mirror of
https://github.com/qurator-spk/eynollah.git
synced 2025-11-04 11:44:15 +01:00
split do_order_of_regions, lots of logging
This commit is contained in:
Konstantin Baierer
parent
8cd4067fc5
commit
ca23b32e9b
1 changed files with 323 additions and 303 deletions
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@ -276,6 +276,7 @@ class eynollah:
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return prediction_true
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def check_dpi(self):
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self.logger.debug("enter check_dpi")
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dpi = os.popen('identify -format "%x " ' + self.image_filename).read()
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return int(float(dpi))
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@ -368,7 +369,7 @@ class eynollah:
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label_p_pred = model_num_classifier.predict(img_in)
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num_col = np.argmax(label_p_pred[0]) + 1
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print(num_col, label_p_pred, "num_col_classifier")
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self.logger.info("Found %s columns (%s)", num_col, label_p_pred)
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session_col_classifier.close()
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del model_num_classifier
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@ -421,7 +422,7 @@ class eynollah:
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label_p_pred = model_num_classifier.predict(img_in)
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num_col = np.argmax(label_p_pred[0]) + 1
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print(num_col, label_p_pred, "num_col_classifier")
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self.logger.info("Found %s columns (%s)", num_col, label_p_pred)
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session_col_classifier.close()
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del model_num_classifier
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@ -431,7 +432,7 @@ class eynollah:
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del page_coord
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K.clear_session()
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gc.collect()
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print(dpi)
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self.logger.info("%s DPI" % dpi)
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if dpi < 298:
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img_new, num_column_is_classified = self.calculate_width_height_by_columns(img, num_col, width_early, label_p_pred)
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@ -484,7 +485,7 @@ class eynollah:
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del img_res
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def start_new_session_and_model(self, model_dir):
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self.logger.debug("enter start_new_session_and_model")
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self.logger.debug("enter start_new_session_and_model (model_dir=%s)", model_dir)
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config = tf.ConfigProto()
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config.gpu_options.allow_growth = True
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@ -507,7 +508,7 @@ class eynollah:
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if img.shape[1] < img_width_model:
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img = resize_image(img, img.shape[0], img_width_model)
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# print(img_height_model,img_width_model)
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self.logger.info("Image dimensions: %sx%s", img_height_model, img_width_model)
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margin = int(marginal_of_patch_percent * img_height_model)
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width_mid = img_width_model - 2 * margin
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height_mid = img_height_model - 2 * margin
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@ -660,9 +661,11 @@ class eynollah:
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del img_page_prediction
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gc.collect()
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self.logger.debug("exit resize_and_enhance_image_with_column_classifier")
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return croped_page, page_coord
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def extract_page(self):
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self.logger.debug("enter extract_page")
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patches = False
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model_page, session_page = self.start_new_session_and_model(self.model_page_dir)
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for ii in range(1):
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@ -708,6 +711,7 @@ class eynollah:
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return croped_page, page_coord
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def extract_text_regions(self, img, patches, cols):
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self.logger.debug("enter extract_text_regions")
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img_height_h = img.shape[0]
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img_width_h = img.shape[1]
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@ -809,9 +813,11 @@ class eynollah:
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del session_region
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del img
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gc.collect()
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self.logger.debug("exit extract_text_regions")
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return prediction_regions, prediction_regions2
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def get_slopes_and_deskew_new(self, contours, contours_par, textline_mask_tot, image_page_rotated, boxes, slope_deskew):
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self.logger.debug("enter get_slopes_and_deskew_new")
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num_cores = cpu_count()
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queue_of_all_params = Queue()
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@ -858,10 +864,12 @@ class eynollah:
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for i in range(num_cores):
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processes[i].join()
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# print(slopes,'slopes')
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self.logger.debug('slopes %s', slopes)
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self.logger.debug("exit get_slopes_and_deskew_new")
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return slopes, all_found_texline_polygons, boxes, all_found_text_regions, all_found_text_regions_par, all_box_coord, all_index_text_con
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def get_slopes_and_deskew_new_curved(self, contours, contours_par, textline_mask_tot, image_page_rotated, boxes, mask_texts_only, num_col, scale_par, slope_deskew):
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self.logger.debug("enter get_slopes_and_deskew_new_curved")
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num_cores = cpu_count()
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queue_of_all_params = Queue()
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@ -912,6 +920,7 @@ class eynollah:
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return all_found_texline_polygons, boxes, all_found_text_regions, all_found_text_regions_par, all_box_coord, all_index_text_con, slopes
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def do_work_of_slopes_new_curved(self, queue_of_all_params, boxes_text, textline_mask_tot_ea, contours_per_process, contours_par_per_process, image_page_rotated, mask_texts_only, num_col, scale_par, indexes_r_con_per_pro, slope_deskew):
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self.logger.debug("enter do_work_of_slopes_new_curved")
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slopes_per_each_subprocess = []
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bounding_box_of_textregion_per_each_subprocess = []
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textlines_rectangles_per_each_subprocess = []
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@ -1021,6 +1030,7 @@ class eynollah:
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queue_of_all_params.put([textlines_rectangles_per_each_subprocess, bounding_box_of_textregion_per_each_subprocess, contours_textregion_per_each_subprocess, contours_textregion_par_per_each_subprocess, all_box_coord_per_process, index_by_text_region_contours, slopes_per_each_subprocess])
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def do_work_of_slopes_new(self, queue_of_all_params, boxes_text, textline_mask_tot_ea, contours_per_process, contours_par_per_process, indexes_r_con_per_pro, image_page_rotated, slope_deskew):
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self.logger.debug('enter do_work_of_slopes_new')
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slopes_per_each_subprocess = []
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bounding_box_of_textregion_per_each_subprocess = []
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@ -1095,6 +1105,7 @@ class eynollah:
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queue_of_all_params.put([slopes_per_each_subprocess, textlines_rectangles_per_each_subprocess, bounding_box_of_textregion_per_each_subprocess, contours_textregion_per_each_subprocess, contours_textregion_par_per_each_subprocess, all_box_coord_per_process, index_by_text_region_contours])
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def textline_contours(self, img, patches, scaler_h, scaler_w):
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self.logger.debug('enter textline_contours')
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if patches:
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model_textline, session_textline = self.start_new_session_and_model(self.model_textline_dir)
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@ -1127,6 +1138,7 @@ class eynollah:
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return prediction_textline[:, :, 0], prediction_textline_longshot_true_size[:, :, 0]
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def do_work_of_slopes(self, q, poly, box_sub, boxes_per_process, textline_mask_tot, contours_per_process):
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self.logger.debug('enter do_work_of_slopes')
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slope_biggest = 0
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slopes_sub = []
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boxes_sub_new = []
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@ -1167,6 +1179,7 @@ class eynollah:
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box_sub.put(boxes_sub_new)
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def serialize_lines_in_region(self, textregion, all_found_texline_polygons, region_idx, page_coord, all_box_coord, slopes, id_indexer_l):
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self.logger.debug('enter serialize_lines_in_region')
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for j in range(len(all_found_texline_polygons[region_idx])):
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textline=ET.SubElement(textregion, 'TextLine')
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textline.set('id','l'+str(id_indexer_l))
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@ -1245,6 +1258,7 @@ class eynollah:
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return id_indexer_l
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def calculate_polygon_coords(self, contour_list, i, page_coord):
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self.logger.debug('enter calculate_polygon_coords')
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coords = ''
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for j in range(len(contour_list[i])):
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if len(contour_list[i][j]) == 2:
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@ -1262,6 +1276,7 @@ class eynollah:
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return coords
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def write_into_page_xml_full(self, contours, contours_h, page_coord, dir_of_image, order_of_texts, id_of_texts, all_found_texline_polygons, all_found_texline_polygons_h, all_box_coord, all_box_coord_h, found_polygons_text_region_img, found_polygons_tables, found_polygons_drop_capitals, found_polygons_marginals, all_found_texline_polygons_marginals, all_box_coord_marginals, slopes, slopes_marginals):
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self.logger.debug('enter write_into_page_xml_full')
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found_polygons_text_region = contours
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found_polygons_text_region_h = contours_h
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@ -1481,13 +1496,14 @@ class eynollah:
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##tree = ET.ElementTree(pcgts)
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##tree.write(os.path.join(dir_of_image, self.image_filename_stem) + ".xml")
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print(self.image_filename_stem)
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self.logger.info("filename stem: '%s'", self.image_filename_stem)
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# print(os.path.join(dir_of_image, self.image_filename_stem) + ".xml")
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tree = ET.ElementTree(pcgts)
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tree.write(os.path.join(dir_of_image, self.image_filename_stem) + ".xml")
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def calculate_page_coords(self):
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self.logger.debug('enter calculate_page_coords')
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points_page_print = ""
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for lmm in range(len(self.cont_page[0])):
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if len(self.cont_page[0][lmm]) == 2:
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@ -1504,6 +1520,7 @@ class eynollah:
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return points_page_print
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def write_into_page_xml(self, contours, page_coord, dir_of_image, order_of_texts, id_of_texts, all_found_texline_polygons, all_box_coord, found_polygons_text_region_img, found_polygons_marginals, all_found_texline_polygons_marginals, all_box_coord_marginals, curved_line, slopes, slopes_marginals):
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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_h=contours_h
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@ -1669,11 +1686,9 @@ class eynollah:
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pass
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print(self.image_filename_stem)
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# print(os.path.join(dir_of_image, self.image_filename_stem) + ".xml")
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self.logger.info("filename stem: '%s'", self.image_filename_stem)
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tree = ET.ElementTree(pcgts)
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tree.write(os.path.join(dir_of_image, self.image_filename_stem) + ".xml")
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# cv2.imwrite(os.path.join(dir_of_image, self.image_filename_stem) + ".tif",self.image_org)
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def get_regions_from_xy_2models(self,img,is_image_enhanced):
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self.logger.debug("enter get_regions_from_xy_2models")
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@ -1792,7 +1807,7 @@ class eynollah:
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rate_two_models=text_sume_second/float(text_sume_early)*100
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print(rate_two_models,'ratio_of_two_models')
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self.logger.info("ratio_of_two_models: %s", rate_two_models)
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if is_image_enhanced and rate_two_models<95.50:#98.45:
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pass
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else:
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@ -1843,292 +1858,299 @@ class eynollah:
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return text_regions_p_true
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def do_order_of_regions(self, contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot):
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def do_order_of_regions_full_layout(self, contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot):
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self.logger.debug("enter do_order_of_regions_full_layout")
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cx_text_only, cy_text_only, x_min_text_only, _, _, _, y_cor_x_min_main = find_new_features_of_contoures(contours_only_text_parent)
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cx_text_only_h, cy_text_only_h, x_min_text_only_h, _, _, _, y_cor_x_min_main_h = find_new_features_of_contoures(contours_only_text_parent_h)
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try:
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arg_text_con = []
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for ii in range(len(cx_text_only)):
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for jj in range(len(boxes)):
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if (x_min_text_only[ii] + 80) >= boxes[jj][0] and (x_min_text_only[ii] + 80) < boxes[jj][1] and y_cor_x_min_main[ii] >= boxes[jj][2] and y_cor_x_min_main[ii] < boxes[jj][3]:
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arg_text_con.append(jj)
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break
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arg_arg_text_con = np.argsort(arg_text_con)
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args_contours = np.array(range(len(arg_text_con)))
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arg_text_con_h = []
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for ii in range(len(cx_text_only_h)):
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for jj in range(len(boxes)):
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if (x_min_text_only_h[ii] + 80) >= boxes[jj][0] and (x_min_text_only_h[ii] + 80) < boxes[jj][1] and y_cor_x_min_main_h[ii] >= boxes[jj][2] and y_cor_x_min_main_h[ii] < boxes[jj][3]:
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arg_text_con_h.append(jj)
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break
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arg_arg_text_con = np.argsort(arg_text_con_h)
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args_contours_h = np.array(range(len(arg_text_con_h)))
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order_by_con_head = np.zeros(len(arg_text_con_h))
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order_by_con_main = np.zeros(len(arg_text_con))
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ref_point = 0
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order_of_texts_tot = []
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id_of_texts_tot = []
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for iij in range(len(boxes)):
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args_contours_box = args_contours[np.array(arg_text_con) == iij]
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args_contours_box_h = args_contours_h[np.array(arg_text_con_h) == iij]
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con_inter_box = []
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con_inter_box_h = []
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for i in range(len(args_contours_box)):
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con_inter_box.append(contours_only_text_parent[args_contours_box[i]])
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for i in range(len(args_contours_box_h)):
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con_inter_box_h.append(contours_only_text_parent_h[args_contours_box_h[i]])
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indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2])
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order_of_texts, id_of_texts = order_and_id_of_texts(con_inter_box, con_inter_box_h, matrix_of_orders, indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
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indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1]
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indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1]
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indexes_sorted_head = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 2]
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indexes_by_type_head = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 2]
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zahler = 0
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for mtv in args_contours_box:
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arg_order_v = indexes_sorted_main[zahler]
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tartib = np.where(indexes_sorted == arg_order_v)[0][0]
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order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point
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zahler = zahler + 1
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zahler = 0
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for mtv in args_contours_box_h:
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arg_order_v = indexes_sorted_head[zahler]
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tartib = np.where(indexes_sorted == arg_order_v)[0][0]
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# print(indexes_sorted,np.where(indexes_sorted==arg_order_v ),arg_order_v,tartib,'inshgalla')
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order_by_con_head[args_contours_box_h[indexes_by_type_head[zahler]]] = tartib + ref_point
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zahler = zahler + 1
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for jji in range(len(id_of_texts)):
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order_of_texts_tot.append(order_of_texts[jji] + ref_point)
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id_of_texts_tot.append(id_of_texts[jji])
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ref_point = ref_point + len(id_of_texts)
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order_of_texts_tot = []
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for tj1 in range(len(contours_only_text_parent)):
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order_of_texts_tot.append(int(order_by_con_main[tj1]))
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for tj1 in range(len(contours_only_text_parent_h)):
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order_of_texts_tot.append(int(order_by_con_head[tj1]))
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order_text_new = []
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for iii in range(len(order_of_texts_tot)):
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tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0]
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order_text_new.append(tartib_new)
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except:
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arg_text_con = []
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for ii in range(len(cx_text_only)):
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for jj in range(len(boxes)):
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if cx_text_only[ii] >= boxes[jj][0] and cx_text_only[ii] < boxes[jj][1] and cy_text_only[ii] >= boxes[jj][2] and cy_text_only[ii] < boxes[jj][3]: # this is valid if the center of region identify in which box it is located
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arg_text_con.append(jj)
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break
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arg_arg_text_con = np.argsort(arg_text_con)
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args_contours = np.array(range(len(arg_text_con)))
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order_by_con_main = np.zeros(len(arg_text_con))
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############################# head
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arg_text_con_h = []
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for ii in range(len(cx_text_only_h)):
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for jj in range(len(boxes)):
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if cx_text_only_h[ii] >= boxes[jj][0] and cx_text_only_h[ii] < boxes[jj][1] and cy_text_only_h[ii] >= boxes[jj][2] and cy_text_only_h[ii] < boxes[jj][3]: # this is valid if the center of region identify in which box it is located
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arg_text_con_h.append(jj)
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break
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arg_arg_text_con_h = np.argsort(arg_text_con_h)
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args_contours_h = np.array(range(len(arg_text_con_h)))
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order_by_con_head = np.zeros(len(arg_text_con_h))
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ref_point = 0
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order_of_texts_tot = []
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id_of_texts_tot = []
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for iij in range(len(boxes)):
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args_contours_box = args_contours[np.array(arg_text_con) == iij]
|
||||
args_contours_box_h = args_contours_h[np.array(arg_text_con_h) == iij]
|
||||
con_inter_box = []
|
||||
con_inter_box_h = []
|
||||
|
||||
for i in range(len(args_contours_box)):
|
||||
|
||||
con_inter_box.append(contours_only_text_parent[args_contours_box[i]])
|
||||
for i in range(len(args_contours_box_h)):
|
||||
|
||||
con_inter_box_h.append(contours_only_text_parent_h[args_contours_box_h[i]])
|
||||
|
||||
indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2])
|
||||
|
||||
order_of_texts, id_of_texts = order_and_id_of_texts(con_inter_box, con_inter_box_h, matrix_of_orders, indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
|
||||
|
||||
indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_sorted_head = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
indexes_by_type_head = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box:
|
||||
arg_order_v = indexes_sorted_main[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box_h:
|
||||
arg_order_v = indexes_sorted_head[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
# print(indexes_sorted,np.where(indexes_sorted==arg_order_v ),arg_order_v,tartib,'inshgalla')
|
||||
order_by_con_head[args_contours_box_h[indexes_by_type_head[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
for jji in range(len(id_of_texts)):
|
||||
order_of_texts_tot.append(order_of_texts[jji] + ref_point)
|
||||
id_of_texts_tot.append(id_of_texts[jji])
|
||||
ref_point = ref_point + len(id_of_texts)
|
||||
|
||||
order_of_texts_tot = []
|
||||
for tj1 in range(len(contours_only_text_parent)):
|
||||
order_of_texts_tot.append(int(order_by_con_main[tj1]))
|
||||
|
||||
for tj1 in range(len(contours_only_text_parent_h)):
|
||||
order_of_texts_tot.append(int(order_by_con_head[tj1]))
|
||||
|
||||
order_text_new = []
|
||||
for iii in range(len(order_of_texts_tot)):
|
||||
tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0]
|
||||
order_text_new.append(tartib_new)
|
||||
return order_text_new, id_of_texts_tot
|
||||
|
||||
def do_order_of_regions_no_full_layout(self, contours_only_text_parent, contours_only_text_parent_h, boxes, textline_mask_tot):
|
||||
self.logger.debug("enter do_order_of_regions_no_full_layout")
|
||||
cx_text_only, cy_text_only, x_min_text_only, _, _, _, y_cor_x_min_main = find_new_features_of_contoures(contours_only_text_parent)
|
||||
|
||||
try:
|
||||
arg_text_con = []
|
||||
for ii in range(len(cx_text_only)):
|
||||
for jj in range(len(boxes)):
|
||||
if (x_min_text_only[ii] + 80) >= boxes[jj][0] and (x_min_text_only[ii] + 80) < boxes[jj][1] and y_cor_x_min_main[ii] >= boxes[jj][2] and y_cor_x_min_main[ii] < boxes[jj][3]:
|
||||
arg_text_con.append(jj)
|
||||
break
|
||||
arg_arg_text_con = np.argsort(arg_text_con)
|
||||
args_contours = np.array(range(len(arg_text_con)))
|
||||
|
||||
order_by_con_main = np.zeros(len(arg_text_con))
|
||||
|
||||
ref_point = 0
|
||||
order_of_texts_tot = []
|
||||
id_of_texts_tot = []
|
||||
for iij in range(len(boxes)):
|
||||
|
||||
args_contours_box = args_contours[np.array(arg_text_con) == iij]
|
||||
|
||||
con_inter_box = []
|
||||
con_inter_box_h = []
|
||||
|
||||
for i in range(len(args_contours_box)):
|
||||
con_inter_box.append(contours_only_text_parent[args_contours_box[i]])
|
||||
|
||||
indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2])
|
||||
|
||||
order_of_texts, id_of_texts = order_and_id_of_texts(con_inter_box, con_inter_box_h, matrix_of_orders, indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
|
||||
|
||||
indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_sorted_head = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
indexes_by_type_head = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box:
|
||||
arg_order_v = indexes_sorted_main[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
for jji in range(len(id_of_texts)):
|
||||
order_of_texts_tot.append(order_of_texts[jji] + ref_point)
|
||||
id_of_texts_tot.append(id_of_texts[jji])
|
||||
ref_point = ref_point + len(id_of_texts)
|
||||
|
||||
order_of_texts_tot = []
|
||||
for tj1 in range(len(contours_only_text_parent)):
|
||||
order_of_texts_tot.append(int(order_by_con_main[tj1]))
|
||||
|
||||
order_text_new = []
|
||||
for iii in range(len(order_of_texts_tot)):
|
||||
tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0]
|
||||
order_text_new.append(tartib_new)
|
||||
|
||||
except:
|
||||
arg_text_con = []
|
||||
for ii in range(len(cx_text_only)):
|
||||
for jj in range(len(boxes)):
|
||||
if cx_text_only[ii] >= boxes[jj][0] and cx_text_only[ii] < boxes[jj][1] and cy_text_only[ii] >= boxes[jj][2] and cy_text_only[ii] < boxes[jj][3]: # this is valid if the center of region identify in which box it is located
|
||||
arg_text_con.append(jj)
|
||||
break
|
||||
arg_arg_text_con = np.argsort(arg_text_con)
|
||||
args_contours = np.array(range(len(arg_text_con)))
|
||||
|
||||
order_by_con_main = np.zeros(len(arg_text_con))
|
||||
|
||||
ref_point = 0
|
||||
order_of_texts_tot = []
|
||||
id_of_texts_tot = []
|
||||
for iij in range(len(boxes)):
|
||||
args_contours_box = args_contours[np.array(arg_text_con) == iij]
|
||||
con_inter_box = []
|
||||
con_inter_box_h = []
|
||||
|
||||
for i in range(len(args_contours_box)):
|
||||
|
||||
con_inter_box.append(contours_only_text_parent[args_contours_box[i]])
|
||||
|
||||
indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2])
|
||||
|
||||
order_of_texts, id_of_texts = order_and_id_of_texts(con_inter_box, con_inter_box_h, matrix_of_orders, indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
|
||||
|
||||
indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_sorted_head = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
indexes_by_type_head = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box:
|
||||
arg_order_v = indexes_sorted_main[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
for jji in range(len(id_of_texts)):
|
||||
order_of_texts_tot.append(order_of_texts[jji] + ref_point)
|
||||
id_of_texts_tot.append(id_of_texts[jji])
|
||||
ref_point = ref_point + len(id_of_texts)
|
||||
|
||||
order_of_texts_tot = []
|
||||
for tj1 in range(len(contours_only_text_parent)):
|
||||
order_of_texts_tot.append(int(order_by_con_main[tj1]))
|
||||
|
||||
order_text_new = []
|
||||
for iii in range(len(order_of_texts_tot)):
|
||||
tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0]
|
||||
order_text_new.append(tartib_new)
|
||||
|
||||
return order_text_new, id_of_texts_tot
|
||||
|
||||
def do_order_of_regions(self, *args, **kwargs):
|
||||
if self.full_layout:
|
||||
cx_text_only, cy_text_only, x_min_text_only, _, _, _, y_cor_x_min_main = find_new_features_of_contoures(contours_only_text_parent)
|
||||
cx_text_only_h, cy_text_only_h, x_min_text_only_h, _, _, _, y_cor_x_min_main_h = find_new_features_of_contoures(contours_only_text_parent_h)
|
||||
|
||||
try:
|
||||
arg_text_con = []
|
||||
for ii in range(len(cx_text_only)):
|
||||
for jj in range(len(boxes)):
|
||||
if (x_min_text_only[ii] + 80) >= boxes[jj][0] and (x_min_text_only[ii] + 80) < boxes[jj][1] and y_cor_x_min_main[ii] >= boxes[jj][2] and y_cor_x_min_main[ii] < boxes[jj][3]:
|
||||
arg_text_con.append(jj)
|
||||
break
|
||||
arg_arg_text_con = np.argsort(arg_text_con)
|
||||
args_contours = np.array(range(len(arg_text_con)))
|
||||
|
||||
arg_text_con_h = []
|
||||
for ii in range(len(cx_text_only_h)):
|
||||
for jj in range(len(boxes)):
|
||||
if (x_min_text_only_h[ii] + 80) >= boxes[jj][0] and (x_min_text_only_h[ii] + 80) < boxes[jj][1] and y_cor_x_min_main_h[ii] >= boxes[jj][2] and y_cor_x_min_main_h[ii] < boxes[jj][3]:
|
||||
arg_text_con_h.append(jj)
|
||||
break
|
||||
arg_arg_text_con = np.argsort(arg_text_con_h)
|
||||
args_contours_h = np.array(range(len(arg_text_con_h)))
|
||||
|
||||
order_by_con_head = np.zeros(len(arg_text_con_h))
|
||||
order_by_con_main = np.zeros(len(arg_text_con))
|
||||
|
||||
ref_point = 0
|
||||
order_of_texts_tot = []
|
||||
id_of_texts_tot = []
|
||||
for iij in range(len(boxes)):
|
||||
|
||||
args_contours_box = args_contours[np.array(arg_text_con) == iij]
|
||||
args_contours_box_h = args_contours_h[np.array(arg_text_con_h) == iij]
|
||||
con_inter_box = []
|
||||
con_inter_box_h = []
|
||||
|
||||
for i in range(len(args_contours_box)):
|
||||
con_inter_box.append(contours_only_text_parent[args_contours_box[i]])
|
||||
|
||||
for i in range(len(args_contours_box_h)):
|
||||
con_inter_box_h.append(contours_only_text_parent_h[args_contours_box_h[i]])
|
||||
|
||||
indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2])
|
||||
|
||||
order_of_texts, id_of_texts = order_and_id_of_texts(con_inter_box, con_inter_box_h, matrix_of_orders, indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
|
||||
|
||||
indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_sorted_head = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
indexes_by_type_head = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box:
|
||||
arg_order_v = indexes_sorted_main[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box_h:
|
||||
arg_order_v = indexes_sorted_head[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
# print(indexes_sorted,np.where(indexes_sorted==arg_order_v ),arg_order_v,tartib,'inshgalla')
|
||||
order_by_con_head[args_contours_box_h[indexes_by_type_head[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
for jji in range(len(id_of_texts)):
|
||||
order_of_texts_tot.append(order_of_texts[jji] + ref_point)
|
||||
id_of_texts_tot.append(id_of_texts[jji])
|
||||
ref_point = ref_point + len(id_of_texts)
|
||||
|
||||
order_of_texts_tot = []
|
||||
for tj1 in range(len(contours_only_text_parent)):
|
||||
order_of_texts_tot.append(int(order_by_con_main[tj1]))
|
||||
|
||||
for tj1 in range(len(contours_only_text_parent_h)):
|
||||
order_of_texts_tot.append(int(order_by_con_head[tj1]))
|
||||
|
||||
order_text_new = []
|
||||
for iii in range(len(order_of_texts_tot)):
|
||||
tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0]
|
||||
order_text_new.append(tartib_new)
|
||||
|
||||
except:
|
||||
arg_text_con = []
|
||||
for ii in range(len(cx_text_only)):
|
||||
for jj in range(len(boxes)):
|
||||
if cx_text_only[ii] >= boxes[jj][0] and cx_text_only[ii] < boxes[jj][1] and cy_text_only[ii] >= boxes[jj][2] and cy_text_only[ii] < boxes[jj][3]: # this is valid if the center of region identify in which box it is located
|
||||
arg_text_con.append(jj)
|
||||
break
|
||||
arg_arg_text_con = np.argsort(arg_text_con)
|
||||
args_contours = np.array(range(len(arg_text_con)))
|
||||
|
||||
order_by_con_main = np.zeros(len(arg_text_con))
|
||||
|
||||
############################# head
|
||||
|
||||
arg_text_con_h = []
|
||||
for ii in range(len(cx_text_only_h)):
|
||||
for jj in range(len(boxes)):
|
||||
if cx_text_only_h[ii] >= boxes[jj][0] and cx_text_only_h[ii] < boxes[jj][1] and cy_text_only_h[ii] >= boxes[jj][2] and cy_text_only_h[ii] < boxes[jj][3]: # this is valid if the center of region identify in which box it is located
|
||||
arg_text_con_h.append(jj)
|
||||
break
|
||||
arg_arg_text_con_h = np.argsort(arg_text_con_h)
|
||||
args_contours_h = np.array(range(len(arg_text_con_h)))
|
||||
|
||||
order_by_con_head = np.zeros(len(arg_text_con_h))
|
||||
|
||||
ref_point = 0
|
||||
order_of_texts_tot = []
|
||||
id_of_texts_tot = []
|
||||
for iij in range(len(boxes)):
|
||||
args_contours_box = args_contours[np.array(arg_text_con) == iij]
|
||||
args_contours_box_h = args_contours_h[np.array(arg_text_con_h) == iij]
|
||||
con_inter_box = []
|
||||
con_inter_box_h = []
|
||||
|
||||
for i in range(len(args_contours_box)):
|
||||
|
||||
con_inter_box.append(contours_only_text_parent[args_contours_box[i]])
|
||||
for i in range(len(args_contours_box_h)):
|
||||
|
||||
con_inter_box_h.append(contours_only_text_parent_h[args_contours_box_h[i]])
|
||||
|
||||
indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2])
|
||||
|
||||
order_of_texts, id_of_texts = order_and_id_of_texts(con_inter_box, con_inter_box_h, matrix_of_orders, indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
|
||||
|
||||
indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_sorted_head = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
indexes_by_type_head = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box:
|
||||
arg_order_v = indexes_sorted_main[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box_h:
|
||||
arg_order_v = indexes_sorted_head[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
# print(indexes_sorted,np.where(indexes_sorted==arg_order_v ),arg_order_v,tartib,'inshgalla')
|
||||
order_by_con_head[args_contours_box_h[indexes_by_type_head[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
for jji in range(len(id_of_texts)):
|
||||
order_of_texts_tot.append(order_of_texts[jji] + ref_point)
|
||||
id_of_texts_tot.append(id_of_texts[jji])
|
||||
ref_point = ref_point + len(id_of_texts)
|
||||
|
||||
order_of_texts_tot = []
|
||||
for tj1 in range(len(contours_only_text_parent)):
|
||||
order_of_texts_tot.append(int(order_by_con_main[tj1]))
|
||||
|
||||
for tj1 in range(len(contours_only_text_parent_h)):
|
||||
order_of_texts_tot.append(int(order_by_con_head[tj1]))
|
||||
|
||||
order_text_new = []
|
||||
for iii in range(len(order_of_texts_tot)):
|
||||
tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0]
|
||||
order_text_new.append(tartib_new)
|
||||
return order_text_new, id_of_texts_tot
|
||||
|
||||
else:
|
||||
cx_text_only, cy_text_only, x_min_text_only, _, _, _, y_cor_x_min_main = find_new_features_of_contoures(contours_only_text_parent)
|
||||
|
||||
try:
|
||||
arg_text_con = []
|
||||
for ii in range(len(cx_text_only)):
|
||||
for jj in range(len(boxes)):
|
||||
if (x_min_text_only[ii] + 80) >= boxes[jj][0] and (x_min_text_only[ii] + 80) < boxes[jj][1] and y_cor_x_min_main[ii] >= boxes[jj][2] and y_cor_x_min_main[ii] < boxes[jj][3]:
|
||||
arg_text_con.append(jj)
|
||||
break
|
||||
arg_arg_text_con = np.argsort(arg_text_con)
|
||||
args_contours = np.array(range(len(arg_text_con)))
|
||||
|
||||
order_by_con_main = np.zeros(len(arg_text_con))
|
||||
|
||||
ref_point = 0
|
||||
order_of_texts_tot = []
|
||||
id_of_texts_tot = []
|
||||
for iij in range(len(boxes)):
|
||||
|
||||
args_contours_box = args_contours[np.array(arg_text_con) == iij]
|
||||
|
||||
con_inter_box = []
|
||||
con_inter_box_h = []
|
||||
|
||||
for i in range(len(args_contours_box)):
|
||||
con_inter_box.append(contours_only_text_parent[args_contours_box[i]])
|
||||
|
||||
indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2])
|
||||
|
||||
order_of_texts, id_of_texts = order_and_id_of_texts(con_inter_box, con_inter_box_h, matrix_of_orders, indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
|
||||
|
||||
indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_sorted_head = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
indexes_by_type_head = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box:
|
||||
arg_order_v = indexes_sorted_main[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
for jji in range(len(id_of_texts)):
|
||||
order_of_texts_tot.append(order_of_texts[jji] + ref_point)
|
||||
id_of_texts_tot.append(id_of_texts[jji])
|
||||
ref_point = ref_point + len(id_of_texts)
|
||||
|
||||
order_of_texts_tot = []
|
||||
for tj1 in range(len(contours_only_text_parent)):
|
||||
order_of_texts_tot.append(int(order_by_con_main[tj1]))
|
||||
|
||||
order_text_new = []
|
||||
for iii in range(len(order_of_texts_tot)):
|
||||
tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0]
|
||||
order_text_new.append(tartib_new)
|
||||
|
||||
except:
|
||||
arg_text_con = []
|
||||
for ii in range(len(cx_text_only)):
|
||||
for jj in range(len(boxes)):
|
||||
if cx_text_only[ii] >= boxes[jj][0] and cx_text_only[ii] < boxes[jj][1] and cy_text_only[ii] >= boxes[jj][2] and cy_text_only[ii] < boxes[jj][3]: # this is valid if the center of region identify in which box it is located
|
||||
arg_text_con.append(jj)
|
||||
break
|
||||
arg_arg_text_con = np.argsort(arg_text_con)
|
||||
args_contours = np.array(range(len(arg_text_con)))
|
||||
|
||||
order_by_con_main = np.zeros(len(arg_text_con))
|
||||
|
||||
ref_point = 0
|
||||
order_of_texts_tot = []
|
||||
id_of_texts_tot = []
|
||||
for iij in range(len(boxes)):
|
||||
args_contours_box = args_contours[np.array(arg_text_con) == iij]
|
||||
con_inter_box = []
|
||||
con_inter_box_h = []
|
||||
|
||||
for i in range(len(args_contours_box)):
|
||||
|
||||
con_inter_box.append(contours_only_text_parent[args_contours_box[i]])
|
||||
|
||||
indexes_sorted, matrix_of_orders, kind_of_texts_sorted, index_by_kind_sorted = order_of_regions(textline_mask_tot[int(boxes[iij][2]) : int(boxes[iij][3]), int(boxes[iij][0]) : int(boxes[iij][1])], con_inter_box, con_inter_box_h, boxes[iij][2])
|
||||
|
||||
order_of_texts, id_of_texts = order_and_id_of_texts(con_inter_box, con_inter_box_h, matrix_of_orders, indexes_sorted, index_by_kind_sorted, kind_of_texts_sorted, ref_point)
|
||||
|
||||
indexes_sorted_main = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_by_type_main = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 1]
|
||||
indexes_sorted_head = np.array(indexes_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
indexes_by_type_head = np.array(index_by_kind_sorted)[np.array(kind_of_texts_sorted) == 2]
|
||||
|
||||
zahler = 0
|
||||
for mtv in args_contours_box:
|
||||
arg_order_v = indexes_sorted_main[zahler]
|
||||
tartib = np.where(indexes_sorted == arg_order_v)[0][0]
|
||||
order_by_con_main[args_contours_box[indexes_by_type_main[zahler]]] = tartib + ref_point
|
||||
zahler = zahler + 1
|
||||
|
||||
for jji in range(len(id_of_texts)):
|
||||
order_of_texts_tot.append(order_of_texts[jji] + ref_point)
|
||||
id_of_texts_tot.append(id_of_texts[jji])
|
||||
ref_point = ref_point + len(id_of_texts)
|
||||
|
||||
order_of_texts_tot = []
|
||||
for tj1 in range(len(contours_only_text_parent)):
|
||||
order_of_texts_tot.append(int(order_by_con_main[tj1]))
|
||||
|
||||
order_text_new = []
|
||||
for iii in range(len(order_of_texts_tot)):
|
||||
tartib_new = np.where(np.array(order_of_texts_tot) == iii)[0][0]
|
||||
order_text_new.append(tartib_new)
|
||||
|
||||
return order_text_new, id_of_texts_tot
|
||||
return self.do_order_of_regions_full_layout(*args, **kwargs)
|
||||
return self.do_order_of_regions_no_full_layout(*args, **kwargs)
|
||||
|
||||
def run(self):
|
||||
"""
|
||||
Get image and scales, then extract the page of scanned image
|
||||
"""
|
||||
self.logger.debug("enter run")
|
||||
is_image_enhanced = False
|
||||
# get image and sclaes, then extract the page of scanned image
|
||||
t1 = time.time()
|
||||
|
||||
##########
|
||||
|
|
@ -2230,7 +2252,7 @@ class eynollah:
|
|||
#print(np.unique(textline_mask_tot_ea[:, :]), "textline")
|
||||
if self.plotter:
|
||||
self.plotter.save_plot_of_textlines(textline_mask_tot_ea, image_page)
|
||||
print("textline: " + str(time.time() - t1))
|
||||
self.logger.info("textline detection took %ss", str(time.time() - t1))
|
||||
# plt.imshow(textline_mask_tot_ea)
|
||||
# plt.show()
|
||||
# sys.exit()
|
||||
|
|
@ -2243,12 +2265,12 @@ class eynollah:
|
|||
if self.plotter:
|
||||
self.plotter.save_deskewed_image(slope_deskew)
|
||||
# img_rotated=rotyate_image_different(self.image_org,slope_deskew)
|
||||
print(slope_deskew, "slope_deskew")
|
||||
self.logger.info("slope_deskew: %s", slope_deskew)
|
||||
|
||||
##plt.imshow(img_rotated)
|
||||
##plt.show()
|
||||
##sys.exit()
|
||||
print("deskewing: " + str(time.time() - t1))
|
||||
self.logger.info("deskewing: " + str(time.time() - t1))
|
||||
|
||||
image_page_rotated, textline_mask_tot = image_page[:, :], textline_mask_tot_ea[:, :]
|
||||
textline_mask_tot[mask_images[:, :] == 1] = 0
|
||||
|
|
@ -2278,7 +2300,7 @@ class eynollah:
|
|||
self.plotter.save_plot_of_layout_main_all(text_regions_p, image_page)
|
||||
self.plotter.save_plot_of_layout_main(text_regions_p, image_page)
|
||||
|
||||
print("marginals: " + str(time.time() - t1))
|
||||
self.logger.info("detection of marginals took %ss", str(time.time() - t1))
|
||||
|
||||
if not self.full_layout:
|
||||
|
||||
|
|
@ -2298,8 +2320,7 @@ class eynollah:
|
|||
K.clear_session()
|
||||
gc.collect()
|
||||
|
||||
# print(peaks_neg_fin,num_col,'num_col2')
|
||||
print(num_col_classifier, "num_col_classifier")
|
||||
self.logger.info("num_col_classifier: %s", num_col_classifier)
|
||||
|
||||
if num_col_classifier >= 3:
|
||||
if np.abs(slope_deskew) < SLOPE_THRESHOLD:
|
||||
|
|
@ -2323,9 +2344,8 @@ class eynollah:
|
|||
else:
|
||||
boxes_d = return_boxes_of_images_by_order_of_reading_new(spliter_y_new_d, regions_without_seperators_d, matrix_of_lines_ch_d, num_col_classifier)
|
||||
|
||||
# print(len(boxes),'boxes')
|
||||
# sys.exit()
|
||||
print("boxes in: " + str(time.time() - t1))
|
||||
self.logger.debug("len(boxes): %s", len(boxes))
|
||||
self.logger.info("detecting boxes took %ss", str(time.time() - t1))
|
||||
img_revised_tab = text_regions_p[:, :]
|
||||
pixel_img = 2
|
||||
polygons_of_images = return_contours_of_interested_region(img_revised_tab, pixel_img)
|
||||
|
|
@ -2412,7 +2432,7 @@ class eynollah:
|
|||
K.clear_session()
|
||||
gc.collect()
|
||||
img_revised_tab = np.copy(text_regions_p[:, :])
|
||||
print("full layout in: " + str(time.time() - t1))
|
||||
self.logger.info("detection of full layout took %ss", str(time.time() - t1))
|
||||
pixel_img = 5
|
||||
polygons_of_images = return_contours_of_interested_region(img_revised_tab, pixel_img)
|
||||
|
||||
|
|
@ -2638,7 +2658,7 @@ class eynollah:
|
|||
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)
|
||||
else:
|
||||
contours_only_text_parent_h = None
|
||||
# print('bura galmir?')
|
||||
# self.logger.debug('bura galmir?')
|
||||
if np.abs(slope_deskew) < SLOPE_THRESHOLD:
|
||||
#contours_only_text_parent = list(np.array(contours_only_text_parent)[index_by_text_par_con])
|
||||
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)
|
||||
|
|
@ -2648,4 +2668,4 @@ class eynollah:
|
|||
# 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)
|
||||
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)
|
||||
|
||||
print("Job done in: " + str(time.time() - t1))
|
||||
self.logger.info("Job done in %ss", str(time.time() - t1))
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue