树莓派,opencv,Picamera2利用舵机云台追踪特定颜色对象

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:
    在这里插入图片描述

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
    树莓派,opencv,Picamera2利用舵机云台追踪特定颜色对象_第1张图片

  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 cv2
path='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'):
        break
cv2.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。
    树莓派,opencv,Picamera2利用舵机云台追踪特定颜色对象_第2张图片
    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。
    树莓派,opencv,Picamera2利用舵机云台追踪特定颜色对象_第3张图片

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 cv2
from picamera2 import Picamera2
import time
import numpy as np
from servo import Servo
picam2 = 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=0
tiltAngle=0

pan.set_angle(panAngle)
tilt.set_angle(tiltAngle)

#初始化pi camera
dispW=1280
dispH=720
picam2.preview_configuration.main.size = (dispW,dispH)
picam2.preview_configuration.main.format = "RGB888"
picam2.preview_configuration.controls.FrameRate=30
picam2.preview_configuration.align()
picam2.configure("preview")
picam2.start()
fps=0
pos=(30,60)
font=cv2.FONT_HERSHEY_SIMPLEX
height=1.5
weight=3
myColor=(0,0,255)

def nothing(x):
    pass

cv2.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-1
            if panAngle<-90:
                panAngle=-90
            pan.set_angle(panAngle)
        if errorX<-30:
            panAngle=panAngle+1
            if panAngle>90:
                panAngle=90
            pan.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-1
            if tiltAngle<-90:
                tiltAngle=-90
            tilt.set_angle(tiltAngle)
        if errorY<-30:
            tiltAngle=tiltAngle+1
            if tiltAngle>90:
                tiltAngle=90
            tilt.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()
        break
    tEnd=time.time()
    loopTime=tEnd-tStart
    fps=.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 python3
import pigpio
from time import sleep
# Start the pigpiod daemon
import subprocess
result = None
status = 1
for 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:
        break
    sleep(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*100
    MIN_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 = 0
        self.max_angle = max_angle
        self.min_angle = min_angle
        self.pi.set_PWM_dutycycle(self.pin, 0)

    def set_angle(self, angle):
        if angle > self.max_angle:
            angle = self.max_angle
        elif angle < self.min_angle:
            angle = self.min_angle
        self.angle = angle
        duty = self.map(angle, -90, 90, 250, 1250)
        self.pi.set_PWM_dutycycle(self.pin, duty)


    def get_angle(self):
        return self.angle

	def 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):
    #     pass

    def map(self, x, in_min, in_max, out_min, out_max):
        return (x - in_min) * (out_max - out_min) / (in_max - in_min) + out_min


if __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 = 0
    tiltAngle = 0
    pan.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
    树莓派,opencv,Picamera2利用舵机云台追踪特定颜色对象_第4张图片

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