1.物體識別

本案例實現對特殊顏色物體的識別，並實現根據物體位置的改變進行控制跟隨。

import cv2 as cv

# 定義結構元素
kernel = cv.getStructuringElement(cv.MORPH_RECT,(3,3))
# print kernel

capture = cv.VideoCapture(0)		
print capture.isOpened()
ok,frame = capture.read()
lower_b = (65,43,46)
upper_b = (110,255,255)

height,width = frame.shape[0:2]
screen_center = width / 2
offset = 50

while ok:
 # 將影象轉成HSV顏色空間
 hsv_frame = cv.cvtColor(frame,cv.COLOR_BGR2HSV)
 # 基於顏色的物體提取
 mask = cv.inRange(hsv_frame,lower_b,upper_b)
 mask2 = cv.morphologyEx(mask,cv.MORPH_OPEN,kernel)
 mask3 = cv.morphologyEx(mask2,cv.MORPH_CLOSE,kernel)
 
 # 找出面積最大的區域
 _,contours,_ = cv.findContours(mask3,cv.RETR_EXTERNAL,cv.CHAIN_APPROX_SIMPLE)

 maxArea = 0
 maxIndex = 0
 for i,c in enumerate(contours):
 area = cv.contourArea(c)
 if area > maxArea:
 maxArea = area
 maxIndex = i
	# 繪製
 cv.drawContours(frame,maxIndex,(255,0),2)
 # 獲取外切矩形
 x,y,w,h = cv.boundingRect(contours[maxIndex])
 cv.rectangle(frame,(x,y),(x+w,y+h),2)
 # 獲取中心畫素點
 center_x = int(x + w/2)
 center_y = int(y + h/2)
 cv.circle(frame,(center_x,center_y),5,(0,255),-1)

 # 簡單的列印反饋資料，之後補充運動控制
 if center_x < screen_center - offset:
 print "turn left"
 elif screen_center - offset <= center_x <= screen_center + offset:
 print "keep"
 elif center_x > screen_center + offset:
 print "turn right"

 cv.imshow("mask4",mask3)
 cv.imshow("frame",frame)
 cv.waitKey(1)
 ok,frame = capture.read()

實際效果圖

2.移動跟隨

結合ROS控制turtlebot3或其他機器人運動，turtlebot3機器人的教程見我另一個博文：ROS控制Turtlebot3

首先啟動turtlebot3，如下程式碼可以放在機器人的樹莓派中，將相機插在USB口即可

程式碼示例：

import rospy
import cv2 as cv
from geometry_msgs.msg import Twist


def shutdown():
 twist = Twist()
 twist.linear.x = 0
 twist.angular.z = 0
 cmd_vel_Publisher.publish(twist)
 print "stop"


if __name__ == '__main__':
 rospy.init_node("follow_node")
 rospy.on_shutdown(shutdown)
 rate = rospy.Rate(100)

 cmd_vel_Publisher = rospy.Publisher("/cmd_vel",Twist,queue_size=1)
 # 定義結構元素
 kernel = cv.getStructuringElement(cv.MORPH_RECT,3))
 # print kernel

 capture = cv.VideoCapture(0)
 print capture.isOpened()
 ok,frame = capture.read()
 lower_b = (65,46)
 upper_b = (110,255)

 height,width = frame.shape[0:2]
 screen_center = width / 2
 offset = 50

 while not rospy.is_shutdown():
 # 將影象轉成HSV顏色空間
 hsv_frame = cv.cvtColor(frame,kernel)

 # 找出面積最大的區域
 _,c in enumerate(contours):
 area = cv.contourArea(c)
 if area > maxArea:
 maxArea = area
 maxIndex = i
 # 繪製
 cv.drawContours(frame,(x + w,y + h),2)
 # 獲取中心畫素點
 center_x = int(x + w / 2)
 center_y = int(y + h / 2)
 cv.circle(frame,-1)

 # 簡單的列印反饋資料，之後補充運動控制
 twist = Twist()
 if center_x < screen_center - offset:
 twist.linear.x = 0.1
 twist.angular.z = 0.5
 print "turn left"
 elif screen_center - offset <= center_x <= screen_center + offset:
 twist.linear.x = 0.3
 twist.angular.z = 0
 print "keep"
 elif center_x > screen_center + offset:
 twist.linear.x = 0.1
 twist.angular.z = -0.5
 print "turn right"
 else:
 twist.linear.x = 0
 twist.angular.z = 0
 print "stop"

 # 將速度發出
 cmd_vel_Publisher.publish(twist)

 # cv.imshow("mask4",mask3)
 # cv.imshow("frame",frame)
 cv.waitKey(1)
 rate.sleep()
 ok,frame = capture.read()

總結

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