Update video_processing.py

video_processing.py

@@ -22,7 +22,6 @@ mtcnn = MTCNN(keep_all=False, device=device, thresholds=[0.9, 0.9, 0.9], min_fac
 mp_face_mesh = mp.solutions.face_mesh
 face_mesh = mp_face_mesh.FaceMesh(static_image_mode=False, max_num_faces=1, min_detection_confidence=0.8)
 
-
 def extract_frames(video_path, output_folder, desired_fps, progress_callback=None):
     os.makedirs(output_folder, exist_ok=True)
     clip = VideoFileClip(video_path)
@@ -45,7 +44,6 @@ def extract_frames(video_path, output_folder, desired_fps, progress_callback=Non
     clip.close()
     return frame_count, original_fps
 
-
 def process_frames(frames_folder, aligned_faces_folder, frame_count, progress):
     embeddings_by_frame = {}
     posture_scores_by_frame = {}
@@ -89,7 +87,6 @@ def process_frames(frames_folder, aligned_faces_folder, frame_count, progress):
 
     return embeddings_by_frame, posture_scores_by_frame, posture_landmarks_by_frame, aligned_face_paths, facial_landmarks_by_frame
 
-
 def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
     start_time = time.time()
     output_folder = "output"
@@ -182,6 +179,7 @@ def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
             progress(0.9, "Generating video with heatmap")
 
             # Create video with heatmap
+            heatmap_video_path = os.path.join(output_folder, "heatmap_video.mp4")
             heatmap_video_path = create_video_with_heatmap(video_path, df, mse_embeddings, mse_posture, heatmap_video_path, desired_fps, largest_cluster)
             
         except Exception as e:
@@ -254,7 +252,6 @@ def process_video(video_path, anomaly_threshold, desired_fps, progress=None):
             heatmap_video_path
         )
 
-
 def is_frontal_face(landmarks, threshold=60):
     nose_tip = landmarks[4]
     left_chin = landmarks[234]
@@ -269,7 +266,6 @@ def is_frontal_face(landmarks, threshold=60):
     angle_degrees = math.degrees(angle)
     return abs(180 - angle_degrees) < threshold
 
-
 def save_person_data_to_csv(embeddings_by_frame, clusters, desired_fps, original_fps, output_folder, video_duration):
     person_data = {}
 
@@ -303,7 +299,6 @@ def save_person_data_to_csv(embeddings_by_frame, clusters, desired_fps, original
 
     return df, largest_cluster
 
-
 def get_all_face_samples(organized_faces_folder, output_folder, largest_cluster, max_samples=100):
     face_samples = {"most_frequent": [], "others": []}
     for cluster_folder in sorted(os.listdir(organized_faces_folder)):