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]]
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:
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