环境
windows 10 64bit
mediapipe 0.8.10.1
前言
本文使用 google 家的 mediapipe 机器学习框架，结合 opencv 和 numpy，实现了一个实时识别 站立、坐下、走动、挥手 共4个动作的简单系统。
mediapipe 能做的事情非常多，感兴趣的童鞋可以去研究研究。
代码实践
首先，需要安装 mediapipe
pip install -U mediapipe接着，来看代码，部分加了注释
import cv2
import mediapipe as mp
import numpy as npdef calculate_angle(a, b, c):'''计算角度:param a::param b::param c::return:'''a = np.array(a)b = np.array(b)c = np.array(c)radians = np.arctan2(c[1] - b[1], c[0] - b[0]) - np.arctan2(a[1] - b[1], a[0] - b[0])angle = np.abs(radians * 180.0 / np.pi)if angle > 180.0:angle = 360 - anglereturn angledef calculate_dist(a, b):'''计算欧式距离:param a::param b::return:'''a = np.array(a)b = np.array(b)dist = np.linalg.norm(a - b)return distif __name__ == '__main__':mp_drawing = mp.solutions.drawing_utilsmp_pose = mp.solutions.posecap = cv2.VideoCapture('liuruoying.mp4')# 分辨率frame_width = int(cap.get(3))frame_height = int(cap.get(4))# 保存结果视频out = cv2.VideoWriter("result.mp4", cv2.VideoWriter_fourcc(*'mp4v'), 30, (frame_width, frame_height))counter = 0stage = Nonewith mp_pose.Pose(min_detection_confidence=0.3, min_tracking_confidence=0.8) as pose:while cap.isOpened():ret, frame = cap.read()if not ret:break# 转换下颜色空间image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)# 这里设置为不可写image.flags.writeable = False# 检测results = pose.process(image)# 这里设置为可写，颜色也转换回去image.flags.writeable = Trueimage = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)# 提取关键点try:landmarks = results.pose_landmarks.landmark# 获取相应关键点的坐标lshoulder = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x,landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y]lelbow = [landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].x,landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].y]lwrist = [landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x,landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y]lhip = [landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].x,landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].y]lankle = [landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].x,landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].y]lknee = [landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].x,landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].y]rshoulder = [landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].x,landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].y]relbow = [landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value].x,landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value].y]rwrist = [landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].x,landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].y]rhip = [landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value].x,landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value].y]rankle = [landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value].x,landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value].y]rknee = [landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value].x,landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value].y]# 计算角度langle = calculate_angle(lshoulder, lelbow, lwrist)rangle = calculate_angle(rshoulder, relbow, rwrist)lsangle = calculate_angle(lhip, lshoulder, lelbow)rsangle = calculate_angle(rhip, rshoulder, relbow)ankdist = calculate_dist(lankle, rankle)rwdist = calculate_dist(rhip, rwrist)lwdist = calculate_dist(lhip, lwrist)rhangle = calculate_angle(rshoulder, rhip, rknee)lhangle = calculate_angle(lshoulder, lhip, lknee)rkangle = calculate_angle(rankle, rknee, rhip)lkangle = calculate_angle(lankle, lknee, lhip)# 这块是具体的业务逻辑，各个数值，可根据自己实际情况适当调整if ((rhangle > 80 and lhangle > 80) and (rhangle < 110 and lhangle < 110) and (lkangle < 100 and rkangle < 100)):stage = 'sitting'elif (langle < 160 and langle > 40) or (rangle < 160 and rangle > 40):if ((lsangle > 20 or rsangle > 20) and (lwdist > 0.3 or rwdist > 0.3)):stage = "wave"elif ((ankdist > 0.084) and (langle > 150) and (rangle > 150)):counter += 1if counter > 1:stage = 'walking'else:stage = 'standing'counter = 0except:passcv2.rectangle(image, (0, 0), (225, 73), (245, 117, 16), -1)cv2.putText(image, 'STAGE', (65, 12), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 1, cv2.LINE_AA)cv2.putText(image, stage, (60, 60), cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255), 2, cv2.LINE_AA)# 画骨骼关键点mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS,mp_drawing.DrawingSpec(color=(245, 117, 66), thickness=2, circle_radius=2),mp_drawing.DrawingSpec(color=(245, 66, 230), thickness=2, circle_radius=2))# 显示结果帧cv2.imshow('mediapipe demo', image)# 保存结果帧out.write(image)# 按q退出if cv2.waitKey(10) & 0xFF == ord('q'):break# 资源释放cap.release()cv2.destroyAllWindows()
