Update app.py

app.py

@@ -13,11 +13,11 @@ def process_and_show_completion(video_input_path, anomaly_threshold_input, fps,
         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
-    
+            return [results[0]] + [None] * 26
+
         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, \
@@ -26,24 +26,12 @@ def process_and_show_completion(video_input_path, anomaly_threshold_input, fps,
             anomaly_faces_embeddings, anomaly_frames_posture_images, \
             aligned_faces_folder, frames_folder, \
             stacked_heatmap, audio_waveform_plot = results
-    
-        # Handle potential string values for image data
-        def safe_image_conversion(image_data):
-            if isinstance(image_data, np.ndarray):
-                return Image.fromarray(image_data)
-            elif isinstance(image_data, str):
-                print(f"Warning: Expected image data, got string: {image_data[:100]}...")  # Print first 100 chars
-                return None
-            else:
-                print(f"Warning: Unexpected data type for image: {type(image_data)}")
-                return None
-    
-        anomaly_faces_embeddings_pil = [safe_image_conversion(face) for face in anomaly_faces_embeddings] if isinstance(anomaly_faces_embeddings, list) else []
-        anomaly_frames_posture_pil = [safe_image_conversion(frame) for frame in anomaly_frames_posture_images] if isinstance(anomaly_frames_posture_images, list) else []
-        
-        # For face_samples_frequent, we're expecting paths, so we'll keep it as is
-        face_samples_frequent = [Image.open(path) for path in face_samples_frequent] if isinstance(face_samples_frequent, list) else []
-    
+
+        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,
@@ -54,11 +42,11 @@ def process_and_show_completion(video_input_path, anomaly_threshold_input, fps,
             face_samples_frequent,
             aligned_faces_folder, frames_folder,
             mse_embeddings, mse_posture, mse_voice,
-            stacked_heatmap,
-            audio_waveform_plot
+            stacked_heatmap, audio_waveform_plot
         ]
+
         return output
-    
+
     except Exception as e:
         error_message = f"An error occurred: {str(e)}"
         print(error_message)