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
|
from __future__ import print_function
from __future__ import division
import cv2 as cv
import numpy as np
import argparse
import random as rng
rng.seed(12345)
def thresh_callback(val):
threshold = val
## [Canny]
# Detect edges using Canny
canny_output = cv.Canny(src_gray, threshold, threshold * 2)
## [Canny]
## [findContours]
# Find contours
contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
## [findContours]
# Get the moments
mu = [None]*len(contours)
for i in range(len(contours)):
mu[i] = cv.moments(contours[i])
# Get the mass centers
mc = [None]*len(contours)
for i in range(len(contours)):
# add 1e-5 to avoid division by zero
mc[i] = (mu[i]['m10'] / (mu[i]['m00'] + 1e-5), mu[i]['m01'] / (mu[i]['m00'] + 1e-5))
# Draw contours
## [zeroMat]
drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)
## [zeroMat]
## [forContour]
for i in range(len(contours)):
color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256))
cv.drawContours(drawing, contours, i, color, 2)
cv.circle(drawing, (int(mc[i][0]), int(mc[i][1])), 4, color, -1)
## [forContour]
## [showDrawings]
# Show in a window
cv.imshow('Contours', drawing)
## [showDrawings]
# Calculate the area with the moments 00 and compare with the result of the OpenCV function
for i in range(len(contours)):
print(' * Contour[%d] - Area (M_00) = %.2f - Area OpenCV: %.2f - Length: %.2f' % (i, mu[i]['m00'], cv.contourArea(contours[i]), cv.arcLength(contours[i], True)))
## [setup]
# Load source image
parser = argparse.ArgumentParser(description='Code for Image Moments tutorial.')
parser.add_argument('--input', help='Path to input image.', default='stuff.jpg')
args = parser.parse_args()
src = cv.imread(cv.samples.findFile(args.input))
if src is None:
print('Could not open or find the image:', args.input)
exit(0)
# Convert image to gray and blur it
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
src_gray = cv.blur(src_gray, (3,3))
## [setup]
## [createWindow]
# Create Window
source_window = 'Source'
cv.namedWindow(source_window)
cv.imshow(source_window, src)
## [createWindow]
## [trackbar]
max_thresh = 255
thresh = 100 # initial threshold
cv.createTrackbar('Canny Thresh:', source_window, thresh, max_thresh, thresh_callback)
thresh_callback(thresh)
## [trackbar]
cv.waitKey()
|
