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"""Hand Tracker using MediaPipe to detect hand positions in images.""" |
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import cv2 |
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import mediapipe as mp |
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import numpy as np |
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mp_drawing = mp.solutions.drawing_utils |
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mp_drawing_styles = mp.solutions.drawing_styles |
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mp_hands = mp.solutions.hands |
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class HandTracker: |
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"""Hand Tracker using MediaPipe Hands to detect hand positions.""" |
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def __init__(self, nb_hands=1): |
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"""Initialize the Hand Tracker.""" |
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self.hands = mp_hands.Hands( |
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static_image_mode=True, max_num_hands=nb_hands, min_detection_confidence=0.5 |
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) |
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def get_hands_positions(self, img): |
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"""Get the positions of the hands in the image.""" |
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img = cv2.flip(img, 1) |
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results = self.hands.process(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) |
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if results.multi_hand_landmarks is not None: |
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palm_centers = [] |
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for landmarks in results.multi_hand_landmarks: |
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middle_finger_pip_landmark = landmarks.landmark[ |
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mp_hands.HandLandmark.MIDDLE_FINGER_PIP |
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] |
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palm_center = np.array( |
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[middle_finger_pip_landmark.x, middle_finger_pip_landmark.y] |
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) |
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palm_center = [-(palm_center[0] - 0.5) * 2, (palm_center[1] - 0.5) * 2] |
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palm_centers.append(palm_center) |
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return palm_centers |
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return None |
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