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threshold.py
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threshold.py
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import cv2
import numpy as np
def preprocess(img):
"""
Input: Original image
Output: Gray-scale processed image
"""
# convert RGB to gray-scale
if (np.array(img).shape[2] != 1):
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#Gassian blur
blured = cv2.GaussianBlur(gray_img, (9,9), 0)
#set a threshold
thresh = cv2.adaptiveThreshold(blured, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2)
#invert so that the grid line and text are line, the rest is black
inverted = cv2.bitwise_not(thresh, 0)
morphy_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2,2))
# Opening morphology to remove noise (while dot etc...)
morph = cv2.morphologyEx(inverted, cv2.MORPH_OPEN, morphy_kernel)
# dilate to increase border size
result = cv2.dilate(morph, morphy_kernel, iterations=1)
return result
if __name__ == "__main__":
img = "testimg\sudoku_real_4.jpeg"
img = cv2.imread(img)
processed = preprocess(img)
cv2.imshow("img", cv2.resize(img, (600,600), cv2.INTER_AREA))
cv2.waitKey(0)