updates

app.py

@@ -55,7 +55,7 @@ def preprocess(filename, max_frames=0, resize=(224,224)):
     video = np.expand_dims(video, axis=0)
     return video
 
-def translate(video_file):
+def translate(video_file, text):
 
     video = preprocess(video_file, max_frames=0, resize=(224,224))
 
@@ -86,6 +86,7 @@ More information about the models can be found in our GitHub repository <a href=
 
 A limitation of this architecture is the size of the MoViNets model, making it especially slow during inference on a CPU. 
 We do not recommend uploading videos longer than 4 seconds as the video embedding generation may take some time. 
+The application does not accept videos that are longer than 10 seconds.
 We have provided some pre-cached videos with their original captions and translations as examples.
 """
 
@@ -98,8 +99,6 @@ examples = [
     ]
 
 
-article =  "More information about the models can be found <a href=https://github.com/deanna-emery/ASL-Translator>here</a>."
-
 article =  """The captions for the example videos are as follows in order: \n
 1. 'My second ASL professor's name was Will White'
 2. 'You are my sunshine'
@@ -109,7 +108,7 @@ article =  """The captions for the example videos are as follows in order: \n
 
 # Gradio App interface
 gr.Interface(fn=translate,
-              inputs=["video", 'text'], 
+              inputs=gr.Video(label='Video', show_label=True, max_length=10), 
               outputs="text",
               allow_flagging="never",
               title=title,