updates

app.py

@@ -74,14 +74,23 @@ def translate(video_file):
 title = "ASL Translation (MoViNet + T5)"
 
 examples = [
-        ["videos/My_second_ASL_professors_name_was_Will_White.mp4", "My second ASL professor's name was Will White"],
-        ['videos/You_are_my_sunshine.mp4', 'You are my sunshine'],
-        ['videos/scrub_your_hands_for_at_least_20_seconds.mp4', 'scrub your hands for at least 20 seconds'],
-        ['videos/no.mp4', 'no'],
-        ['videos/all.mp4', 'all']
-        ['videos/white.mp4', 'white']
+        ["videos/My_second_ASL_professors_name_was_Will_White.mp4",],
+        ['videos/You_are_my_sunshine.mp4'],
+        ['videos/scrub_your_hands_for_at_least_20_seconds.mp4'],
+        ['videos/no.mp4'],
+        ['videos/all.mp4']
+        ['videos/white.mp4']
     ]
 
+# examples = [
+#         ["videos/My_second_ASL_professors_name_was_Will_White.mp4", "My second ASL professor's name was Will White"],
+#         ['videos/You_are_my_sunshine.mp4', 'You are my sunshine'],
+#         ['videos/scrub_your_hands_for_at_least_20_seconds.mp4', 'scrub your hands for at least 20 seconds'],
+#         ['videos/no.mp4', 'no'],
+#         ['videos/all.mp4', 'all']
+#         ['videos/white.mp4', 'white']
+#     ]
+
 description =   "Gradio demo of word-level sign language classification using I3D model pretrained on the WLASL video dataset. " \
                 "WLASL is a large-scale dataset containing more than 2000 words in American Sign Language. " \
                 "Examples used in the demo are videos from the the test subset. "  \