Update video_processing.py

video_processing.py

@@ -10,7 +10,7 @@ from face_analysis import get_face_embedding, cluster_faces, organize_faces_by_p
 from pose_analysis import pose, calculate_posture_score, draw_pose_landmarks
 from voice_analysis import get_speaker_embeddings, align_voice_embeddings, extract_audio_from_video, diarize_speakers
 from anomaly_detection import anomaly_detection
-from visualization import plot_mse, plot_mse_histogram, plot_mse_heatmap, create_video_with_heatmap
+from visualization import plot_mse, plot_mse_histogram, plot_mse_heatmap, create_video_with_heatmap, plot_correlation_heatmap, plot_3d_scatter
 from utils import frame_to_timecode
 import pandas as pd
 from facenet_pytorch import MTCNN
@@ -209,6 +209,12 @@ def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
             mse_heatmap_embeddings = plot_mse_heatmap(mse_embeddings, "Facial Features MSE Heatmap", df)
             mse_heatmap_posture = plot_mse_heatmap(mse_posture, "Body Posture MSE Heatmap", df)
             mse_heatmap_voice = plot_mse_heatmap(mse_voice, "Voice MSE Heatmap", df)
+
+            # Generate the correlation heatmap
+            correlation_heatmap = plot_correlation_heatmap(mse_embeddings, mse_posture, mse_voice)
+        
+            # Generate the 3D scatter plot
+            scatter_plot_3d = plot_3d_scatter(mse_embeddings, mse_posture, mse_voice)
         
             try:
                 if progress is not None:
@@ -238,7 +244,7 @@ def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
             print(f"Error details: {str(e)}")
             import traceback
             traceback.print_exc()
-            return (f"Error in video processing: {str(e)}",) + (None,) * 21
+            return (f"Error in video processing: {str(e)}",) + (None,) * 23
 
         progress(1.0, "Preparing results")
         results = f"Number of persons detected: {num_clusters}\n\n"
@@ -305,7 +311,9 @@ def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
             anomaly_frames_posture_images,
             aligned_faces_folder,
             frames_folder,
-            heatmap_video_path
+            heatmap_video_path,
+            correlation_heatmap,
+            scatter_plot_3d
         )
 
 def is_frontal_face(landmarks, threshold=60):