Update app.py

app.py

@@ -8,56 +8,13 @@ matplotlib.rcParams['figure.dpi'] = 300
 matplotlib.rcParams['savefig.dpi'] = 300
 
 def process_and_show_completion(video_input_path, anomaly_threshold_input, fps, progress=gr.Progress()):
-    try:
-        print("Starting video processing...")
-        results = process_video(video_input_path, anomaly_threshold_input, fps, progress=progress)
-        print("Video processing completed.")
-
-        if isinstance(results[0], str) and results[0].startswith("Error"):
-            print(f"Error occurred: {results[0]}")
-            return [results[0]] + [None] * 27
-
-        exec_time, results_summary, df, mse_embeddings, mse_posture, mse_voice, \
-            mse_plot_embeddings, mse_plot_posture, mse_plot_voice, \
-            mse_histogram_embeddings, mse_histogram_posture, mse_histogram_voice, \
-            mse_heatmap_embeddings, mse_heatmap_posture, mse_heatmap_voice, \
-            face_samples_frequent, \
-            anomaly_faces_embeddings, anomaly_frames_posture_images, \
-            aligned_faces_folder, frames_folder, \
-            heatmap_video_path, combined_mse_plot, correlation_heatmap = results
-
-        anomaly_faces_embeddings_pil = [Image.fromarray(face) for face in anomaly_faces_embeddings] if anomaly_faces_embeddings is not None else []
-        anomaly_frames_posture_pil = [Image.fromarray(frame) for frame in anomaly_frames_posture_images] if anomaly_frames_posture_images is not None else []
-
-        face_samples_frequent = [Image.open(path) for path in face_samples_frequent] if face_samples_frequent is not None else []
-
-        output = [
-            exec_time, results_summary,
-            df, mse_embeddings, mse_posture, mse_voice,
-            mse_plot_embeddings, mse_plot_posture, mse_plot_voice,
-            mse_histogram_embeddings, mse_histogram_posture, mse_histogram_voice,
-            mse_heatmap_embeddings, mse_heatmap_posture, mse_heatmap_voice,
-            anomaly_faces_embeddings_pil, anomaly_frames_posture_pil,
-            face_samples_frequent,
-            aligned_faces_folder, frames_folder,
-            mse_embeddings, mse_posture, mse_voice,
-            heatmap_video_path, combined_mse_plot, correlation_heatmap
-        ]
-
-        return output
-
-    except Exception as e:
-        error_message = f"An error occurred: {str(e)}"
-        print(error_message)
-        import traceback
-        traceback.print_exc()
-        return [error_message] + [None] * 27
+    # ... (keep the existing function code)
 
 def show_results(outputs):
-    return gr.Tabs(visible=True), gr.Group(visible=True)
+    return [gr.Tab.update(visible=True) for _ in range(4)] + [gr.Tab.update(visible=False)], gr.Group(visible=True)
 
 def hide_description_show_results():
-    return gr.Tabs(visible=True), gr.Tab(visible=False)
+    return [gr.Tab.update(visible=False)] + [gr.Tab.update(visible=True) for _ in range(4)]
 
 with gr.Blocks() as iface:
     with gr.Row():
@@ -73,7 +30,7 @@ with gr.Blocks() as iface:
         execution_time = gr.Number(label="Execution Time (seconds)")
 
     with gr.Tabs() as all_tabs:
-        with gr.Tab("Description", elem_id="description_tab"):
+        with gr.Tab("Description", visible=True):
             gr.Markdown("""
             # Multimodal Behavioral Anomalies Detection
 
@@ -118,7 +75,7 @@ with gr.Blocks() as iface:
     process_btn.click(
         hide_description_show_results,
         inputs=None,
-        outputs=[all_tabs, all_tabs.select("Description")]
+        outputs=all_tabs.children
     ).then(
         process_and_show_completion,
         inputs=[video_input, anomaly_threshold, fps_slider],
@@ -137,7 +94,7 @@ with gr.Blocks() as iface:
     ).then(
         show_results,
         inputs=None,
-        outputs=[all_tabs, execution_time_group]
+        outputs=[all_tabs.children, execution_time_group]
     )
 
 if __name__ == "__main__":