OPENCV PYTHON 中的透视变换

Question

I am trying to perform a perspective transform of a sudoku puzzle. The expected transformation is happening only on the left side. Please help me by pointing out my mistake.

Input Image:

Expected Output Image:

The output I am getting:

The corners of the sudoku puzzle found using cv2.approxpolydp() are as follows:

top_left = [71,62]
top_right = [59, 418]
bottom_right = [443, 442]
bottom_left = [438, 29]

The shape of the output image is [300,300].

The corresponding output coordinates are :

output_top_left = [0,0]
output_top_right = [0, 299]
output_bottom_right = [299, 299]
output_bottom_left = [299,0]

The following is the code I used for perspective transform:

#corners = [[71,62], [59, 418], [443, 442], [438, 29]]
new = np.float32([[0,0], [0,299], [299,299], [299,0]])
M = cv2.getPerspectiveTransform(np.float32(corners), new)
dst = cv2.warpPerspective(gray, M, (300,300))

The generated Transformation Matrix is :

[[ 9.84584842e-01  3.31882531e-02 -7.19631955e+01]
 [ 8.23993265e-02  9.16380389e-01 -6.26659363e+01]
 [ 4.58051741e-04  1.45318012e-04  1.00000000e+00]]

Answer 1

You have your X,Y coordinates reversed. Python/OpenCV requires them listed as X,Y (even though you define them as numpy values). The array you must specify to getPerspectiveTransform must list them as X,Y.

Input:

import numpy as np
import cv2

# read input
img = cv2.imread("sudoku.jpg")

# specify desired output size 
width = 350
height = 350

# specify conjugate x,y coordinates (not y,x)
input = np.float32([[62,71], [418,59], [442,443], [29,438]])
output = np.float32([[0,0], [width-1,0], [width-1,height-1], [0,height-1]])

# compute perspective matrix
matrix = cv2.getPerspectiveTransform(input,output)

print(matrix.shape)
print(matrix)

# do perspective transformation setting area outside input to black
imgOutput = cv2.warpPerspective(img, matrix, (width,height), cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT, borderValue=(0,0,0))
print(imgOutput.shape)

# save the warped output
cv2.imwrite("sudoku_warped.jpg", imgOutput)

# show the result
cv2.imshow("result", imgOutput)
cv2.waitKey(0)
cv2.destroyAllWindows()

Results:

Answer 2

You should note that:

1. Coordinate are reversed: width, height
2. Destination is scaled: First Place Ratio: width/height Second Place Ratio: height/width
3. Order of points coordinate do not matter but Source and Destination points should be correspondent to each other.