OpenCV doesn't have a skeleton function, but you can make your own function. From here:
The skeleton/MAT can be produced in two main ways.
The first is to use some kind of morphological thinning that successively erodes away pixels from the boundary (while preserving the end points of line segments) until no more thinning is possible, at which point what is left approximates the skeleton.
The alternative method is to first calculate the distance transform of the image. The skeleton then lies along the singularities (i.e. creases or curvature discontinuities) in the distance transform. This latter approach is more suited to calculating the MAT since the MAT is the same as the distance transform but with all points off the skeleton suppressed to zero.
Here you can find an example that uses morphological operations:
import cv2
import numpy as np
img = cv2.imread('sofsk.png',0)
size = np.size(img)
skel = np.zeros(img.shape,np.uint8)
ret,img = cv2.threshold(img,127,255,0)
element = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))
done = False
while( not done):
eroded = cv2.erode(img,element)
temp = cv2.dilate(eroded,element)
temp = cv2.subtract(img,temp)
skel = cv2.bitwise_or(skel,temp)
img = eroded.copy()
zeros = size - cv2.countNonZero(img)
if zeros==size:
done = True
cv2.imshow("skel",skel)
cv2.waitKey(0)
cv2.destroyAllWindows()
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