simplify dir_in conditionals

src/eynollah/eynollah.py

@@ -274,7 +274,8 @@ class Eynollah:
         
         self.models = {}
         
-        if dir_in and light_version:
+        if dir_in:
+            # as in start_new_session:
             config = tf.compat.v1.ConfigProto()
             config.gpu_options.allow_growth = True
             session = tf.compat.v1.Session(config=config)
@@ -283,62 +284,31 @@ class Eynollah:
             self.model_page = self.our_load_model(self.model_page_dir)
             self.model_classifier = self.our_load_model(self.model_dir_of_col_classifier)
             self.model_bin = self.our_load_model(self.model_dir_of_binarization)
-            self.model_textline = self.our_load_model(self.model_textline_dir)
-            self.model_region = self.our_load_model(self.model_region_dir_p_ens_light)
-            self.model_region_1_2 = self.our_load_model(self.model_region_dir_p_1_2_sp_np)
-            ###self.model_region_fl_new = self.our_load_model(self.model_region_dir_fully_new)
-            self.model_region_fl_np = self.our_load_model(self.model_region_dir_fully_np)
-            self.model_region_fl = self.our_load_model(self.model_region_dir_fully)
-            self.model_reading_order = self.our_load_model(self.model_reading_order_dir)
-            if self.ocr:
-                self.model_ocr = VisionEncoderDecoderModel.from_pretrained(self.model_ocr_dir)
-                self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
-                self.processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")#("microsoft/trocr-base-printed")#("microsoft/trocr-base-handwritten")
-            if self.tables:
-                self.model_table = self.our_load_model(self.model_table_dir)
-                
-            
-            self.ls_imgs  = os.listdir(self.dir_in)
-            
-        if dir_in and self.extract_only_images:
-            config = tf.compat.v1.ConfigProto()
-            config.gpu_options.allow_growth = True
-            session = tf.compat.v1.Session(config=config)
-            set_session(session)
-
-            self.model_page = self.our_load_model(self.model_page_dir)
-            self.model_classifier = self.our_load_model(self.model_dir_of_col_classifier)
-            self.model_bin = self.our_load_model(self.model_dir_of_binarization)
-            #self.model_textline = self.our_load_model(self.model_textline_dir)
-            self.model_region = self.our_load_model(self.model_region_dir_p_ens_light_only_images_extraction)
-            #self.model_region_fl_np = self.our_load_model(self.model_region_dir_fully_np)
-            #self.model_region_fl = self.our_load_model(self.model_region_dir_fully)
-
-            self.ls_imgs  = os.listdir(self.dir_in)
-
-        if dir_in and not (light_version or self.extract_only_images):
-            config = tf.compat.v1.ConfigProto()
-            config.gpu_options.allow_growth = True
-            session = tf.compat.v1.Session(config=config)
-            set_session(session)
+            if self.extract_only_images:
+                self.model_region = self.our_load_model(self.model_region_dir_p_ens_light_only_images_extraction)
+            else:
+                self.model_textline = self.our_load_model(self.model_textline_dir)
+                if self.light_version:
+                    self.model_region = self.our_load_model(self.model_region_dir_p_ens_light)
+                    self.model_region_1_2 = self.our_load_model(self.model_region_dir_p_1_2_sp_np)
+                else:
+                    self.model_region = self.our_load_model(self.model_region_dir_p_ens)
+                    self.model_region_p2 = self.our_load_model(self.model_region_dir_p2)
+                    self.model_enhancement = self.our_load_model(self.model_dir_of_enhancement)
+                ###self.model_region_fl_new = self.our_load_model(self.model_region_dir_fully_new)
+                self.model_region_fl_np = self.our_load_model(self.model_region_dir_fully_np)
+                self.model_region_fl = self.our_load_model(self.model_region_dir_fully)
+                if self.reading_order_machine_based:
+                    self.model_reading_order = self.our_load_model(self.model_reading_order_dir)
+                if self.ocr:
+                    self.model_ocr = VisionEncoderDecoderModel.from_pretrained(self.model_ocr_dir)
+                    self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+                    self.processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")#("microsoft/trocr-base-printed")#("microsoft/trocr-base-handwritten")
+                if self.tables:
+                    self.model_table = self.our_load_model(self.model_table_dir)
             
-            self.model_page = self.our_load_model(self.model_page_dir)
-            self.model_classifier = self.our_load_model(self.model_dir_of_col_classifier)
-            self.model_bin = self.our_load_model(self.model_dir_of_binarization)
-            self.model_textline = self.our_load_model(self.model_textline_dir)
-            self.model_region = self.our_load_model(self.model_region_dir_p_ens)
-            self.model_region_p2 = self.our_load_model(self.model_region_dir_p2)
-            self.model_region_fl_np = self.our_load_model(self.model_region_dir_fully_np)
-            self.model_region_fl = self.our_load_model(self.model_region_dir_fully)
-            self.model_enhancement = self.our_load_model(self.model_dir_of_enhancement)
-            self.model_reading_order = self.our_load_model(self.model_reading_order_dir)
-            if self.tables:
-                self.model_table = self.our_load_model(self.model_table_dir)
-                
             self.ls_imgs  = os.listdir(self.dir_in)
             
-
-            
         
     def _cache_images(self, image_filename=None, image_pil=None):
         ret = {}