Hey-o
Just sharing a code snippet to warp images to cylindrical coordinates, in case you’re stitching panoramas in Python OpenCV…
This is an improved version from what I had in class some time ago…
It runs VERY fast. No loops involved, all matrix operations. In C++ this code would look gnarly.. Thanks Numpy!
Enjoy!
Roy
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| 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 = Kinv.dot(X.T).T # 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 = K.dot(A.T).T # 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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