36 lines
1.0 KiB
Python
36 lines
1.0 KiB
Python
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import cv2
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import mediapipe as mp
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mp_drawing = mp.solutions.drawing_utils
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mp_hands = mp.solutions.hands
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hands = mp_hands.Hands(
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min_detection_confidence=0.5, min_tracking_confidence=0.5)
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cap = cv2.VideoCapture(0)
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while cap.isOpened():
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success, image = cap.read()
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# Flip the image horizontally for a later selfie-view display, and convert
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# the BGR image to RGB.
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image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
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# To improve performance, optionally mark the image as not writeable to
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# pass by reference.
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image.flags.writeable = False
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results = hands.process(image)
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# Draw the hand annotations on the image.
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image.flags.writeable = True
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image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
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if results.multi_hand_landmarks:
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for hand_landmarks in results.multi_hand_landmarks:
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mp_drawing.draw_landmarks(
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image, hand_landmarks, mp_hands.HAND_CONNECTIONS)
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#print(hand_landmarks) ## spójrz na to
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cv2.imshow('MediaPipe Hands', image)
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if cv2.waitKey(5) & 0xFF == 27:
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break
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hands.close()
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cap.release()
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