MULTI_HAND_LANDMARKS: 被检测/跟踪的手的集合,其中每只手被表示为21个手部地标的列表,每个地标由x, y, z组成。x和y分别由图像的宽度和高度归一化为[0,1]。Z表示地标深度。 MULTI_HANDEDNESS: 被检测/追踪的手是左手还是右手的集合。每只手由label(标签)和score(分数)组成。label 是‘Left’ 或‘Right’...
multi_handedness[h_idx].classification[0].label) + ", " print(hand_info) 结果如下 0:Left, 1:Right, Process finished with exit code 0 单帧手势识别代码优化 完整代码 import cv2 import mediapipe as mp import matplotlib.pyplot as plt if __name__ == '__main__': mp_hands = mp....
2.multi_hand_world_landmarks 这个参数跟multi_hand_landmarks 的形式一致,但是坐标的组织方式不同,根据官方说明,检测到跟踪的手的集合,其中每只手都表示为世界坐标中 21 个手地标的列表。每个地标由x、y和z组成,以米为单位的真实世界 3D 坐标,原点位于手部的近似几何中心。 3.multi_handedness 这个参数记录...
results = hands.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) # Print handedness and draw hand landmarks on the image. print('Handedness:', results.multi_handedness) if not results.multi_hand_landmarks: continue image_hight, image_width, _ = image.shape annotated_image = image.copy(...
# MULTI_HANDEDNESS: 被检测/追踪的手是左手还是右手的集合。每只手由label(标签)和score(分数)组成。 label 是 'Left' 或 'Right' 值的字符串。 score 是预测左右手的估计概率。mpDraw=mp.solutions.drawing_utils# 创建检测手部关键点和关键点之间连线的方法whileTrue:success,img=cap.read()# 从摄像投...
print('Handedness:', results.multi_handedness) if not results.multi_hand_landmarks: continue image_height, image_width, _ = image.shape annotated_image = image.copy() for hand_landmarks in results.multi_hand_landmarks: print('hand_landmarks:', hand_landmarks) ...
multi_hand_landmarks != None: #print(results.multi_handedness) for hand in results.multi_handedness: #print(hand) #print(hand.classification) #print(hand.classification[0]) handType=hand.classification[0].label handsType.append(handType) for handLandMarks in results.multi_hand_landmarks: ...
MULTI_HANDEDNESS Collection of handedness of the detected/tracked hands (i.e. is it a left or right hand). Each hand is composed oflabelandscore.labelis a string of value either"Left"or"Right".scoreis the estimated probability of the predicted handedness and is always greater than or equ...
hand_21 = results.multi_hand_landmarks[hand_idx] # 可视化关键点及骨架连线 mpDraw.draw_landmarks(img, hand_21, mp_hands.HAND_CONNECTIONS) # 记录左右手信息 temp_handness = results.multi_handedness[hand_idx].classification[0].label
results.multi_handedness: 包括label和score,label是字符串'Left'或'Right',score是置信度 results.multi_hand_landmarks: 手部21个关键点的位置信息,包括x,y,z 其中x,y是归一化后的坐标。z代表地标深度,以手腕处的深度为原点,值越小,地标就越靠近相机(我暂时也不清楚啥意思) 视频检测代码 import cv2 import...