64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
from functools import partial
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import cv2
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import numpy as np
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import pdf2image
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from iteration_utilities import starfilter, first
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from matplotlib import pyplot as plt
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def is_filled(hierarchy):
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# See https://stackoverflow.com/questions/60095520/how-to-distinguish-filled-circle-contour-and-unfilled-circle-contour-in-opencv
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return hierarchy[3] <= 0 and hierarchy[2] == -1
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def is_boxy(contour):
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epsilon = 0.01 * cv2.arcLength(contour, True)
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approx = cv2.approxPolyDP(contour, epsilon, True)
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return len(approx) <= 10
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def is_large_enough(contour, min_area):
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return cv2.contourArea(contour, False) > min_area
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def is_likely_redaction(contour, hierarchy, min_area):
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return is_filled(hierarchy) and is_boxy(contour) and is_large_enough(contour, min_area)
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def find_redactions(image: np.array, min_nomralized_area=200000):
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min_nomralized_area /= 200 # Assumes 200 DPI PDF -> image conversion resolution
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gray = ~cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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blurred = cv2.GaussianBlur(gray, (5, 5), 1)
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thresh = cv2.threshold(blurred, 252, 255, cv2.THRESH_BINARY)[1]
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contours, hierarchies = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
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contours = map(
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first, starfilter(partial(is_likely_redaction, min_area=min_nomralized_area), zip(contours, hierarchies[0]))
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)
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return contours
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def annotate_poly(image, conts):
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for cont in conts:
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cv2.drawContours(image, cont, -1, (0, 255, 0), 2)
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return image
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def annotate_boxes_in_pdf(pdf_path, page_index=1):
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page = pdf2image.convert_from_path(pdf_path, first_page=page_index + 1, last_page=page_index + 1)[0]
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page = np.array(page)
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asd = find_redactions(page)
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page = annotate_poly(page, asd)
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fig, ax = plt.subplots(1, 1)
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fig.set_size_inches(20, 20)
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ax.imshow(page)
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plt.show()
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