Update main.py

main.py

@@ -67,16 +67,15 @@ You will use the [MS-COCO dataset](http://cocodataset.org/#home) to train your m
 
 **Caution: large download ahead**. You'll use the training set, which is a 13GB file.
 """
-os.system("wget http://images.cocodataset.org/zips/train2014.zip")
+# os.system("wget http://images.cocodataset.org/zips/train2014.zip")
 # Download caption annotation files
 annotation_folder = '/annotations/'
-if not os.path.exists(os.path.abspath('.') + annotation_folder):
-  annotation_zip = tf.keras.utils.get_file('captions.zip',
+annotation_zip = tf.keras.utils.get_file('captions.zip',
                                            cache_subdir=os.path.abspath('.'),
                                            origin='http://images.cocodataset.org/annotations/annotations_trainval2014.zip',
                                            extract=True)
-  annotation_file = os.path.dirname(annotation_zip)+'/annotations/captions_train2014.json'
-  os.remove(annotation_zip)
+annotation_file = os.path.dirname(annotation_zip)+'/annotations/captions_train2014.json'
+# os.remove(annotation_zip)
 
 # Download image files
 image_folder = '/train2014/'
@@ -86,7 +85,7 @@ image_zip = tf.keras.utils.get_file('train2014.zip',
                                       origin='http://images.cocodataset.org/zips/train2014.zip',
                                       extract=True)
 PATH = os.path.dirname(image_zip) + image_folder
-os.remove(image_zip)
+# os.remove(image_zip)