diff --git a/model.py b/model.py
index a8e7d78..6dcfae0 100644
--- a/model.py
+++ b/model.py
@@ -46,13 +46,11 @@ def __init__(self,  cfg_file):
         self.l_model = []
 
         self.encodings_path = params['encodings_path']
-        self.configs_path = params['configs_path']
         self.plots_path = params['plots_path']
         self.tensorboard_log_path = params['tensorboard_log_path']
         self.weights_save_path = params['weights_save_path']
         
         os.makedirs(self.encodings_path, exist_ok=True)
-        os.makedirs(self.configs_path, exist_ok=True)
         os.makedirs(self.plots_path, exist_ok=True)
         os.makedirs(self.tensorboard_log_path, exist_ok=True)
         os.makedirs(self.weights_save_path, exist_ok=True)
@@ -235,7 +233,6 @@ def predict(self, image):
         else:
             img = image
         img = cv2.resize(img, (self.input_shape[0], self.input_shape[1]))
-        print(img.shape)
         encoding = self.base_model.predict(np.expand_dims(img, axis=0))
         distances = self.calculate_distances(encoding)
         max_element = np.argmin(distances)
diff --git a/utils.py b/utils.py
index e8d94a2..3f1b761 100644
--- a/utils.py
+++ b/utils.py
@@ -97,19 +97,13 @@ def parse_net_params(filename='configs/road_signs.yml'):
 
     params = {k: v for k, v in cfg.items() if k not in ['optimizer']}
 
-    current_directory = os.path.dirname(os.path.abspath(__file__))
-    print(current_directory)
-    params['encodings_path'] = os.path.join(current_directory,
-                                            cfg['encodings_path'],
+    params['encodings_path'] = os.path.join(cfg['encodings_path'],
                                             cfg['project_name'])
-    params['plots_path'] = os.path.join(current_directory,
-                                        cfg['plots_path'],
+    params['plots_path'] = os.path.join(cfg['plots_path'],
                                         cfg['project_name'])
-    params['tensorboard_log_path'] = os.path.join(current_directory,
-                                                  cfg['tensorboard_log_path'],
+    params['tensorboard_log_path'] = os.path.join(cfg['tensorboard_log_path'],
                                                   cfg['project_name'])
-    params['weights_save_path'] = os.path.join(current_directory,
-                                               cfg['weights_save_path'],
+    params['weights_save_path'] = os.path.join(cfg['weights_save_path'],
                                                cfg['project_name'])
 
     if 'dataset_path' in cfg: