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| import cv2 | |
| import mediapipe as mp | |
| def process_video_with_landmarks(video_path, output_path, scale_percent=100): | |
| """ | |
| Process a video to identify and draw landmarks on faces and hands. | |
| Parameters: | |
| video_path (str): The path to the input video file. | |
| output_path (str): The path to the output video file. | |
| scale_percent (int, optional): The percentage of the original size. Default is 100. | |
| """ | |
| # MediaPipe solutions | |
| mp_drawing = mp.solutions.drawing_utils | |
| mp_face_mesh = mp.solutions.face_mesh | |
| mp_hands = mp.solutions.hands | |
| # Open the video file | |
| cap = cv2.VideoCapture(video_path) | |
| # Get the video properties | |
| width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) | |
| height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) | |
| fps = cap.get(cv2.CAP_PROP_FPS) | |
| # Calculate the scale dimensions | |
| width = int(width * scale_percent / 100) | |
| height = int(height * scale_percent / 100) | |
| # Define the output video file | |
| fourcc = cv2.VideoWriter_fourcc(*'h264') | |
| # fourcc = cv2.VideoWriter_fourcc(*'HEVC') | |
| out_fps = fps / 0.6 # Set the output fps to half of the original fps | |
| out = cv2.VideoWriter(output_path, fourcc, out_fps, (width, height)) | |
| # Process each frame | |
| with mp_face_mesh.FaceMesh() as face_mesh, mp_hands.Hands() as hands: | |
| while cap.isOpened(): | |
| success, frame = cap.read() | |
| if not success: | |
| break | |
| # Resize the frame | |
| frame = cv2.resize(frame, (width, height), interpolation = cv2.INTER_AREA) | |
| # Convert the frame to RGB | |
| rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) | |
| # Process face landmarks | |
| results_face = face_mesh.process(rgb_frame) | |
| if results_face.multi_face_landmarks: | |
| for face_landmarks in results_face.multi_face_landmarks: | |
| mp_drawing.draw_landmarks( | |
| frame, | |
| face_landmarks, | |
| mp_face_mesh.FACEMESH_TESSELATION, | |
| landmark_drawing_spec=mp_drawing.DrawingSpec(color=(255, 255, 255), thickness=1, circle_radius=1), | |
| connection_drawing_spec=mp_drawing.DrawingSpec(color=(255, 255, 255), thickness=1) | |
| ) | |
| # Process hand landmarks | |
| results_hands = hands.process(rgb_frame) | |
| if results_hands.multi_hand_landmarks: | |
| for hand_landmarks in results_hands.multi_hand_landmarks: | |
| if hand_landmarks.landmark[mp_hands.HandLandmark.WRIST].x < hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_TIP].x: | |
| landmark_color = (255, 0, 0) # Left hand (Blue) | |
| else: | |
| landmark_color = (0, 0, 255) # Right hand (Red) | |
| mp_drawing.draw_landmarks( | |
| frame, | |
| hand_landmarks, | |
| mp_hands.HAND_CONNECTIONS, | |
| landmark_drawing_spec=mp_drawing.DrawingSpec(color=landmark_color, thickness=1, circle_radius=1), | |
| connection_drawing_spec=mp_drawing.DrawingSpec(color=landmark_color, thickness=1) | |
| ) | |
| # Write the annotated frame to the output video | |
| out.write(frame) | |
| # If 'q' is pressed on the keyboard, exit this loop | |
| if cv2.waitKey(1) & 0xFF == ord('q'): | |
| break | |
| # Close the video file | |
| cap.release() | |
| out.release() | |
| cv2.destroyAllWindows() | |
| return |