Update main.py

main.py

@@ -67,7 +67,7 @@ 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.
 """
-
+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):
@@ -80,15 +80,14 @@ if not os.path.exists(os.path.abspath('.') + annotation_folder):
 
 # Download image files
 image_folder = '/train2014/'
-if not os.path.exists(os.path.abspath('.') + image_folder):
-  image_zip = tf.keras.utils.get_file('train2014.zip',
+
+image_zip = tf.keras.utils.get_file('train2014.zip',
                                       cache_subdir=os.path.abspath('.'),
                                       origin='http://images.cocodataset.org/zips/train2014.zip',
                                       extract=True)
-  PATH = os.path.dirname(image_zip) + image_folder
-  os.remove(image_zip)
-else:
-  PATH = os.path.abspath('.') + image_folder
+PATH = os.path.dirname(image_zip) + image_folder
+os.remove(image_zip)
+
 
 
 """## Optional: limit the size of the training set