Update app.py

app.py

@@ -51,8 +51,8 @@ data_path = 'signs'
 # Custom CSS to control output video size
 custom_css = """
 #landmarked_video {
-    max-height: 600px;
-    width: auto;
+    max-height: 350px;
+    width: 500px;
 }
 """
 
@@ -245,7 +245,7 @@ def prod_function(model_pretrained, prod_ds):
     return prod_pred
 
 # Function to get landmarked video
-def save_video_to_mp4(video_tensor, fps=15):
+def save_video_to_mp4(video_tensor, fps=10):
     # Convert pytorch tensor to numpy ndarray
     video_numpy = video_tensor.permute(0, 2, 3, 1).cpu().numpy()
     # Normalize values to [0, 255] if necessary
@@ -316,7 +316,7 @@ with gr.Blocks(css=custom_css) as demo:
     
     # Gesture recognition Tab
     with gr.Tab("Gesture recognition"):
-        landmarked_video = gr.State([])
+        #landmarked_video = gr.State([])
         with gr.Row(height=350, variant="panel"): # equal_height=False, show_progress=True
             with gr.Column(scale=1, variant="panel"):
                 # Add webcam input for sign language video capture