postprocessing of textline contour dilation + skip layout and reading order passed as an argument

qurator/eynollah/cli.py

@@ -201,6 +201,12 @@ def machine_based_reading_order(dir_xml, dir_out_modal_image, dir_out_classes, i
     "-ncl",
     help="upper limit of columns in document image",
 )
+@click.option(
+    "--skip_layout_and_reading_order",
+    "-slro/-noslro",
+    is_flag=True,
+    help="if this parameter set to true, this tool will ignore layout detection and reading order. It means that textline detection will be done within printspace and contours of textline will be written in xml output file.",
+)
 @click.option(
     "--log_level",
     "-l",
@@ -208,7 +214,7 @@ def machine_based_reading_order(dir_xml, dir_out_modal_image, dir_out_classes, i
     help="Override log level globally to this",
 )
 
-def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, save_all, save_page, enable_plotting, allow_enhancement, curved_line, textline_light, full_layout, tables, right2left, input_binary, allow_scaling, headers_off, light_version, reading_order_machine_based, do_ocr, num_col_upper, num_col_lower, ignore_page_extraction, log_level):
+def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, save_all, save_page, enable_plotting, allow_enhancement, curved_line, textline_light, full_layout, tables, right2left, input_binary, allow_scaling, headers_off, light_version, reading_order_machine_based, do_ocr, num_col_upper, num_col_lower, skip_layout_and_reading_order, ignore_page_extraction, log_level):
     if log_level:
         setOverrideLogLevel(log_level)
     initLogging()
@@ -247,6 +253,7 @@ def layout(image, out, dir_in, model, save_images, save_layout, save_deskewed, s
         do_ocr=do_ocr,
         num_col_upper=num_col_upper,
         num_col_lower=num_col_lower,
+        skip_layout_and_reading_order=skip_layout_and_reading_order,
     )
     if dir_in:
         eynollah.run()

qurator/eynollah/eynollah.py

@@ -180,6 +180,7 @@ class Eynollah:
         do_ocr=False,
         num_col_upper=None,
         num_col_lower=None,
+        skip_layout_and_reading_order = False,
         override_dpi=None,
         logger=None,
         pcgts=None,
@@ -213,6 +214,7 @@ class Eynollah:
         self.allow_scaling = allow_scaling
         self.headers_off = headers_off
         self.ignore_page_extraction = ignore_page_extraction
+        self.skip_layout_and_reading_order = skip_layout_and_reading_order
         self.ocr = do_ocr
         if num_col_upper:
             self.num_col_upper = int(num_col_upper)
@@ -1951,7 +1953,7 @@ class Eynollah:
         q.put(slopes_sub)
         poly.put(poly_sub)
         box_sub.put(boxes_sub_new)
-    def get_regions_light_v(self,img,is_image_enhanced, num_col_classifier, skip_layout_ro=False):
+    def get_regions_light_v(self,img,is_image_enhanced, num_col_classifier, skip_layout_and_reading_order=False):
         self.logger.debug("enter get_regions_light_v")
         t_in = time.time()
         erosion_hurts = False
@@ -2019,7 +2021,7 @@ class Eynollah:
         
         textline_mask_tot_ea = resize_image(textline_mask_tot_ea,img_height_h, img_width_h )
         
-        if not skip_layout_ro:
+        if not skip_layout_and_reading_order:
             #print("inside 2 ", time.time()-t_in)
             
             #print(img_resized.shape, num_col_classifier, "num_col_classifier")
@@ -3818,6 +3820,30 @@ class Eynollah:
     def return_list_of_contours_with_desired_order(self, ls_cons, sorted_indexes):
         return [ls_cons[sorted_indexes[index]] for index in range(len(sorted_indexes))]
     
+    def return_it_in_two_groups(self,x_differential):
+        split = [ind if x_differential[ind]!=x_differential[ind+1] else -1 for ind in range(len(x_differential)-1)]
+
+        split_masked = list( np.array(split[:])[np.array(split[:])!=-1] )
+
+        if 0 not in split_masked:
+            split_masked.insert(0, -1)
+
+        split_masked.append(len(x_differential)-1)
+
+        split_masked = np.array(split_masked) +1
+
+        sums = [np.sum(x_differential[split_masked[ind]:split_masked[ind+1]]) for ind in range(len(split_masked)-1)]
+
+        indexes_to_bec_changed = [ind if ( np.abs(sums[ind-1]) > np.abs(sums[ind]) and  np.abs(sums[ind+1]) > np.abs(sums[ind])) else -1 for ind in range(1,len(sums)-1)  ]
+
+        indexes_to_bec_changed_filtered = np.array(indexes_to_bec_changed)[np.array(indexes_to_bec_changed)!=-1]
+
+        x_differential_new = np.copy(x_differential)
+        for i in indexes_to_bec_changed_filtered:
+            x_differential_new[split_masked[i]:split_masked[i+1]] = -1*np.array(x_differential)[split_masked[i]:split_masked[i+1]]
+            
+        return x_differential_new
+    
     def dilate_textlines(self,all_found_textline_polygons):
         for i in range(len(all_found_textline_polygons[0])):
             con_ind = all_found_textline_polygons[0][i]
@@ -3863,6 +3889,8 @@ class Eynollah:
                 
                 y_differential = [-1 if y_differential[ind]<0 else 1 for ind in range(len(y_differential))]
                 
+                y_differential = self.return_it_in_two_groups(y_differential)
+                
                 y_differential = np.array(y_differential)
                 
                 
@@ -3890,7 +3918,6 @@ class Eynollah:
             
             
             else:
-            
                 y_biger_than_x = np.abs(y_differential) > np.abs(x_differential)
                 
                 mult = y_biger_than_x*y_differential
@@ -3918,8 +3945,10 @@ class Eynollah:
                 
                 x_differential = [-1 if x_differential[ind]<0 else 1 for ind in range(len(x_differential))]
                 
+                x_differential = self.return_it_in_two_groups(x_differential)
                 x_differential = np.array(x_differential)
                 
+                
                 con_scaled = con_ind*1
                 
                 con_scaled[:,0, 1] = con_ind[:,0,1] + 8*x_differential
@@ -3949,8 +3978,6 @@ class Eynollah:
         Get image and scales, then extract the page of scanned image
         """
         self.logger.debug("enter run")
-        
-        skip_layout_ro = True
 
         t0_tot = time.time()
 
@@ -3968,7 +3995,7 @@ class Eynollah:
             self.logger.info("Enhancing took %.1fs ", time.time() - t0)
             #print("text region early -1 in %.1fs", time.time() - t0)
             t1 = time.time()
-            if not skip_layout_ro:
+            if not self.skip_layout_and_reading_order:
                 if self.light_version:
                     text_regions_p_1 ,erosion_hurts, polygons_lines_xml, textline_mask_tot_ea, img_bin_light = self.get_regions_light_v(img_res, is_image_enhanced, num_col_classifier)
                     #print("text region early -2 in %.1fs", time.time() - t0)
@@ -4356,7 +4383,7 @@ class Eynollah:
                         return pcgts
                 #print("text region early 7 in %.1fs", time.time() - t0)
             else:
-                _ ,_, _, textline_mask_tot_ea, img_bin_light = self.get_regions_light_v(img_res, is_image_enhanced, num_col_classifier, skip_layout_ro=skip_layout_ro)
+                _ ,_, _, textline_mask_tot_ea, img_bin_light = self.get_regions_light_v(img_res, is_image_enhanced, num_col_classifier, skip_layout_and_reading_order=self.skip_layout_and_reading_order)
                 
                 page_coord, image_page, textline_mask_tot_ea, img_bin_light, cont_page = self.run_graphics_and_columns_without_layout(textline_mask_tot_ea, img_bin_light)