| 1 | import cv2 |
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| 2 | import numpy as np |
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| 3 | |
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| 4 | # read input |
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| 5 | img = cv2.imread('white_black_text_threshold.png') |
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| 6 | |
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| 7 | # convert to hsv and extract saturation |
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| 8 | hsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV) |
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| 9 | sat = hsv[:,:,1] |
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| 10 | |
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| 11 | # threshold and invert |
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| 12 | thresh = cv2.threshold(sat, 10, 255, cv2.THRESH_BINARY)[1] |
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| 13 | thresh = 255 - thresh |
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| 14 | |
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| 15 | # apply morphology dilate |
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| 16 | kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (15,15)) |
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| 17 | thresh = cv2.morphologyEx(thresh, cv2.MORPH_DILATE, kernel) |
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| 18 | thresh3 = cv2.merge([thresh,thresh,thresh]) |
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| 19 | |
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| 20 | # do inpainting |
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| 21 | result1 = cv2.inpaint(img,thresh,11,cv2.INPAINT_TELEA) |
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| 22 | result2 = cv2.inpaint(img,thresh,11,cv2.INPAINT_NS) |
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| 23 | result3 = np.where(thresh3!=0, img, thresh3) |
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| 24 | cv2.xphoto.inpaint(img, thresh, result3, cv2.xphoto.INPAINT_FSR_FAST) |
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| 25 | |
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| 26 | |
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| 27 | # save results |
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| 28 | cv2.imwrite('white_black_text_threshold.png', thresh) |
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| 29 | cv2.imwrite('white_black_text_inpainted1.png', result1) |
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| 30 | cv2.imwrite('white_black_text_inpainted2.png', result2) |
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| 31 | |
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| 32 | # show results |
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| 33 | cv2.imshow('thresh',thresh) |
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| 34 | cv2.imshow('result1',result1) |
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| 35 | cv2.imshow('result2',result2) |
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| 36 | cv2.imshow('result3',result3) |
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| 37 | cv2.waitKey(0) |
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| 38 | cv2.destroyAllWindows() |
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