Update app.py

app.py

@@ -103,11 +103,10 @@ with gr.Blocks() as iface:
     anomaly_threshold = gr.Slider(minimum=1, maximum=5, step=0.1, value=3, label="Anomaly Detection Threshold (Standard deviation)")
     fps_slider = gr.Slider(minimum=5, maximum=20, step=1, value=10, label="Frames Per Second (FPS)")
     process_btn = gr.Button("Detect Anomalies")
-    progress_bar = gr.Progress()
     
     execution_time = gr.Number(label="Execution Time (seconds)", visible=False)
 
-    description = gr.Markdown("""
+    description = gr.Markdown(visible=True, value="""
     # Multimodal Behavioral Anomalies Detection
     
     The purpose of this tool is to detect anomalies in facial expressions, body language, and voice over the timeline of a video.   
@@ -141,9 +140,10 @@ with gr.Blocks() as iface:
     
     ## Conclusion
     This tool offers solutions for detecting behavioral anomalies in video content. However, users should be aware of its limitations and interpret results with caution.
-    """, visible=True)
+    """)
 
-    with gr.Tabs(visible=False) as results:
+    results = gr.Tabs(visible=False)
+    with results:
         with gr.TabItem("Facial Features"):
             video_display_facial = gr.Video(label="Input Video")
             results_text = gr.TextArea(label="Faces Breakdown", lines=5)