Update app.py

app.py

@@ -382,6 +382,19 @@ def process_video(video_path, num_anomalies, num_components, desired_fps, batch_
         progress(0.8, "Saving person data")
         df, largest_cluster = save_person_data_to_csv(embeddings_by_frame, emotions_by_frame, clusters, desired_fps, original_fps, temp_dir, num_components)
 
+        progress(0.9, "Performing anomaly detection")
+        feature_columns = [col for col in df.columns if col not in ['Frame', 'Timecode', 'Time (Minutes)', 'Embedding_Index']]
+        X = df[feature_columns].values
+        print(f"Shape of input data: {X.shape}")
+        print(f"Feature columns: {feature_columns}")
+        try:
+            anomalies_all, anomaly_scores_all, top_indices_all, anomalies_comp, anomaly_scores_comp, top_indices_comp, _ = lstm_anomaly_detection(X, feature_columns, num_anomalies=num_anomalies, batch_size=batch_size)
+        except Exception as e:
+            print(f"Error details: {str(e)}")
+            print(f"X shape: {X.shape}")
+            print(f"X dtype: {X.dtype}")
+            return f"Error in anomaly detection: {str(e)}", None, None, None, None, None, None
+
         progress(0.95, "Generating plots")
         try:
             anomaly_plot_all = plot_anomaly_scores(df, anomaly_scores_all, top_indices_all, "All Features")
@@ -393,18 +406,6 @@ def process_video(video_path, num_anomalies, num_components, desired_fps, batch_
             ]
         except Exception as e:
             return f"Error generating plots: {str(e)}", None, None, None, None, None, None
-        
-        progress(0.95, "Generating plots")
-        try:
-            anomaly_plot_all = plot_anomaly_scores(df, anomaly_scores_all, top_indices_all, "All Features")
-            anomaly_plot_comp = plot_anomaly_scores(df, anomaly_scores_comp, top_indices_comp, "Components Only")
-            emotion_plots = [
-                plot_emotion(df, 'fear', num_anomalies, 'lightblue'),
-                plot_emotion(df, 'sad', num_anomalies, 'lightgreen'),
-                plot_emotion(df, 'angry', num_anomalies, 'salmon')
-            ]
-        except Exception as e:
-            return f"Error generating plots: {str(e)}", None, None, None, None, None, None
 
         # Get a random face sample
         face_sample = get_random_face_sample(organized_faces_folder, largest_cluster, output_folder)