Update video_processing.py

video_processing.py

@@ -133,20 +133,20 @@ def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
         clusters = cluster_faces(embeddings)
         num_clusters = len(set(clusters))
 
-        progress(0.7, "Organizing faces")
+        progress(0.65, "Organizing faces")
         organize_faces_by_person(embeddings_by_frame, clusters, aligned_faces_folder, organized_faces_folder)
 
-        progress(0.8, "Saving person data")
+        progress(0.7, "Saving person data")
         df, largest_cluster = save_person_data_to_csv(embeddings_by_frame, clusters, desired_fps,
                                                       original_fps, temp_dir, video_duration)
 
         df['Seconds'] = df['Timecode'].apply(
             lambda x: sum(float(t) * 60 ** i for i, t in enumerate(reversed(x.split(':')))))
 
-        progress(0.85, "Getting face samples")
+        progress(0.75, "Getting face samples")
         face_samples = get_all_face_samples(organized_faces_folder, output_folder, largest_cluster)
 
-        progress(0.9, "Performing anomaly detection")
+        progress(0.8, "Performing anomaly detection")
         embedding_columns = [col for col in df.columns if col.startswith('Raw_Embedding_')]
 
         X_embeddings = df[embedding_columns].values
@@ -160,7 +160,7 @@ def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
 
             mse_embeddings, mse_posture = anomaly_detection(X_embeddings, X_posture)
 
-            progress(0.95, "Generating plots")
+            progress(0.85, "Generating graphs")
             mse_plot_embeddings, anomaly_frames_embeddings = plot_mse(df, mse_embeddings, "Facial Features",
                                                                       color=GRAPH_COLORS['facial_embeddings'],
                                                                       anomaly_threshold=anomaly_threshold)
@@ -179,9 +179,11 @@ def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
 
             mse_heatmap_embeddings = plot_mse_heatmap(mse_embeddings, "Facial Features MSE Heatmap", df)
 
+            progress(0.9, "Generating video with heatmap")
+
             # Create video with heatmap
             heatmap_video_path = os.path.join(output_folder, "video_with_heatmap.mp4")
-            create_video_with_heatmap(video_path, df, mse_embeddings, mse_posture, heatmap_video_path)
+            create_video_with_heatmap(video_path, df, mse_embeddings, mse_posture, output_path, desired_fps)
 
         except Exception as e:
             print(f"Error details: {str(e)}")