handData = findHands.marks(frame) # Get the locations of both hands & fingers handDataLength = len(handData) # Get the number of hands in the frame if handDataLength == 2: # We proceed only if there are two hands # The handData consists of 21 landmarks of each hand. We are inte...
results = hands.process(cv2.cvtColor(sample_img, cv2.COLOR_BGR2RGB)) if results.multi_hand_landmarks: for hand_no, hand_landmarks in enumerate(results.multi_hand_landmarks): print(f'HAND NUMBER: {hand_no+1}') print('---') for i in range(2): print(f'{mp_hands.HandLandmark(i...
results = hands.process(cv2.cvtColor(sample_img, cv2.COLOR_BGR2RGB))if results.multi_hand_landmarks: for hand_no, hand_landmarks in enumerate(results.multi_hand_landmarks): print(f'HAND NUMBER: {hand_no+1}') print('---') for i in range(2): print(f'{mp_hands.HandLandmark...
The ability to perceive the shape and motion of hands can be a vital component in improving the user experience across a variety of technological domains and platforms. For example, it can form the basis for sign language understanding and hand gesture control, and can also enable the overlay ...
results = hands.process(cv2.cvtColor(sample_img, cv2.COLOR_BGR2RGB)) if results.multi_hand_landmarks: for hand_no, hand_landmarks in enumerate(results.multi_hand_landmarks): print(f'HAND NUMBER: {hand_no+1}') print('---') for i in range(2): print(f...
self._landmark_names)), 'Unexpected number of landmarks: {}'.format(landmarks.shape[0]) landmarks = self._normalize_landmarks(landmarks) # Get embedding. embedding = self._get_embedding(landmarks) return embedding else: print('ERROR: Can NOT embedding the data you provided !') ...
results = hands.process(cv2.cvtColor(sample_img, cv2.COLOR_BGR2RGB)) if results.multi_hand_landmarks: for hand_no, hand_landmarks in enumerate(results.multi_hand_landmarks): print(f'HAND NUMBER: {hand_no+1}') print('---') for i in range(2): print(f...
recognizer.Dataset.from_folder方法，它也调用了method _get_hand_data_get_hand_dataNumber of hands...
在该图中，首先单独处理每只手，然后收集每只手的惯用手和界标并将其分组在向量内。因此，我在检测到...
max_num_hands: Maximum number of hands to detect. Defaults to 2. min_detection_confidence: Minimum confidence value (between 0 and 1) for the hand detection to be considered successful. Defaults to 0.5. min_tracking_confidence: Minimum confidence value (between 0 and 1) for the hand landmar...