最近，我被委托使用gazebo中已经制造的机器人，使用Ros，它有一个摄像头，我可以通过.py代码看到图像。现在他们让我过滤颜色(绿色、红色和蓝色(，我已经有了高值和低值，我可以用图像来做，但我不知道如何混合这两个程序，所以按颜色过滤的东西，我只知道什么传输机器人的相机，而不知道图像。
所有这些，同时使用Open CV
附两个代码
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Code to see the gazeebo virtual camera
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#!/usr/bin/env python
import rospy
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
import cv2
bridge_object = CvBridge() # create the cv_bridge object
image_received = 0 #Flag to indicate that we have already received an image
cv_image = 0 #This is just to create the global variable cv_image
def show_image():
image_sub = rospy.Subscriber("/two_wheels_robot/camera1/image_raw",Image,camera_callback)
r = rospy.Rate(10) #10Hz
while not rospy.is_shutdown():
if image_received:
cv2.waitKey(1)
r.sleep()
cv2.destroyAllWindows()
def camera_callback(data):
global bridge_object
global cv_image
global image_received
image_received=1
try:
print("received ROS image, I will convert it to opencv")
# We select bgr8 because its the OpenCV encoding by default
cv_image = bridge_object.imgmsg_to_cv2(data, desired_encoding="bgr8")
#Add your code to save the image here:
#Save the image "img" in the current path
cv2.imwrite('robot_image.jpg', cv_image)
#Display the image in a window
cv2.imshow('Image from robot camera', cv_image)
except CvBridgeError as e:
print(e)
if __name__ == '__main__':
rospy.init_node('load_image', anonymous=True)
show_image()
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code to see an image segmented in RGB by windows
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#!/usr/bin/env python
import rospy
from sensor_msgs.msg import Image
#Import the numpy library which will help with some matrix operations
import numpy as np
from cv_bridge import CvBridge, CvBridgeError
import cv2
bridge_object = CvBridge() # create the cv_bridge object
image_received = 0 #Flag to indicate that we have already received an image
cv_image = 0 #This is just to create the global variable cv_image
def show_image():
image_sub = rospy.Subscriber("/two_wheels_robot/camera1/image_raw",Image,camera_callback)
r = rospy.Rate(10) #10Hz
image = cv2.imread('/home/user/catkin_ws/src/opencv_for_robotics_images/Unit_2/Course_images/Filtering.png')
while not rospy.is_shutdown():
#I resized the image so it can be easier to work with
image = cv2.resize(image,(300,300))
#Once we read the image we need to change the color space to HSV
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
#Hsv limits are defined
#here is where you define the range of the color you're looking for
#each value of the vector corresponds to the H,S & V values respectively
min_green = np.array([50,220,220])
max_green = np.array([60,255,255])
min_red = np.array([170,220,220])
max_red = np.array([180,255,255])
min_blue = np.array([110,220,220])
max_blue = np.array([120,255,255])
#This is the actual color detection
#Here we will create a mask that contains only the colors defined in your limits
#This mask has only one dimension, so its black and white }
mask_g = cv2.inRange(hsv, min_green, max_green)
mask_r = cv2.inRange(hsv, min_red, max_red)
mask_b = cv2.inRange(hsv, min_blue, max_blue)
#We use the mask with the original image to get the colored post-processed image
res_b = cv2.bitwise_and(image, image, mask= mask_b)
res_g = cv2.bitwise_and(image,image, mask= mask_g)
res_r = cv2.bitwise_and(image,image, mask= mask_r)
cv2.imshow('Green',res_g)
cv2.imshow('Red',res_b)
cv2.imshow('Blue',res_r)
cv2.imshow('Original',image)
cv2.waitKey(1)
r.sleep()
cv2.destroyAllWindows()
def camera_callback(data):
global bridge_object
global cv_image
global image_received
image_received=1
try:
print("received ROS image, I will convert it to opencv")
# We select bgr8 because its the OpenCV encoding by default
cv_image = bridge_object.imgmsg_to_cv2(data, desired_encoding="bgr8")
except CvBridgeError as e:
print(e)
if __name__ == '__main__':
rospy.init_node('opencv_example1', anonymous=True)
show_image()
首先，代码中有很多结构问题。您应该考虑使用类，并通过实现相互通信的独立节点来遵循ROS哲学。请看一下rospy教程。
致"；混合"；两个程序都可以创建一个函数，在接收图像的第一个程序中处理颜色
def process_image(image):
image = cv2.resize(image,(300,300))
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
min_green = np.array([50,220,220])
max_green = np.array([60,255,255])
min_red = np.array([170,220,220])
max_red = np.array([180,255,255])
min_blue = np.array([110,220,220])
max_blue = np.array([120,255,255])
mask_g = cv2.inRange(hsv, min_green, max_green)
mask_r = cv2.inRange(hsv, min_red, max_red)
mask_b = cv2.inRange(hsv, min_blue, max_blue)
res_b = cv2.bitwise_and(image, image, mask= mask_b)
res_g = cv2.bitwise_and(image,image, mask= mask_g)
res_r = cv2.bitwise_and(image,image, mask= mask_r)
cv2.imshow('Green',res_g)
cv2.imshow('Red',res_b)
cv2.imshow('Blue',res_r)
cv2.imshow('Original',image)
cv2.waitKey(1)
并在每次收到图像时调用它一次(在回调中(。通常，最好将所有这些处理划分为多个线程，但是，作为起点，您可以使用以下内容：
#!/usr/bin/env python
import rospy
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
import cv2
bridge_object = CvBridge() # create the cv_bridge object
image_received = 0 #Flag to indicate that we have already received an image
cv_image = 0 #This is just to create the global variable cv_image
def show_image():
image_sub = rospy.Subscriber("/two_wheels_robot/camera1/image_raw",Image,camera_callback)
r = rospy.Rate(10) #10Hz
while not rospy.is_shutdown():
if image_received:
cv2.waitKey(1)
r.sleep()
cv2.destroyAllWindows()
def process_image(image):
image = cv2.resize(image,(300,300))
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
min_green = np.array([50,220,220])
max_green = np.array([60,255,255])
min_red = np.array([170,220,220])
max_red = np.array([180,255,255])
min_blue = np.array([110,220,220])
max_blue = np.array([120,255,255])
mask_g = cv2.inRange(hsv, min_green, max_green)
mask_r = cv2.inRange(hsv, min_red, max_red)
mask_b = cv2.inRange(hsv, min_blue, max_blue)
res_b = cv2.bitwise_and(image, image, mask= mask_b)
res_g = cv2.bitwise_and(image,image, mask= mask_g)
res_r = cv2.bitwise_and(image,image, mask= mask_r)
cv2.imshow('Green',res_g)
cv2.imshow('Red',res_b)
cv2.imshow('Blue',res_r)
cv2.imshow('Original',image)
cv2.waitKey(1)
def camera_callback(data):
global bridge_object
global cv_image
global image_received
image_received=1
try:
print("received ROS image, I will convert it to opencv")
# We select bgr8 because its the OpenCV encoding by default
cv_image = bridge_object.imgmsg_to_cv2(data, desired_encoding="bgr8")
#Add your code to save the image here:
#Save the image "img" in the current path
cv2.imwrite('robot_image.jpg', cv_image)
## Calling the processing function
process_image(cv_image)
cv2.imshow('Image from robot camera', cv_image)
except CvBridgeError as e:
print(e)
if __name__ == '__main__':
rospy.init_node('load_image', anonymous=True)
show_image()
您还应该避免在函数中声明全局变量。