Update app.py

app.py

@@ -59,47 +59,40 @@ def save_uploaded_file(uploaded_file):
     return file_path
 
 def display_results(video_url, video_file, description):
-    print("Starting video processing...")
+    output_message = None
     if video_url:
         video_path = download_video(video_url)
     elif video_file:
         video_path = save_uploaded_file(video_file)
     else:
-        return "No video provided", None, None
-
-    print(f"Video path: {video_path}")
-
-    scenes = find_scenes(video_path)
-    if not scenes:
-        return "No scenes detected", None, None
-
-    best_scene_info = analyze_scenes(video_path, scenes, description)
-    if not best_scene_info:
-        return "Analysis failed", None, None
-
-    best_scene, sentiment_distribution = best_scene_info if isinstance(best_scene_info, tuple) else (None, None)
-    print(f"Best scene: {best_scene}, Sentiments: {sentiment_distribution}")
-
-    if best_scene:
-        final_clip = extract_best_scene(video_path, best_scene)
-        if final_clip:
-            output_dir = "output"
-            os.makedirs(output_dir, exist_ok=True)
-            final_clip_path = os.path.join(output_dir, f"{uuid.uuid4()}_final_clip.mp4")
-            final_clip.write_videofile(final_clip_path, codec='libx264', audio_codec='aac')
-            cleanup_temp_files()
-
-            print(f"Final clip saved to: {final_clip_path}")
-
-            if sentiment_distribution:
-                plot = create_radial_plot(sentiment_distribution)
+        output_message = "No video provided"
+
+    if not output_message:
+        scenes = find_scenes(video_path)
+        if not scenes:
+            output_message = "No scenes detected"
+
+    if not output_message:
+        best_scene_info = analyze_scenes(video_path, scenes, description)
+        if best_scene_info:
+            best_scene = best_scene_info[0] if isinstance(best_scene_info, tuple) else None
+            sentiment_distribution = best_scene_info[-1] if isinstance(best_scene_info, tuple) else None
+            final_clip = extract_best_scene(video_path, best_scene) if best_scene else None
+            if final_clip:
+                output_dir = "output"
+                os.makedirs(output_dir, exist_ok=True)
+                final_clip_path = os.path.join(output_dir, f"{uuid.uuid4()}_final_clip.mp4")
+                final_clip.write_videofile(final_clip_path, codec='libx264', audio_codec='aac')
+                cleanup_temp_files()
+
+                plot = create_radial_plot(sentiment_distribution) if sentiment_distribution else "No sentiment data available"
                 return final_clip_path, plot
             else:
-                return final_clip_path, "No sentiment data available"
+                output_message = "No matching scene found"
         else:
-            return "No matching scene found", None
-    else:
-        return "No suitable scenes found", None
+            output_message = "Analysis failed or no suitable scenes found"
+
+    return None, output_message
 
 
 # Custom CSS for additional styling
@@ -148,21 +141,19 @@ h3 {
     text-transform: uppercase;
 }
 """
-
 with gr.Blocks(theme=custom_theme, css=css) as demo:
     with gr.Column():
-        gr.Markdown("# **Sickstadium AI**", elem_classes="centered-markdown", elem_id="sickstadium-title")
-        gr.Markdown("### Upload your videos. Find sick clips. Tell your truth.", elem_classes="centered-markdown")
-        video_url = gr.Textbox(label="Video URL:", elem_id="video_url")
-        video_file = gr.File(label="Upload Video File:", interactive=True, file_types=["video"], type="binary")
-        description = gr.Textbox(label="Describe your clip:", elem_id="description")
+        video_url_input = gr.Textbox(label="Video URL:", elem_id="video_url")
+        video_file_input = gr.File(label="Upload Video File:", interactive=True, file_types=["video"], type="binary")
+        description_input = gr.Textbox(label="Describe your clip:", elem_id="description")
         submit_button = gr.Button("Process Video", elem_id="submit_button")
         video_output = gr.Video(label="Processed Video", elem_id="video_output")
-        sentiment_plot = gr.Plot(label="Sentiment Distribution", elem_id="sentiment_plot")
+        sentiment_plot_output = gr.Plot(label="Sentiment Distribution", elem_id="sentiment_plot")
+
         submit_button.click(
             fn=display_results,
-            inputs=[video_url, video_file, description],
-            outputs=[video_output, sentiment_plot]
+            inputs=[video_url_input, video_file_input, description_input],
+            outputs=[video_output, sentiment_plot_output]
         )
 
 demo.launch()