Realtime_Face_Landmark_Detection.py

import cv2
import mediapipe as mp
import time

# model = 'model.task'
capture = cv2.VideoCapture(0)
 
previousTime = 0
currentTime = 0
mp_holistic = mp.solutions.holistic
holistic_model = mp_holistic.Holistic(
    min_detection_confidence=0.5,
    min_tracking_confidence=0.5
)

mp_drawing = mp.solutions.drawing_utils
 
while capture.isOpened():
    ret, frame = capture.read()
 
    frame = cv2.resize(frame, (800, 600))
    image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    image.flags.writeable = False


    results = holistic_model.process(image)
    image.flags.writeable = True
 
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
 
    mp_drawing.draw_landmarks(
      image,
      results.face_landmarks,
      mp_holistic.FACEMESH_CONTOURS,
      mp_drawing.DrawingSpec(
        color=(255,0,255),
        thickness=1,
        circle_radius=1
      ),
      mp_drawing.DrawingSpec(
        color=(0,255,255),
        thickness=1,
        circle_radius=1
      )
    )
 
    mp_drawing.draw_landmarks(
      image,
      results.right_hand_landmarks,
      mp_holistic.HAND_CONNECTIONS
    )
 
    mp_drawing.draw_landmarks(
      image,
      results.left_hand_landmarks,
      mp_holistic.HAND_CONNECTIONS
    )
     
    currentTime = time.time()
    fps = 1 / (currentTime-previousTime)
    previousTime = currentTime
    
    cv2.putText(image, str(int(fps))+" FPS", (10, 70), cv2.FONT_HERSHEY_COMPLEX, 1, (0,255,0), 2)

    cv2.imshow("Facial and Hand Landmarks", image)
    if cv2.waitKey(5) & 0xFF == ord('q'):
        break


capture.release()
cv2.destroyAllWindows()