Merge pull request #102 from qurator-spk/right2left_reading_order

Right2left reading order

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,

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()

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)):
 
                 
@@ -2028,6 +2036,7 @@ 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]])
+            
+    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