diff --git a/qurator/eynollah/cli.py b/qurator/eynollah/cli.py index 4bbd3f2..a2a2ad0 100644 --- a/qurator/eynollah/cli.py +++ b/qurator/eynollah/cli.py @@ -97,6 +97,12 @@ from qurator.eynollah.eynollah import Eynollah is_flag=True, help="if this parameter set to true, this tool will try to detect tables.", ) +@click.option( + "--right2left/--left2right", + "-r2l/-l2r", + is_flag=True, + help="if this parameter set to true, this tool will extract right-to-left reading order.", +) @click.option( "--input_binary/--input-RGB", "-ib/-irgb", @@ -149,6 +155,7 @@ def main( textline_light, full_layout, tables, + right2left, input_binary, allow_scaling, headers_off, @@ -184,6 +191,7 @@ def main( textline_light=textline_light, full_layout=full_layout, tables=tables, + right2left=right2left, input_binary=input_binary, allow_scaling=allow_scaling, headers_off=headers_off, diff --git a/qurator/eynollah/eynollah.py b/qurator/eynollah/eynollah.py index a408b42..ad3f312 100644 --- a/qurator/eynollah/eynollah.py +++ b/qurator/eynollah/eynollah.py @@ -158,6 +158,7 @@ class Eynollah: textline_light=False, full_layout=False, tables=False, + right2left=False, input_binary=False, allow_scaling=False, headers_off=False, @@ -189,6 +190,7 @@ class Eynollah: self.textline_light = textline_light self.full_layout = full_layout self.tables = tables + self.right2left = right2left self.input_binary = input_binary self.allow_scaling = allow_scaling self.headers_off = headers_off @@ -2069,6 +2071,7 @@ class Eynollah: arg_text_con = [] for ii in range(len(cx_text_only)): for jj in range(len(boxes)): + print(cx_text_only[ii],cy_text_only[ii],'markaz') 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 @@ -2104,6 +2107,9 @@ class Eynollah: ref_point += len(id_of_texts) order_of_texts_tot = [] + print(len(contours_only_text_parent),'contours_only_text_parent') + print(len(order_by_con_main),'order_by_con_main') + for tj1 in range(len(contours_only_text_parent)): order_of_texts_tot.append(int(order_by_con_main[tj1])) @@ -2618,7 +2624,7 @@ class Eynollah: regions_without_separators_d = cv2.erode(regions_without_separators_d[:, :], KERNEL, iterations=6) t1 = time.time() if np.abs(slope_deskew) < SLOPE_THRESHOLD: - boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables) + boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables, self.right2left) boxes_d = None self.logger.debug("len(boxes): %s", len(boxes)) @@ -2628,7 +2634,7 @@ class Eynollah: img_revised_tab2 = self.add_tables_heuristic_to_layout(text_regions_p_tables, boxes, 0, splitter_y_new, peaks_neg_tot_tables, text_regions_p_tables , num_col_classifier , 0.000005, pixel_line) img_revised_tab2, contoures_tables = self.check_iou_of_bounding_box_and_contour_for_tables(img_revised_tab2,table_prediction, 10, num_col_classifier) else: - boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables) + boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables, self.right2left) boxes = None self.logger.debug("len(boxes): %s", len(boxes_d)) @@ -2713,7 +2719,7 @@ class Eynollah: pass if np.abs(slope_deskew) < SLOPE_THRESHOLD: - boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables) + boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables, self.right2left) text_regions_p_tables = np.copy(text_regions_p) text_regions_p_tables[:,:][(table_prediction[:,:]==1)] = 10 pixel_line = 3 @@ -2722,7 +2728,7 @@ class Eynollah: img_revised_tab2,contoures_tables = self.check_iou_of_bounding_box_and_contour_for_tables(img_revised_tab2, table_prediction, 10, num_col_classifier) else: - boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables) + boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables, self.right2left) text_regions_p_tables = np.copy(text_regions_p_1_n) text_regions_p_tables = np.round(text_regions_p_tables) text_regions_p_tables[:,:][(text_regions_p_tables[:,:]!=3) & (table_prediction_n[:,:]==1)] = 10 @@ -3065,10 +3071,17 @@ class Eynollah: if np.abs(slope_deskew) < SLOPE_THRESHOLD: - boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables) + boxes, peaks_neg_tot_tables = return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, self.tables, self.right2left) else: - boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables) - + boxes_d, peaks_neg_tot_tables_d = return_boxes_of_images_by_order_of_reading_new(splitter_y_new_d, regions_without_separators_d, matrix_of_lines_ch_d, num_col_classifier, erosion_hurts, self.tables, self.right2left) + + #print(boxes_d,'boxes_d') + #img_once = np.zeros((textline_mask_tot_d.shape[0],textline_mask_tot_d.shape[1])) + #for box_i in boxes_d: + #img_once[int(box_i[2]):int(box_i[3]),int(box_i[0]):int(box_i[1]) ] =1 + #plt.imshow(img_once) + #plt.show() + #print(np.unique(img_once),'img_once') if self.plotter: self.plotter.write_images_into_directory(polygons_of_images, image_page) t_order = time.time() diff --git a/qurator/eynollah/utils/__init__.py b/qurator/eynollah/utils/__init__.py index e9f872c..b85abdf 100644 --- a/qurator/eynollah/utils/__init__.py +++ b/qurator/eynollah/utils/__init__.py @@ -1672,7 +1672,9 @@ def find_number_of_columns_in_document(region_pre_p, num_col_classifier, tables, return num_col_fin, peaks_neg_fin_fin,matrix_of_lines_ch,splitter_y_new,separators_closeup_n -def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, tables): +def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_without_separators, matrix_of_lines_ch, num_col_classifier, erosion_hurts, tables, right2left_readingorder): + if right2left_readingorder: + regions_without_separators = cv2.flip(regions_without_separators,1) boxes=[] peaks_neg_tot_tables = [] @@ -1763,6 +1765,13 @@ def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_witho cy_hor_diff=matrix_new[:,7][ (matrix_new[:,9]==0) ] arg_org_hor_some=matrix_new[:,0][ (matrix_new[:,9]==0) ] + if right2left_readingorder: + x_max_hor_some_new = regions_without_separators.shape[1] - x_min_hor_some + x_min_hor_some_new = regions_without_separators.shape[1] - x_max_hor_some + + x_min_hor_some =list(np.copy(x_min_hor_some_new)) + x_max_hor_some =list(np.copy(x_max_hor_some_new)) + @@ -1774,7 +1783,6 @@ def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_witho reading_order_type,x_starting,x_ending,y_type_2,y_diff_type_2,y_lines_without_mother,x_start_without_mother,x_end_without_mother,there_is_sep_with_child,y_lines_with_child_without_mother,x_start_with_child_without_mother,x_end_with_child_without_mother,new_main_sep_y=return_x_start_end_mothers_childs_and_type_of_reading_order(x_min_hor_some,x_max_hor_some,cy_hor_some,peaks_neg_tot,cy_hor_diff) - if (reading_order_type==1) or (reading_order_type==0 and (len(y_lines_without_mother)>=2 or there_is_sep_with_child==1)): @@ -2027,6 +2035,7 @@ def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_witho columns_not_covered_child_no_mother=np.sort(columns_not_covered_child_no_mother) + ind_args=np.array(range(len(y_type_2))) @@ -2281,7 +2290,6 @@ def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_witho ind_args=np.array(range(len(y_type_2))) #ind_args=np.array(ind_args) - #print(ind_args,'ind_args') for column in range(len(peaks_neg_tot)-1): #print(column,'column') ind_args_in_col=ind_args[x_starting==column] @@ -2337,4 +2345,21 @@ def return_boxes_of_images_by_order_of_reading_new(splitter_y_new, regions_witho #else: #boxes.append([ 0, regions_without_separators[:,:].shape[1] ,splitter_y_new[i],splitter_y_new[i+1]]) - return boxes, peaks_neg_tot_tables + + if right2left_readingorder: + peaks_neg_tot_tables_new = [] + if len(peaks_neg_tot_tables)>=1: + for peaks_tab_ind in peaks_neg_tot_tables: + peaks_neg_tot_tables_ind = regions_without_separators.shape[1] - np.array(peaks_tab_ind) + peaks_neg_tot_tables_ind = list(peaks_neg_tot_tables_ind[::-1]) + peaks_neg_tot_tables_new.append(peaks_neg_tot_tables_ind) + + + for i in range(len(boxes)): + x_start_new = regions_without_separators.shape[1] - boxes[i][1] + x_end_new = regions_without_separators.shape[1] - boxes[i][0] + boxes[i][0] = x_start_new + boxes[i][1] = x_end_new + return boxes, peaks_neg_tot_tables_new + else: + return boxes, peaks_neg_tot_tables