add some track bar controllers for settings
constant = 10
cv2.createTrackbar("constant, C", window_name2, constant, 100, nothing)
sigma = 1
cv2.createTrackbar("sigma (*0.01)", window_name2, sigma, 10, nothing)
while (keep_processing):
# if video file or camera successfully open then read frame from video
if (cap.isOpened):
ret, frame = cap.read()
# when we reach the end of the video (file) exit cleanly
if (ret == 0):
keep_processing = False
continue
# rescale if specified
if (args.rescale != 1.0):
frame = cv2.resize(
frame, (0, 0), fx=args.rescale, fy=args.rescale)
# convert to grayscale
gray_img = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# get parameters from track bars
constant = cv2.getTrackbarPos("constant, C", window_name2)
sigma = cv2.getTrackbarPos("sigma (*0.01)", window_name2) * 0.01
# make a copy and log tranform it
log_img = gray_img.copy()
log_img = logarithmic_transform(log_img, constant, sigma)
# display image
cv2.imshow(window_name, gray_img)
cv2.imshow(window_name2, log_img)
# start the event loop - essential
# cv2.waitKey() is a keyboard binding function (argument is the time in
# ms). It waits for specified milliseconds for any keyboard event.
# If you press any key in that time, the program continues.
# If 0 is passed, it waits indefinitely for a key stroke.
# (bitwise and with 0xFF to extract least significant byte of
# multi-byte response)
# wait 40ms (i.e. 1000ms / 25 fps = 40 ms)
key = cv2.waitKey(40) & 0xFF
# It can also be set to detect specific key strokes by recording which
# key is pressed
# e.g. if user presses "x" then exit
if (key == ord('x')):
keep_processing = False
# close all windows
cv2.destroyAllWindows()
else:
print("No usable camera connected.")
#####################################################################