一、需要准备的硬件

  1. Raspiberry 4b
  2. 两个SG90 180度舵机（注意舵机的角度，最好是180度且带限位的，切勿选360度舵机）
  3. 二自由度舵机云台（如下图）
  4. Raspiberry CSI 摄像头
    组装后的效果：

二、项目目标

追踪特定颜色的物体：
当物体移动时，摄像头通过控制两个伺服电机（分别是偏航和俯仰）把该物体放到视界的中心位置，我在这里追踪的是一支红色的铅笔。

三、具体步骤

3.1 获得被追踪对象的颜色参数

  1. 提前准备一张图片（如下图），可以直接用树莓派的CSI摄像头拍摄并保存，具体方法可以在我之前的文章里找到

  2. 利用下面的代码并通过调整滑块（Trackbar）获得红色铅笔的HSV颜色参数，为接下来的颜色追踪做准备

***color_detection.py***import cv2path='test_full.jpg'cv2.namedWindow("TrackBar")def nothing(x):pass#创建滑块控件cv2.createTrackbar("Hue Min","TrackBar",0,179,nothing)cv2.createTrackbar("Hue Max","TrackBar",179,179,nothing)cv2.createTrackbar("Sat Min","TrackBar",0,255,nothing)cv2.createTrackbar("Sat Max","TrackBar",255,255,nothing)cv2.createTrackbar("Val Min","TrackBar",0,255,nothing)cv2.createTrackbar("Val Max","TrackBar",255,255,nothing)while True:#读取目标图片image=cv2.imread(path)image=cv2.resize(image,(640,480))imgHSV=cv2.cvtColor(image,cv2.COLOR_BGR2HSV)hueLow=cv2.getTrackbarPos("Hue Min","TrackBar")hueHigh=cv2.getTrackbarPos("Hue Max","TrackBar")satLow=cv2.getTrackbarPos("Sat Min","TrackBar")satHigh=cv2.getTrackbarPos("Sat Max","TrackBar")valLow=cv2.getTrackbarPos("Val Min","TrackBar")valHigh=cv2.getTrackbarPos("Val Max","TrackBar")print(hueLow,hueHigh,satLow,satHigh,valLow,valHigh)#创建掩膜mask=cv2.inRange(imgHSV,(hueLow,satLow,valLow),(hueHigh,satHigh,valHigh))image=cv2.bitwise_and(image,image,mask=mask)#显示图像cv2.imshow('Origial',image)cv2.imshow('HSV',imgHSV)#按q键退出if cv2.waitKey(1)==ord('q'):breakcv2.destroyAllWindows()
  1. 运行color_detection.py，并调整滑块（TrackBar)如下图，当然你的被追踪物体的颜色不同，参数也必然不同。

    这时你会发现，红色铅笔被显示出来，其它部分被掩膜遮挡，记下Hue Min, Hui Max, Sat Min, Sat Max, Val Min, Val Max这六个数值在接下来的代码中会用到。

3.2 目标追踪代码

  1. 输入color_detection.py里得到的六个参数到相应位置，注释里已经注明。
***color_tracking.py***import cv2from picamera2 import Picamera2import timeimport numpy as npfrom servo import Servopicam2 = Picamera2()#偏航伺服电机连接上GPIO19脚，俯仰伺服电机信号线连接到GPIO16脚上pan=Servo(pin=19)tilt=Servo(pin=16)panAngle=0tiltAngle=0pan.set_angle(panAngle)tilt.set_angle(tiltAngle)#初始化pi cameradispW=1280dispH=720picam2.preview_configuration.main.size = (dispW,dispH)picam2.preview_configuration.main.format = "RGB888"picam2.preview_configuration.controls.FrameRate=30picam2.preview_configuration.align()picam2.configure("preview")picam2.start()fps=0pos=(30,60)font=cv2.FONT_HERSHEY_SIMPLEXheight=1.5weight=3myColor=(0,0,255)def nothing(x):passcv2.namedWindow('myTracker')#输入color_detection.py里得到的六个参数到xxx位置，比如cv2.createTrackbar('Hue Low','myTracker',xxx,179,nothing)cv2.createTrackbar('Hue Low','myTracker',56,179,nothing)cv2.createTrackbar('Hue High','myTracker',179,179,nothing)cv2.createTrackbar('Sat Low','myTracker',165,255,nothing)cv2.createTrackbar('Sat High','myTracker',255,255,nothing)cv2.createTrackbar('Val Low','myTracker',77,255,nothing)cv2.createTrackbar('Val High','myTracker',255,255,nothing)while True:tStart=time.time()#获取取摄像头图片frame= picam2.capture_array()frame=cv2.flip(frame,1)frameHSV=cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)cv2.putText(frame,str(int(fps))+' FPS',pos,font,height,myColor,weight)hueLow=cv2.getTrackbarPos('Hue Low','myTracker')satLow=cv2.getTrackbarPos('Sat Low','myTracker')valLow=cv2.getTrackbarPos('Val Low','myTracker')hueHigh=cv2.getTrackbarPos('Hue High','myTracker')satHigh=cv2.getTrackbarPos('Sat High','myTracker')valHigh=cv2.getTrackbarPos('Val High','myTracker')lowerBound=np.array([hueLow,satLow,valLow])upperBound=np.array([hueHigh,satHigh,valHigh])myMask=cv2.inRange(frameHSV,lowerBound,upperBound)myMaskSmall=cv2.resize(myMask,(int(dispW/2),int(dispH/2)))myObject=cv2.bitwise_and(frame,frame, mask=myMask)myObjectSmall=cv2.resize(myObject,(int(dispW/2),int(dispH/2)))contours,junk=cv2.findContours(myMask,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)if len(contours)>0:contours=sorted(contours,key=lambda x:cv2.contourArea(x),reverse=True)#cv2.drawContours(frame,contours,-1,(255,0,0),3)contour=contours[0]x,y,w,h=cv2.boundingRect(contour)cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255),3)#偏航电机纠偏X轴方向上的偏差，大于30度，偏航角度减小，小于-30度，偏航角度增加errorX=dispW/2-(x+w/2)if errorX>30:panAngle=panAngle-1if panAngle<-90:panAngle=-90pan.set_angle(panAngle)if errorX<-30:panAngle=panAngle+1if panAngle>90:panAngle=90pan.set_angle(panAngle)#俯仰电机纠偏Y轴方向上的偏差，大于30度，俯仰角度减小，小于-30度，俯仰角度增加errorY=dispH/2-(y+h/2)if errorY>30:tiltAngle=tiltAngle-1if tiltAngle<-90:tiltAngle=-90tilt.set_angle(tiltAngle)if errorY<-30:tiltAngle=tiltAngle+1if tiltAngle>90:tiltAngle=90tilt.set_angle(tiltAngle)cv2.imshow('Camera',frame)cv2.imshow('Mask',myMaskSmall)cv2.imshow('My Object',myObjectSmall)#按q键退出if cv2.waitKey(1)==ord('q'):pan.stop()tilt.stop()picam2.stop()breaktEnd=time.time()loopTime=tEnd-tStartfps=.9*fps + .1*(1/loopTime)cv2.destroyAllWindows()
  1. 上述代码中的from servo import Servo导入servo，这个库是没有的，我们要手动创建这个库，在object_tracking.py所在的目录下新建servo.py文件，复制下面的代码到文件中
#!/usr/bin/env python3import pigpiofrom time import sleep# Start the pigpiod daemonimport subprocessresult = Nonestatus = 1for x in range(3):p = subprocess.Popen('sudo pigpiod', shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)result = p.stdout.read().decode('utf-8')status = p.poll()if status == 0:breaksleep(0.2)if status != 0:print(status, result)'''> Use the DMA PWM of the pigpio library to drive the servo> Map the servo angle (0 ~ 180 degree) to (-90 ~ 90 degree)'''class Servo():MAX_PW = 1250# 0.5/20*100MIN_PW = 250 # 2.5/20*100_freq = 50 # 50 Hz, 20ms def __init__(self, pin, min_angle=-90, max_angle=90):self.pi = pigpio.pi()self.pin = pin self.pi.set_PWM_frequency(self.pin, self._freq)self.pi.set_PWM_range(self.pin, 10000)self.angle = 0self.max_angle = max_angleself.min_angle = min_angleself.pi.set_PWM_dutycycle(self.pin, 0)def set_angle(self, angle):if angle > self.max_angle:angle = self.max_angleelif angle < self.min_angle:angle = self.min_angleself.angle = angleduty = self.map(angle, -90, 90, 250, 1250)self.pi.set_PWM_dutycycle(self.pin, duty)def get_angle(self):return self.angledef stop(self):self.pi.set_PWM_dutycycle(self.pin, 0)self.pi.stop()# will be called automatically when the object is deleted# def __del__(self):# passdef map(self, x, in_min, in_max, out_min, out_max):return (x - in_min) * (out_max - out_min) / (in_max - in_min) + out_minif __name__ =='__main__':from vilib import Vilib# Vilib.camera_start(vflip=True,hflip=True) # Vilib.display(local=True,web=True)pan = Servo(pin=13, max_angle=90, min_angle=-90)tilt = Servo(pin=12, max_angle=30, min_angle=-90)panAngle = 0tiltAngle = 0pan.set_angle(panAngle)tilt.set_angle(tiltAngle)sleep(1)while True:for angle in range(0, 90, 1):pan.set_angle(angle)tilt.set_angle(angle)sleep(.01)sleep(.5)for angle in range(90, -90, -1):pan.set_angle(angle)tilt.set_angle(angle)sleep(.01)sleep(.5)for angle in range(-90, 0, 1):pan.set_angle(angle)tilt.set_angle(angle)sleep(.01)sleep(.5)
  1. 运行object_tracking.py，移动红色铅笔，摄像头就会自动追踪该对象