Issue
I have two numpy arrays that are OpenCV convex hulls and I want to check for intersection without creating for loops or creating images and performing numpy.bitwise_and
on them, both of which are quite slow in Python. The arrays look like this:
[[[x1 y1]]
[[x2 y2]]
[[x3 y3]]
...
[[xn yn]]]
Considering [[x1 y1]] as one single element, I want to perform intersection between two numpy ndarrays. How can I do that? I have found a few questions of similar nature, but I could not figure out the solution to this from there.
Solution
So this is what I did to get the job done:
import Polygon, numpy
# Here I extracted and combined some contours and created a convex hull from it.
# Now I wanna check whether a contour acquired differently intersects with this hull or not.
for contour in contours: # The result of cv2.findContours is a list of contours
contour1 = contour.flatten()
contour1 = numpy.reshape(contour1, (int(contour1.shape[0]/2),-1))
poly1 = Polygon.Polygon(contour1)
hull = hull.flatten() # This is the hull is previously constructued
hull = numpy.reshape(hull, (int(hull.shape[0]/2),-1))
poly2 = Polygon.Polygon(hull)
if (poly1 & poly2).area()<= some_max_val:
some_operations
I had to use for loop, and this altogether looks a bit tedious, although it gives me expected results. Any better methods would be greatly appreciated!
Answered By - Subhamoy S.
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