I try to specify a different origin for the warpPerspective() function than the basic (0,0), in order to apply the transform independently of the support image size. I added
A much simpler and cleaner solution is to modify the perspective transformation. You can do a translation which moves the origin to the desired position, then do the perspective transformation and finally do the inverse translation.
Here is a small example program in python, which rotates an image by 45 degrees around the point(100, 100):
import cv2
import numpy as np
def translation_mat(dx, dy):
return np.array([1, 0, dx, 0, 1, dy, 0, 0, 1]).reshape((3,3))
def main():
img = cv2.imread(r"pigeon.png", cv2.IMREAD_GRAYSCALE)
# a simple rotation by 45 degrees
rot = np.array([np.sin(np.pi/4), -np.cos(np.pi/4), 0, np.cos(np.pi/4), np.sin(np.pi/4), 0, 0, 0, 1]).reshape((3,3))
t1 = translation_mat(-100, -100)
t2 = translation_mat(100, 100)
rot_shifted = t2.dot(rot.dot(t1))
size = (img.shape[1], img.shape[0])
img1 = cv2.warpPerspective(img, rot, size)
img2 = cv2.warpPerspective(img, rot_shifted, size)
cv2.imshow("Original image", img)
cv2.imshow("Rotated around (0,0)", img1)
cv2.imshow("Rotated around(100, 100)", img2)
cv2.waitKey(0)
if __name__ == '__main__':
main()
Not that you read the order of transformations from right to left.
rot_shifted = t2.dot(rot.dot(t1))
will apply t1 first, then rot, and then t2.