🎨 unncesssary if True

sbb_newspapers_org_image/eynollah.py

@@ -171,17 +171,9 @@ class eynollah:
 
         if img.shape[1] < img_width_model:
             img = cv2.resize(img, (img_height_model, img.shape[0]), interpolation=cv2.INTER_NEAREST)
-
-        margin = True
-
-        if margin:
-            kernel = np.ones((5, 5), np.uint8)
-
         margin = int(0 * img_width_model)
-
         width_mid = img_width_model - 2 * margin
         height_mid = img_height_model - 2 * margin
-
         img = img / float(255.0)
 
         img_h = img.shape[0]
@@ -203,7 +195,6 @@ class eynollah:
                 else:
                     index_x_d = i * width_mid
                     index_x_u = index_x_d + img_width_model
-
                 if j == 0:
                     index_y_d = j * height_mid
                     index_y_u = index_y_d + img_height_model
@@ -254,9 +245,6 @@ class eynollah:
 
         prediction_true = prediction_true.astype(int)
 
-            del model_enhancement
-            del session_enhancemnet
-
         return prediction_true
 
     def calculate_width_height_by_columns(self, img, num_col, width_early, label_p_pred):
@@ -1252,7 +1240,6 @@ class eynollah:
         id_indexer_l = 0
         if len(found_polygons_text_region) > 0:
             self.xml_reading_order(page, order_of_texts, id_of_texts, id_of_marginalia, found_polygons_marginals)
-
             for mm in range(len(found_polygons_text_region)):
                 textregion = ET.SubElement(page, 'TextRegion')
                 textregion.set('id', 'r%s' % id_indexer)
@@ -1282,9 +1269,9 @@ class eynollah:
                                 points_co += ','
                                 points_co += str(int((all_found_texline_polygons[mm][j][l][1] + page_coord[0]) / self.scale_y))
                             else:
-                                points_co = points_co + str(int((all_found_texline_polygons[mm][j][l][0][0] + page_coord[2]) / self.scale_x))
-                                points_co = points_co + ','
-                                points_co = points_co + str(int((all_found_texline_polygons[mm][j][l][0][1] + page_coord[0]) / self.scale_y))
+                                points_co += str(int((all_found_texline_polygons[mm][j][l][0][0] + page_coord[2]) / self.scale_x))
+                                points_co += ','
+                                points_co += str(int((all_found_texline_polygons[mm][j][l][0][1] + page_coord[0]) / self.scale_y))
                         elif curved_line and abs(slopes[mm]) > 45:
                             if len(all_found_texline_polygons[mm][j][l]) == 2:
                                 points_co += str(int((all_found_texline_polygons[mm][j][l][0] + all_box_coord[mm][2] + page_coord[2]) / self.scale_x))
@@ -1298,7 +1285,6 @@ class eynollah:
                         if l < len(all_found_texline_polygons[mm][j]) - 1:
                             points_co += ' '
                     coord.set('points', points_co)
-
                 add_textequiv(textregion)
 
         for mm in range(len(found_polygons_marginals)):
@@ -2002,12 +1988,13 @@ class eynollah:
         text_regions_p = text_regions_p_1[:, :]  # long_short_region[:,:]#self.get_regions_from_2_models(image_page)
         text_regions_p = np.array(text_regions_p)
 
-        if num_col_classifier == 1 or num_col_classifier == 2:
+        if num_col_classifier in (1, 2):
             try:
                 regions_without_seperators = (text_regions_p[:, :] == 1) * 1
                 regions_without_seperators = regions_without_seperators.astype(np.uint8)
                 text_regions_p = get_marginals(rotate_image(regions_without_seperators, slope_deskew), text_regions_p, num_col_classifier, slope_deskew, kernel=self.kernel)
-            except:
+            except Exception as e:
+                self.logger.error("exception %s", e)
                 pass
 
         if self.plotter: