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@ -1263,7 +1263,6 @@ class eynollah:
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# create the file structure
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# create the file structure
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pcgts, page = create_page_xml(self.image_filename, self.height_org, self.width_org)
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pcgts, page = create_page_xml(self.image_filename, self.height_org, self.width_org)
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page_print_sub = ET.SubElement(page, "Border")
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page_print_sub = ET.SubElement(page, "Border")
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coord_page = ET.SubElement(page_print_sub, "Coords")
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coord_page = ET.SubElement(page_print_sub, "Coords")
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coord_page.set('points', self.calculate_page_coords())
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coord_page.set('points', self.calculate_page_coords())
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@ -1271,10 +1270,7 @@ class eynollah:
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if len(contours) > 0:
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if len(contours) > 0:
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region_order = ET.SubElement(page, 'ReadingOrder')
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region_order = ET.SubElement(page, 'ReadingOrder')
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region_order_sub = ET.SubElement(region_order, 'OrderedGroup')
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region_order_sub = ET.SubElement(region_order, 'OrderedGroup')
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region_order_sub.set('id',"ro357564684568544579089")
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region_order_sub.set('id',"ro357564684568544579089")
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#args_sort=order_of_texts
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for vj in order_of_texts:
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for vj in order_of_texts:
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name = "coord_text_" + str(vj)
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name = "coord_text_" + str(vj)
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name = ET.SubElement(region_order_sub, 'RegionRefIndexed')
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name = ET.SubElement(region_order_sub, 'RegionRefIndexed')
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@ -1285,7 +1281,6 @@ class eynollah:
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indexer_region = len(contours) + len(contours_h)
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indexer_region = len(contours) + len(contours_h)
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for vm in range(len(found_polygons_marginals)):
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for vm in range(len(found_polygons_marginals)):
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id_of_marginalia.append('r' + str(indexer_region))
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id_of_marginalia.append('r' + str(indexer_region))
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name = "coord_text_"+str(indexer_region)
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name = "coord_text_"+str(indexer_region)
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name = ET.SubElement(region_order_sub, 'RegionRefIndexed')
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name = ET.SubElement(region_order_sub, 'RegionRefIndexed')
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name.set('index',str(indexer_region) )
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name.set('index',str(indexer_region) )
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@ -1503,7 +1498,6 @@ class eynollah:
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self.logger.debug('enter write_into_page_xml')
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self.logger.debug('enter write_into_page_xml')
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found_polygons_text_region = contours
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found_polygons_text_region = contours
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##found_polygons_text_region_h=contours_h
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# create the file structure
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# create the file structure
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pcgts, page = create_page_xml(self.image_filename, self.height_org, self.width_org)
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pcgts, page = create_page_xml(self.image_filename, self.height_org, self.width_org)
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@ -1515,14 +1509,10 @@ class eynollah:
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region_order = ET.SubElement(page, 'ReadingOrder')
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region_order = ET.SubElement(page, 'ReadingOrder')
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region_order_sub = ET.SubElement(region_order, 'OrderedGroup')
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region_order_sub = ET.SubElement(region_order, 'OrderedGroup')
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region_order_sub.set('id',"ro357564684568544579089")
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region_order_sub.set('id',"ro357564684568544579089")
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indexer_region=0
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indexer_region=0
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for vj in order_of_texts:
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for vj in order_of_texts:
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name="coord_text_"+str(vj)
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name="coord_text_"+str(vj)
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name = ET.SubElement(region_order_sub, 'RegionRefIndexed')
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name = ET.SubElement(region_order_sub, 'RegionRefIndexed')
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name.set('index',str(indexer_region) )
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name.set('index',str(indexer_region) )
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name.set('regionRef',id_of_texts[vj])
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name.set('regionRef',id_of_texts[vj])
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indexer_region+=1
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indexer_region+=1
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@ -2150,10 +2140,8 @@ class eynollah:
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img_only_regions_with_sep = img_only_regions_with_sep.astype(np.uint8)
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img_only_regions_with_sep = img_only_regions_with_sep.astype(np.uint8)
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img_only_regions = cv2.erode(img_only_regions_with_sep[:, :], self.kernel, iterations=6)
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img_only_regions = cv2.erode(img_only_regions_with_sep[:, :], self.kernel, iterations=6)
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try:
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try:
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num_col, peaks_neg_fin = find_num_col(img_only_regions, multiplier=6.0)
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num_col, peaks_neg_fin = find_num_col(img_only_regions, multiplier=6.0)
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if not num_column_is_classified:
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if not num_column_is_classified:
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num_col_classifier = num_col + 1
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num_col_classifier = num_col + 1
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except:
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except:
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@ -2225,15 +2213,10 @@ class eynollah:
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try:
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try:
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1
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regions_without_seperators = regions_without_seperators.astype(np.uint8)
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regions_without_seperators = regions_without_seperators.astype(np.uint8)
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text_regions_p = get_marginals(rotate_image(regions_without_seperators, slope_deskew), text_regions_p, num_col_classifier, slope_deskew, kernel=self.kernel)
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text_regions_p = get_marginals(rotate_image(regions_without_seperators, slope_deskew), text_regions_p, num_col_classifier, slope_deskew, kernel=self.kernel)
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except:
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except:
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pass
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pass
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# plt.imshow(text_regions_p)
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# plt.show()
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if self.plotter:
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if self.plotter:
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self.plotter.save_plot_of_layout_main_all(text_regions_p, image_page)
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self.plotter.save_plot_of_layout_main_all(text_regions_p, image_page)
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self.plotter.save_plot_of_layout_main(text_regions_p, image_page)
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self.plotter.save_plot_of_layout_main(text_regions_p, image_page)
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@ -2247,13 +2230,10 @@ class eynollah:
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textline_mask_tot_d = resize_image(textline_mask_tot_d, text_regions_p.shape[0], text_regions_p.shape[1])
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textline_mask_tot_d = resize_image(textline_mask_tot_d, text_regions_p.shape[0], text_regions_p.shape[1])
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regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
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regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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text_regions_p_1_n = None
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text_regions_p_1_n = None
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textline_mask_tot_d = None
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textline_mask_tot_d = None
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regions_without_seperators_d = None
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regions_without_seperators_d = None
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pixel_lines = 3
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pixel_lines = 3
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, seperators_closeup_n = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines)
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num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, seperators_closeup_n = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines)
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@ -2279,7 +2259,6 @@ class eynollah:
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#random_pixels_for_image = np.random.randn(regions_without_seperators_d.shape[0], regions_without_seperators_d.shape[1])
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#random_pixels_for_image = np.random.randn(regions_without_seperators_d.shape[0], regions_without_seperators_d.shape[1])
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#random_pixels_for_image[random_pixels_for_image < -0.5] = 0
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#random_pixels_for_image[random_pixels_for_image < -0.5] = 0
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#random_pixels_for_image[random_pixels_for_image != 0] = 1
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#random_pixels_for_image[random_pixels_for_image != 0] = 1
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#regions_without_seperators_d[(random_pixels_for_image[:, :] == 1) & (text_regions_p_1_n[:, :] == 2)] = 1
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#regions_without_seperators_d[(random_pixels_for_image[:, :] == 1) & (text_regions_p_1_n[:, :] == 2)] = 1
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t1 = time.time()
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t1 = time.time()
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@ -2369,21 +2348,17 @@ class eynollah:
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textline_mask_tot_d = resize_image(textline_mask_tot_d, text_regions_p.shape[0], text_regions_p.shape[1])
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textline_mask_tot_d = resize_image(textline_mask_tot_d, text_regions_p.shape[0], text_regions_p.shape[1])
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regions_fully_n = resize_image(regions_fully_n, text_regions_p.shape[0], text_regions_p.shape[1])
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regions_fully_n = resize_image(regions_fully_n, text_regions_p.shape[0], text_regions_p.shape[1])
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regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
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regions_without_seperators_d = (text_regions_p_1_n[:, :] == 1) * 1
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else:
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else:
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text_regions_p_1_n = None
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text_regions_p_1_n = None
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textline_mask_tot_d = None
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textline_mask_tot_d = None
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regions_without_seperators_d = None
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regions_without_seperators_d = None
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
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regions_without_seperators = (text_regions_p[:, :] == 1) * 1 # ( (text_regions_p[:,:]==1) | (text_regions_p[:,:]==2) )*1 #self.return_regions_without_seperators_new(text_regions_p[:,:,0],img_only_regions)
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K.clear_session()
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K.clear_session()
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gc.collect()
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gc.collect()
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img_revised_tab = np.copy(text_regions_p[:, :])
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img_revised_tab = np.copy(text_regions_p[:, :])
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pixel_img = 5
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polygons_of_images = return_contours_of_interested_region(img_revised_tab, 5)
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polygons_of_images = return_contours_of_interested_region(img_revised_tab, pixel_img)
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self.logger.debug('exit run_boxes_full_layout')
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self.logger.debug('exit run_boxes_full_layout')
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return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully, regions_without_seperators
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return polygons_of_images, img_revised_tab, text_regions_p_1_n, textline_mask_tot_d, regions_without_seperators_d, regions_fully, regions_without_seperators
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@ -2406,7 +2381,6 @@ class eynollah:
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self.run_graphics_and_columns(text_regions_p_1, num_col_classifier, num_column_is_classified)
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self.run_graphics_and_columns(text_regions_p_1, num_col_classifier, num_column_is_classified)
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self.logger.info("Graphics detection took %ss ", str(time.time() - t1))
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self.logger.info("Graphics detection took %ss ", str(time.time() - t1))
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if not num_col:
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if not num_col:
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self.logger.info("No columns detected, outputting an empty PAGE-XML")
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self.logger.info("No columns detected, outputting an empty PAGE-XML")
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self.write_into_page_xml([], page_coord, self.dir_out, [], [], [], [], [], [], [], [], self.curved_line, [], [])
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self.write_into_page_xml([], page_coord, self.dir_out, [], [], [], [], [], [], [], [], self.curved_line, [], [])
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@ -2497,11 +2471,8 @@ class eynollah:
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(h, w) = text_only.shape[:2]
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(h, w) = text_only.shape[:2]
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center = (w // 2.0, h // 2.0)
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center = (w // 2.0, h // 2.0)
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M = cv2.getRotationMatrix2D(center, slope_deskew, 1.0)
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M = cv2.getRotationMatrix2D(center, slope_deskew, 1.0)
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M_22 = np.array(M)[:2, :2]
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M_22 = np.array(M)[:2, :2]
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p_big = np.dot(M_22, [cx_bigest_big, cy_biggest_big])
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p_big = np.dot(M_22, [cx_bigest_big, cy_biggest_big])
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x_diff = p_big[0] - cx_bigest_d_big
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x_diff = p_big[0] - cx_bigest_d_big
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y_diff = p_big[1] - cy_biggest_d_big
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y_diff = p_big[1] - cy_biggest_d_big
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@ -2547,9 +2518,9 @@ class eynollah:
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cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contoures([contours_biggest])
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cx_bigest_big, cy_biggest_big, _, _, _, _, _ = find_new_features_of_contoures([contours_biggest])
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cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contoures(contours_only_text_parent)
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cx_bigest, cy_biggest, _, _, _, _, _ = find_new_features_of_contoures(contours_only_text_parent)
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# print(areas_cnt_text_parent,'areas_cnt_text_parent')
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self.logger.debug('areas_cnt_text_parent %s', areas_cnt_text_parent)
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# print(areas_cnt_text_parent_d,'areas_cnt_text_parent_d')
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self.logger.debug('areas_cnt_text_parent_d %s', areas_cnt_text_parent_d)
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# print(len(contours_only_text_parent),len(contours_only_text_parent_d),'vizzz')
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self.logger.debug('len(contours_only_text_parent) %s', len(contours_only_text_parent_d))
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txt_con_org = get_textregion_contours_in_org_image(contours_only_text_parent, self.image, slope_first)
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txt_con_org = get_textregion_contours_in_org_image(contours_only_text_parent, self.image, slope_first)
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boxes_text, _ = get_text_region_boxes_by_given_contours(contours_only_text_parent)
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boxes_text, _ = get_text_region_boxes_by_given_contours(contours_only_text_parent)
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@ -2580,8 +2551,6 @@ class eynollah:
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contours_only_text_parent_d_ordered = None
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contours_only_text_parent_d_ordered = None
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text_regions_p, contours_only_text_parent, contours_only_text_parent_h, all_box_coord, all_box_coord_h, all_found_texline_polygons, all_found_texline_polygons_h, slopes, slopes_h, contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered = check_any_text_region_in_model_one_is_main_or_header(text_regions_p, regions_fully, contours_only_text_parent, all_box_coord, all_found_texline_polygons, slopes, contours_only_text_parent_d_ordered)
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text_regions_p, contours_only_text_parent, contours_only_text_parent_h, all_box_coord, all_box_coord_h, all_found_texline_polygons, all_found_texline_polygons_h, slopes, slopes_h, contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered = check_any_text_region_in_model_one_is_main_or_header(text_regions_p, regions_fully, contours_only_text_parent, all_box_coord, all_found_texline_polygons, slopes, contours_only_text_parent_d_ordered)
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if self.plotter:
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if self.plotter:
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self.plotter.save_plot_of_layout(text_regions_p, image_page)
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self.plotter.save_plot_of_layout(text_regions_p, image_page)
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self.plotter.save_plot_of_layout_all(text_regions_p, image_page)
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self.plotter.save_plot_of_layout_all(text_regions_p, image_page)
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@ -2599,9 +2568,9 @@ class eynollah:
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if not self.headers_off:
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if not self.headers_off:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, seperators_closeup_n = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h)
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num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, _ = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h)
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else:
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else:
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num_col_d, peaks_neg_fin_d, matrix_of_lines_ch_d, spliter_y_new_d, seperators_closeup_n_d = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h_d_ordered)
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num_col_d, peaks_neg_fin_d, matrix_of_lines_ch_d, spliter_y_new_d, _ = find_number_of_columns_in_document(np.repeat(text_regions_p_1_n[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines, contours_only_text_parent_h_d_ordered)
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elif self.headers_off:
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elif self.headers_off:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, seperators_closeup_n = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines)
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num_col, peaks_neg_fin, matrix_of_lines_ch, spliter_y_new, seperators_closeup_n = find_number_of_columns_in_document(np.repeat(text_regions_p[:, :, np.newaxis], 3, axis=2), num_col_classifier, pixel_lines)
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@ -2613,7 +2582,6 @@ class eynollah:
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# print(matrix_of_lines_ch.shape,matrix_of_lines_ch_d.shape,'matrix_of_lines_ch')
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# print(matrix_of_lines_ch.shape,matrix_of_lines_ch_d.shape,'matrix_of_lines_ch')
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if num_col_classifier >= 3:
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if num_col_classifier >= 3:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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regions_without_seperators = regions_without_seperators.astype(np.uint8)
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regions_without_seperators = regions_without_seperators.astype(np.uint8)
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regions_without_seperators = cv2.erode(regions_without_seperators[:, :], self.kernel, iterations=6)
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regions_without_seperators = cv2.erode(regions_without_seperators[:, :], self.kernel, iterations=6)
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@ -2644,16 +2612,14 @@ class eynollah:
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order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered, boxes_d, textline_mask_tot_d)
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order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent_d_ordered, contours_only_text_parent_h_d_ordered, boxes_d, textline_mask_tot_d)
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self.write_into_page_xml_full(contours_only_text_parent, contours_only_text_parent_h, page_coord, self.dir_out, order_text_new, id_of_texts_tot, all_found_texline_polygons, all_found_texline_polygons_h, all_box_coord, all_box_coord_h, polygons_of_images, polygons_of_tabels, polygons_of_drop_capitals, polygons_of_marginals, all_found_texline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals)
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self.write_into_page_xml_full(contours_only_text_parent, contours_only_text_parent_h, page_coord, self.dir_out, order_text_new, id_of_texts_tot, all_found_texline_polygons, all_found_texline_polygons_h, all_box_coord, all_box_coord_h, polygons_of_images, polygons_of_tabels, polygons_of_drop_capitals, polygons_of_marginals, all_found_texline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals)
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else:
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else:
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contours_only_text_parent_h = None
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contours_only_text_parent_h = None
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# self.logger.debug('bura galmir?')
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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if np.abs(slope_deskew) < SLOPE_THRESHOLD:
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#contours_only_text_parent = list(np.array(contours_only_text_parent)[index_by_text_par_con])
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order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot)
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order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot)
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else:
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else:
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contours_only_text_parent_d_ordered = list(np.array(contours_only_text_parent_d_ordered)[index_by_text_par_con])
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contours_only_text_parent_d_ordered = list(np.array(contours_only_text_parent_d_ordered)[index_by_text_par_con])
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order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent_d_ordered, contours_only_text_parent_h, boxes_d, textline_mask_tot_d)
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order_text_new, id_of_texts_tot = self.do_order_of_regions(contours_only_text_parent_d_ordered, contours_only_text_parent_h, boxes_d, textline_mask_tot_d)
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# order_text_new , id_of_texts_tot=self.do_order_of_regions(contours_only_text_parent,contours_only_text_parent_h,boxes,textline_mask_tot)
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self.write_into_page_xml(txt_con_org, page_coord, self.dir_out, order_text_new, id_of_texts_tot, all_found_texline_polygons, all_box_coord, polygons_of_images, polygons_of_marginals, all_found_texline_polygons_marginals, all_box_coord_marginals, self.curved_line, slopes, slopes_marginals)
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self.write_into_page_xml(txt_con_org, page_coord, self.dir_out, order_text_new, id_of_texts_tot, all_found_texline_polygons, all_box_coord, polygons_of_images, polygons_of_marginals, all_found_texline_polygons_marginals, all_box_coord_marginals, self.curved_line, slopes, slopes_marginals)
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self.logger.info("Job done in %ss", str(time.time() - t1))
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self.logger.info("Job done in %ss", str(time.time() - t1))
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