Original image:
Code:
contours, hierarchy = cv.findContours(blobs, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
cv.drawContours(blobs, contours, -1, (0,255,0), 2)
Result:
Why unconnected regions become part of the same contour, as in the example above? Is this the expected behaviour? What can I do to obtain separate contours for these regions?
see documentation
Source, an 8-bit single-channel image. Non-zero pixels are treated as 1's. Zero pixels remain 0's, so the image is treated as binary
be sure you binarized your image
Mat test = imread("test.png", 0);
Mat test1 = imread("test.png", 0);
blur(test, test,Size(19,19));
test = test / 50;
std::vector<std::vector<Point> > contours;
findContours(test, contours, RETR_TREE, CHAIN_APPROX_SIMPLE);
drawContours(test, contours, -1, Scalar(255), 1);
imshow("test", test+test1);
@tester i get slight difference in result image.i think test = test/50 not giving same result in numpy
import cv2
import numpy as np
test = cv2.imread("e:/test.png",0)
test1 = cv2.imread("e:/test.png",0)
test = cv2.blur(test,(19,19))
test = test/50
contours, hierarchy = cv2.findContours(test, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(test, contours,-1, (255), 1)
test = cv2.add(test,test1)
cv2.imshow('test', test)
cv2.waitKey()
Asked: 2020-08-12 22:19:58 -0600
Seen: 1,083 times
Last updated: Aug 13 '20
please upload the original image