diff --git a/examples/largedataset_cnn/process_data.py b/examples/largedataset_cnn/process_data.py
index 04a1750..1fdf185 100644
--- a/examples/largedataset_cnn/process_data.py
+++ b/examples/largedataset_cnn/process_data.py
@@ -35,13 +35,14 @@
 
     return im
 
+
 def process_data(dataset_root, classes):
-    # load class names
+    # Load class names
     with open(classes, 'r', encoding='utf-8') as f:
         classes = f.readlines()
         classes = list(map(lambda x: x.strip(), classes))
 
-    # make input_paths and labels
+    # Make input_paths and labels
     input_paths, labels = [], []
     for class_name in os.listdir(dataset_root):
         class_root = os.path.join(dataset_root, class_name)
@@ -54,17 +55,17 @@
             input_paths.append(path)
             labels.append(class_id)
 
-    # convert to numpy array
+    # Convert to numpy array
     input_paths = np.array(input_paths)
     labels = np.array(labels, dtype=np.int32)
 
-    # shuffle dataset
+    # Shuffle dataset
     np.random.seed(0)
     perm = np.random.permutation(len(input_paths))
     input_paths = input_paths[perm]
     labels = labels[perm]
 
-    # split dataset for training and validation
+    # Split dataset for training and validation
     border = int(len(input_paths) * 0.8)
     train_labels = labels[:border]
     val_labels = labels[border:]
@@ -78,13 +79,13 @@
     return train_input_paths, train_labels, val_input_paths, val_labels
 
 def loaddata():
-    dataset_root = '/Dataset/Data/'  # need to set this path an argument
+    dataset_root = '/Dataset/Data/'
     classes = '/Dataset/classes.txt'
     return process_data(dataset_root, classes)
 
 if __name__ == '__main__':
 
-    # Test loaddata() function in main
+    # test script in main
     train_input_paths, train_labels, val_input_paths, val_labels = loaddata()
 
     print(train_input_paths.shape)