Sorting paths from left to right in Python (OpenCV)
I am using Python and OpenCV to detect contours in my image. But when I run the following code to draw only a specific outline using the outline index, since the allocated indices are random, I get the wrong output.
So, I got to know Centroids (in my case, all centroids lie on the same horizontal line). Is there a way to sort the contour indices from left to right (0 to n) based on the x value of the centroid?
Could you please show the code for this? Any help would be greatly appreciated!
contours, hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
i = 9 ## Contour Index <----
cv2.drawContours(img,contours[i:i+1],-1,(0,0,255),2)
centroids = []
for cnt in contours:
mom = cv2.moments(cnt)
(x,y) = int(mom['m10']/mom['m00']), int(mom['m01']/mom['m00'])
cv2.circle(org,(x,y),4,(255,255,255),-1)
centroids.append((x,y)
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Implements a list sorting function in python like here .
In the implemented function, you compute the center and check if the X position is smoother or less than the other. If gretter returns 1, less than -1 and equal to 0.
def greater(a, b):
momA = cv2.moments(a)
(xa,ya) = int(momA['m10']/momA['m00']), int(momA['m01']/momA['m00'])
momB = cv2.moments(b)
(xb,yb) = int(momB['m10']/momB['m00']), int(momB['m01']/momB['m00'])
if xa>xb
return 1
if xa == xb
return 0
else
return -1
Of course, you can do better if you only calculate the centers once.
then just
contours.sort(greater)
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