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Last active May 7, 2024 06:42
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Warp an image to cylindrical coordinates for cylindrical panorama stitching, using Python OpenCV
import cv2
import numpy as np
def cylindricalWarp(img, K):
"""This function returns the cylindrical warp for a given image and intrinsics matrix K"""
h_,w_ = img.shape[:2]
# pixel coordinates
y_i, x_i = np.indices((h_,w_))
X = np.stack([x_i,y_i,np.ones_like(x_i)],axis=-1).reshape(h_*w_,3) # to homog
Kinv = np.linalg.inv(K)
X = # normalized coords
# calculate cylindrical coords (sin\theta, h, cos\theta)
A = np.stack([np.sin(X[:,0]),X[:,1],np.cos(X[:,0])],axis=-1).reshape(w_*h_,3)
B = # project back to image-pixels plane
# back from homog coords
B = B[:,:-1] / B[:,[-1]]
# make sure warp coords only within image bounds
B[(B[:,0] < 0) | (B[:,0] >= w_) | (B[:,1] < 0) | (B[:,1] >= h_)] = -1
B = B.reshape(h_,w_,-1)
img_rgba = cv2.cvtColor(img,cv2.COLOR_BGR2BGRA) # for transparent borders...
# warp the image according to cylindrical coords
return cv2.remap(img_rgba, B[:,:,0].astype(np.float32), B[:,:,1].astype(np.float32), cv2.INTER_AREA, borderMode=cv2.BORDER_TRANSPARENT)
if __name__ == '__main__':
img = cv2.imread("image.png")
h, w = img.shape[:2]
K = np.array([[800,0,w/2],[0,800,h/2],[0,0,1]]) # mock intrinsics
img_cyl = cylindricalWarp(img, K)
cv2.imwrite("image_cyl.png", img_cyl)
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Thanks for this. For future reference, to wrap an image with a transparent background:
img = cv2.imread("image.png", cv2.IMREAD_UNCHANGED)

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I really want reverse method, cylinderical to flat image. Is there any way?

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@hanish3464 you can invert the mapping B and use that for cv2.remap. here's an answer on stackoverflow with an implementation for how to do that:

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Ascyt commented Apr 13, 2023

Did not work. Only outputted the same image without the outer pixels. I used this image:
And got this:


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