使用 Python 和 Gazebo 在 Ros 中过滤颜色
最近，我受委托使用 Gazebo 中已经制作的机器人，使用带有摄像头的 Ros，我已经能够通过 .py 代码看到该图像。现在他们要求我过滤颜色（绿色，红色和蓝色），我已经有了高值和低值，并且我可以用图像来完成它，但我不知道如何混合这两个程序，以便过滤掉什么通过颜色，我只知道机器人相机传输的是什么，而不是图像。
所有这一切都是在使用 Open CV 时
附加的两个代码
////////////////////////////////////////////////////////////////////////////////////////
Code to see the gazeebo virtual camera
////////////////////////////////////////////////////////////////////////////////////////
#!/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()
////////////////////////////////////////////////////////////////////////////////////////
code to see an image segmented in RGB by windows
////////////////////////////////////////////////////////////////////////////////////////
#!/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()
recently I was commissioned to use a robot already made in gazebo, using Ros which has a camera and I have been able to see that image through .py code. Now they ask me to filter colors (green, red and blue), I already have the high and low values, and I can do it with an image, but I don't know how to mix both programs, so that what is filtered by color, I only know what transmit the robot's camera and not an image.
All of this while using Open CV
Attached both codes
////////////////////////////////////////////////////////////////////////////////////////
Code to see the gazeebo virtual camera
////////////////////////////////////////////////////////////////////////////////////////
#!/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()
////////////////////////////////////////////////////////////////////////////////////////
code to see an image segmented in RGB by windows
////////////////////////////////////////////////////////////////////////////////////////
#!/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()
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评论（1）
首先，该代码中存在很多结构问题。您应该考虑使用类并通过实现相互通信的单独节点来遵循 ROS 理念。另请参阅 rospy 教程。
要“混合”这两个程序，您可以创建一个函数来处理接收图像的第一个程序中的颜色
，并在每次接收图像时调用它一次（在回调内）。通常最好将所有这些处理划分为多个线程，但是，作为起点，您可以使用如下内容：
您还应该避免在函数内声明全局变量。
First of all there a lot structural problems in that code. You should consider using Classes and follow the ROS philosophy by implementing separates nodes that communicates with each other. Please take a look also to the rospy tutorials.
To "mix" both programs you can either create a function that processes the color in your first program that receives the image
And calling it once every time you receive an image (inside the callback). Usually it's preferable to divide all this processing in multiple threads, but, as a start point you could use something like this:
You should also avoid declaring globals variables inside a function.