main.py

import cv2

import mediapipe.python.solutions.hands as mp_hands
import mediapipe.python.solutions.drawing_utils as mp_drawing
import mediapipe.python.solutions.drawing_styles as mp_drawing_styles

def run_hand_tracking():
    
    cam = cv2.VideoCapture(index = 0)
    
    with mp_hands.Hands(
        model_complexity=0,
        max_num_hands=2,
        min_detection_confidence=0.5,
        min_tracking_confidence=0.5) as hands:
        # Frame capture loop
        while cam.isOpened():
            success, frame = cam.read()
            if not success:
                print("empty camera frame.")
                continue
        
        # Convert the BGR image to RGB.
            frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
            results = hands.process(frame_rgb)
            
            if results.multi_hand_landmarks:
                for hand_landmarks in results.multi_hand_landmarks:
                    mp_drawing.draw_landmarks(
                        image = frame,
                        landmark_list = hand_landmarks,
                        connections = mp_hands.HAND_CONNECTIONS,
                        landmark_drawing_spec = mp_drawing_styles.get_default_hand_landmarks_style(),
                        connection_drawing_spec = mp_drawing_styles.get_default_hand_connections_style())
                    
        # Dsplay window and flip frame
            cv2.imshow('Hand Tracking', cv2.flip(frame, 1))
            # Exit on Q key
            if cv2.waitKey(1) & 0xFF == ord('q'):
                break  
    
    cam.release()

if __name__ == "__main__":
    run_hand_tracking()