Update app.py

app.py

@@ -15,13 +15,12 @@ def process_and_show_completion(video_input_path, anomaly_threshold_input, fps,
 
         if isinstance(results[0], str) and results[0].startswith("Error"):
             print(f"Error occurred: {results[0]}")
-            return [results[0]] + [None] * 18  # Increased by 1 for the new heatmap video
+            return [results[0]] + [None] * 17
 
         exec_time, results_summary, df, mse_embeddings, mse_posture, \
             mse_plot_embeddings, mse_histogram_embeddings, \
             mse_plot_posture, mse_histogram_posture, \
             mse_heatmap_embeddings, mse_heatmap_posture, \
-            mse_voice, mse_plot_voice, mse_histogram_voice, mse_heatmap_voice, \
             face_samples_frequent, \
             anomaly_faces_embeddings, anomaly_frames_posture_images, \
             aligned_faces_folder, frames_folder, \
@@ -52,14 +51,14 @@ def process_and_show_completion(video_input_path, anomaly_threshold_input, fps,
         print(error_message)
         import traceback
         traceback.print_exc()
-        return [error_message] + [None] * 18  # Increased by 1 for the new heatmap video
+        return [error_message] + [None] * 17
 
 with gr.Blocks() as iface:
     gr.Markdown("""
     # Multimodal Behavioral Anomalies Detection
 
-    This tool detects anomalies in facial expressions, body language, and voice over the timeline of a video.
-    It extracts faces, postures, and voice features from video frames, and analyzes them to identify anomalies using time series analysis and a variational autoencoder (VAE) approach.
+    This tool detects anomalies in facial expressions and body language over the timeline of a video.
+    It extracts faces and postures from video frames, and analyzes them to identify anomalies using time series analysis and a variational autoencoder (VAE) approach.
     """)
 
     with gr.Row():
@@ -87,11 +86,6 @@ with gr.Blocks() as iface:
             mse_posture_heatmap = gr.Plot(label="MSE Heatmap: Body Posture")
             anomaly_frames_posture = gr.Gallery(label="Anomaly Frames (Body Posture)", columns=6, rows=2, height="auto")
 
-        with gr.Tab("Voice"):
-            mse_voice_plot = gr.Plot(label="MSE: Voice")
-            mse_voice_hist = gr.Plot(label="MSE Distribution: Voice")
-            mse_voice_heatmap = gr.Plot(label="MSE Heatmap: Voice")
-
         with gr.Tab("Video with Heatmap"):
             heatmap_video = gr.Video(label="Video with Anomaly Heatmap")