健身也内卷？这届网友用 Python 掌握了做标准俯卧撑的秘诀

编者按：自己在家锻炼时，我们很难知道自己的动作是否标准。本文作者用Python写了一个可以检测俯卧撑动作是否标准的程序，一起来看看他是怎么做的。

原文链接：https://aryanvij02.medium.com/push-ups-with-python-mediapipe-open-a544bd9b4351

GitHub 地址：https://github.com/aryanvij02/PushUpCounter

译者 | 章雨铭       责编 | 屠敏

在新加坡军队中，有一种测试叫做IPPT（个人身体素质测试）。这个测试的困难不在于它对体力的要求有多高，而在于用来计算做俯卧撑和仰卧起坐次数的电子机器。

和大多数人一样，我的俯卧撑动作总是不达标（根据机器的意见）。此外，由于缺乏参照机器标准的练习，许多NSMen（已经完成两年强制性服役的人）在IPPT测试中都难以取得好成绩。

因此，我决定使用mediapipe和OpenCV创建一个程序，跟踪我们的俯卧撑动作，确保我们每一个俯卧撑动作都达标。

由mediapipe姿势模块检测到的肢体关节

import cv2  import mediapipe as mp  import math    class poseDetector() :            def __init__(self, mode=False, complexity=1, smooth_landmarks=True,                   enable_segmentation=False, smooth_segmentation=True,                   detectionCon=0.5, trackCon=0.5):                    self.mode = mode           self.complexity = complexity          self.smooth_landmarks = smooth_landmarks          self.enable_segmentation = enable_segmentation          self.smooth_segmentation = smooth_segmentation          self.detectionCon = detectionCon          self.trackCon = trackCon                    self.mpDraw = mp.solutions.drawing_utils          self.mpPose = mp.solutions.pose          self.pose = self.mpPose.Pose(self.mode, self.complexity, self.smooth_landmarks,                                       self.enable_segmentation, self.smooth_segmentation,                                       self.detectionCon, self.trackCon)                          def findPose (self, img, draw=True):          imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)          self.results = self.pose.process(imgRGB)                    if self.results.pose_landmarks:              if draw:                  self.mpDraw.draw_landmarks(img,self.results.pose_landmarks,                                             self.mpPose.POSE_CONNECTIONS)                            return img            def findPosition(self, img, draw=True):          self.lmList = []          if self.results.pose_landmarks:              for id, lm in enumerate(self.results.pose_landmarks.landmark):                  #finding height, width of the image printed                  h, w, c = img.shape                  #Determining the pixels of the landmarks                  cx, cy = int(lm.x * w), int(lm.y * h)                  self.lmList.append([id, cx, cy])                  if draw:                      cv2.circle(img, (cx, cy), 5, (255,0,0), cv2.FILLED)          return self.lmList                def findAngle(self, img, p1, p2, p3, draw=True):             #Get the landmarks          x1, y1 = self.lmList[p1][1:]          x2, y2 = self.lmList[p2][1:]          x3, y3 = self.lmList[p3][1:]                    #Calculate Angle          angle = math.degrees(math.atan2(y3-y2, x3-x2) -                                math.atan2(y1-y2, x1-x2))          if angle < 0:              angle += 360              if angle > 180:                  angle = 360 - angle          elif angle > 180:              angle = 360 - angle          # print(angle)                    #Draw          if draw:              cv2.line(img, (x1, y1), (x2, y2), (255,255,255), 3)              cv2.line(img, (x3, y3), (x2, y2), (255,255,255), 3)                              cv2.circle(img, (x1, y1), 5, (0,0,255), cv2.FILLED)              cv2.circle(img, (x1, y1), 15, (0,0,255), 2)              cv2.circle(img, (x2, y2), 5, (0,0,255), cv2.FILLED)              cv2.circle(img, (x2, y2), 15, (0,0,255), 2)              cv2.circle(img, (x3, y3), 5, (0,0,255), cv2.FILLED)              cv2.circle(img, (x3, y3), 15, (0,0,255), 2)                            cv2.putText(img, str(int(angle)), (x2-50, y2+50),                           cv2.FONT_HERSHEY_PLAIN, 2, (0,0,255), 2)          return angle              def main():      detector = poseDetector()      cap = cv2.VideoCapture(0)      while cap.isOpened():          ret, img = cap.read() #ret is just the return variable, not much in there that we will use.           if ret:                  img = detector.findPose(img)              cv2.imshow('Pose Detection', img)          if cv2.waitKey(10) & 0xFF == ord('q'):              break                    cap.release()      cv2.destroyAllWindows()        if __name__ == "__main__":      main()

以上是这个程序的代码。

上面的代码来源于PoseModule.py，有以下几个功能：

• 激活mediapipe的姿势检测模块。

• 检测人体。

• 根据模型找到人体上不同肢体关节的位置。(肢体显示在上面的图片中）。

• 查找关节之间的角度（取决于你选择的关节）。对于我的俯卧撑程序，我选择找到肘部、肩部和臀部的角度，因为这些对俯卧撑动作的标准至关重要。

接下来是实际的俯卧撑计数的代码。我们使用PoseModule并确定一个俯卧撑合格与否的标准。

import cv2  import mediapipe as mp  import numpy as np  import PoseModule as pm        cap = cv2.VideoCapture(0)  detector = pm.poseDetector()  count = 0  direction = 0  form = 0  feedback = "Fix Form"      while cap.isOpened():      ret, img = cap.read() #640 x 480      #Determine dimensions of video - Help with creation of box in Line 43      width  = cap.get(3)  # float `width`      height = cap.get(4)  # float `height`      # print(width, height)            img = detector.findPose(img, False)      lmList = detector.findPosition(img, False)      # print(lmList)      if len(lmList) != 0:          elbow = detector.findAngle(img, 11, 13, 15)          shoulder = detector.findAngle(img, 13, 11, 23)          hip = detector.findAngle(img, 11, 23,25)                    #Percentage of success of pushup          per = np.interp(elbow, (90, 160), (0, 100))                    #Bar to show Pushup progress          bar = np.interp(elbow, (90, 160), (380, 50))            #Check to ensure right form before starting the program          if elbow > 160 and shoulder > 40 and hip > 160:              form = 1                #Check for full range of motion for the pushup          if form == 1:              if per == 0:                  if elbow <= 90 and hip > 160:                      feedback = "Up"                      if direction == 0:                          count += 0.5                          direction = 1                  else:                      feedback = "Fix Form"                                    if per == 100:                  if elbow > 160 and shoulder > 40 and hip > 160:                      feedback = "Down"                      if direction == 1:                          count += 0.5                          direction = 0                  else:                      feedback = "Fix Form"                          # form = 0                                                        print(count)                    #Draw Bar          if form == 1:              cv2.rectangle(img, (580, 50), (600, 380), (0, 255, 0), 3)              cv2.rectangle(img, (580, int(bar)), (600, 380), (0, 255, 0), cv2.FILLED)              cv2.putText(img, f'{int(per)}%', (565, 430), cv2.FONT_HERSHEY_PLAIN, 2,                          (255, 0, 0), 2)              #Pushup counter          cv2.rectangle(img, (0, 380), (100, 480), (0, 255, 0), cv2.FILLED)          cv2.putText(img, str(int(count)), (25, 455), cv2.FONT_HERSHEY_PLAIN, 5,                      (255, 0, 0), 5)                    #Feedback           cv2.rectangle(img, (500, 0), (640, 40), (255, 255, 255), cv2.FILLED)          cv2.putText(img, feedback, (500, 40 ), cv2.FONT_HERSHEY_PLAIN, 2,                      (0, 255, 0), 2)                  cv2.imshow('Pushup counter', img)      if cv2.waitKey(10) & 0xFF == ord('q'):          break            cap.release()  cv2.destroyAllWindows()

有个需要注意的地方在第17-21行。确定从相机捕捉到的图像的分辨率，并在绘制俯卧撑计数的矩形时调整像素值，等等。(第68-82行)。

我们完成了！一个能确保动作标准的俯卧撑计数软件。没有完全俯下？不算数! 膝盖放在了地上？不算数！

快乐的做俯卧撑吧！