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@ -70,7 +70,7 @@ class textlineerkenner:
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np.array([point for point in polygon.exterior.coords], dtype=np.uint))
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return found_polygons_early
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def filter_contours_area_of_image(self, image, contours, hirarchy, max_area, min_area):
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def filter_contours_area_of_image(self, image, contours, hierarchy, max_area, min_area):
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found_polygons_early = list()
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jv = 0
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@ -81,13 +81,13 @@ class textlineerkenner:
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polygon = geometry.Polygon([point[0] for point in c])
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area = polygon.area
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if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(
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image.shape[:2]) and hirarchy[0][jv][3] == -1 : # and hirarchy[0][jv][3]==-1 :
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image.shape[:2]) and hierarchy[0][jv][3] == -1 : # and hierarchy[0][jv][3]==-1 :
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found_polygons_early.append(
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np.array([ [point] for point in polygon.exterior.coords], dtype=np.uint))
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jv += 1
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return found_polygons_early
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def filter_contours_area_of_image_interiors(self, image, contours, hirarchy, max_area, min_area):
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def filter_contours_area_of_image_interiors(self, image, contours, hierarchy, max_area, min_area):
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found_polygons_early = list()
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jv = 0
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@ -98,7 +98,7 @@ class textlineerkenner:
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polygon = geometry.Polygon([point[0] for point in c])
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area = polygon.area
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if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]) and \
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hirarchy[0][jv][3] != -1:
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hierarchy[0][jv][3] != -1:
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# print(c[0][0][1])
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found_polygons_early.append(
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np.array([point for point in polygon.exterior.coords], dtype=np.uint))
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@ -486,9 +486,9 @@ class textlineerkenner:
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_, thresh = cv2.threshold(imgray, 0, 255, 0)
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contours, hirarchy = cv2.findContours(thresh.copy(), cv2.cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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contours, hierarchy = cv2.findContours(thresh.copy(), cv2.cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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main_contours = self.filter_contours_area_of_image(thresh, contours, hirarchy, max_area=1, min_area=0.00001)
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main_contours = self.filter_contours_area_of_image(thresh, contours, hierarchy, max_area=1, min_area=0.00001)
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self.boxes = []
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for jj in range(len(main_contours)):
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