stretch_tutorials/ros1_melodic/example_7.md

Example 7

In this example, we will review the image_view ROS package and a Python script that captures an image from the RealSense camera.

BBegin by checking out the feature/upright_camera_view branch in the stretch_ros repository. The configuration of the camera results in the images being displayed sideways. Thus, this branch publishes a new topic that rotates the raw image upright.

cd ~/catkin_ws/src/stretch_ros/stretch_core
git checkout feature/upright_camera_view

Then run the stretch driver launch file.

# Terminal 1
roslaunch stretch_core stretch_driver.launch

To activate the RealSense camera and publish topics to be visualized, run the following launch file in a new terminal.

# Terminal 2
roslaunch stretch_core d435i_low_resolution.launch

Within this tutorial package, there is an RViz config file with the topics for perception already in the Display tree. You can visualize these topics and the robot model by running the command below in a new terminal.

# Terminal 3
rosrun rviz rviz -d /home/hello-robot/catkin_ws/src/stretch_tutorials/rviz/perception_example.rviz

Capture Image with image_view

There are a couple of methods to save an image using the image_view package.

OPTION 1: Use the image_view node to open a simple image viewer for ROS sensor_msgs/image topics.

# Terminal 4
rosrun image_view image_view image:=/camera/color/image_raw_upright_view

Then you can save the current image by right-clicking on the display window. By deafult, images will be saved as frame000.jpg, frame000.jpg, etc. Note, that the image will be saved to the terminal's current work directory.

OPTION 2: Use the image_saver node to save an image to the terminals current work directory.

# Terminal 4
rosrun image_view image_saver image:=/camera/color/image_raw_upright_view

Capture Image with Python Script

In this section, you can use a Python node to capture an image from the RealSense camera. Execute the capture_image.py node to save a .jpeg image of the image topic /camera/color/image_raw_upright_view.

# Terminal 4
cd ~/catkin_ws/src/stretch_tutorials/src
python capture_image.py

An image named camera_image.jpeg is saved in the stored_data folder in this package.

The Code

#!/usr/bin/env python

import rospy
import sys
import os
import cv2

from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError

class CaptureImage:
    """
    A class that converts a subscribed ROS image to a OpenCV image and saves
    the captured image to a predefined directory.
    """
    def __init__(self):
        """
        A function that initializes a CvBridge class, subscriber, and save path.
        :param self: The self reference.
        """
        self.bridge = CvBridge()
        self.sub = rospy.Subscriber('/camera/color/image_raw', Image, self.callback, queue_size=1)
        self.save_path = '/home/hello-robot/catkin_ws/src/stretch_tutorials/stored_data'

    def callback(self, msg):
        """
        A callback function that converts the ROS image to a CV2 image and stores the
        image.
        :param self: The self reference.
        :param msg: The ROS image message type.
        """
        try:
            image = self.bridge.imgmsg_to_cv2(msg, 'bgr8')
        except CvBridgeError, e:
            rospy.logwarn('CV Bridge error: {0}'.format(e))

        file_name = 'camera_image.jpeg'
        completeName = os.path.join(self.save_path, file_name)
        cv2.imwrite(completeName, image)
        rospy.signal_shutdown("done")
        sys.exit(0)

if __name__ == '__main__':
    rospy.init_node('capture_image', argv=sys.argv)
    CaptureImage()
    rospy.spin()

The Code Explained

Now let's break the code down.

#!/usr/bin/env python

Every Python ROS Node will have this declaration at the top. The first line makes sure your script is executed as a Python script.

import rospy
import sys
import os
import cv2

You need to import rospy if you are writing a ROS Node. There are functions from sys, os, and cv2 that are required within this code. cv2 is a library of Python functions that implements computer vision algorithms. Further information about cv2 can be found here: OpenCV Python.

from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError

The sensor_msgs.msg is imported so that we can subscribe to ROS Image messages. Import CvBridge to convert between ROS Image messages and OpenCV images.

def __init__(self):
    """
    A function that initializes a CvBridge class, subscriber, and save path.
    :param self: The self reference.
    """
    self.bridge = CvBridge()
    self.sub = rospy.Subscriber('/camera/color/image_raw', Image, self.callback, queue_size=1)
    self.save_path = '/home/hello-robot/catkin_ws/src/stretch_tutorials/stored_data'

Initialize the CvBridge class, the subscriber, and the directory of where the captured image will be stored.

def callback(self, msg):
    """
    A callback function that converts the ROS image to a cv2 image and stores the
    image.
    :param self: The self reference.
    :param msg: The ROS image message type.
    """
    try:
        image = self.bridge.imgmsg_to_cv2(msg, 'bgr8')
    except CvBridgeError as e:
        rospy.logwarn('CV Bridge error: {0}'.format(e))

Try to convert the ROS Image message to a cv2 Image message using the imgmsg_to_cv2() function.

file_name = 'camera_image.jpeg'
completeName = os.path.join(self.save_path, file_name)
cv2.imwrite(completeName, image)

Join the directory and file name using the path.join() function. Then use the imwrite() function to save the image.

rospy.signal_shutdown("done")
sys.exit(0)

The first line of code initiates a clean shutdown of ROS. The second line of code exits the Python interpreter.

rospy.init_node('capture_image', argv=sys.argv)
CaptureImage()

The next line, rospy.init_node(NAME, ...), is very important as it tells rospy the name of your node -- until rospy has this information, it cannot start communicating with the ROS Master. NOTE: the name must be a base name, i.e. it cannot contain any slashes "/".

Instantiate the CaptureImage() class.

rospy.spin()

Give control to ROS. This will allow the callback to be called whenever new messages come in. If we don't put this line in, then the node will not work, and ROS will not process any messages.

Edge Detection

In this section, we highlight a node that utilizes the Canny Edge filter algorithm to detect the edges from an image and convert it back as a ROS image to be visualized in RViz. Begin by running the following commands.

# Terminal 4
cd ~/catkin_ws/src/stretch_tutorials/src
python edge_detection.py

The node will publish a new Image topic named /image_edge_detection. This can be visualized in RViz and a gif is provided below for reference.

The Code

#!/usr/bin/env python

import rospy
import sys
import os
import cv2

from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError

class EdgeDetection:
    """
    A class that converts a subscribed ROS image to a OpenCV image and saves
    the captured image to a predefined directory.
    """
    def __init__(self):
        """
        A function that initializes a CvBridge class, subscriber, and other
        parameter values.
        :param self: The self reference.
        """
        self.bridge = CvBridge()
        self.sub = rospy.Subscriber('/camera/color/image_raw', Image, self.callback, queue_size=1)
        self.pub = rospy.Publisher('/image_edge_detection', Image, queue_size=1)
        self.save_path = '/home/hello-robot/catkin_ws/src/stretch_tutorials/stored_data'
        self.lower_thres = 100
        self.upper_thres = 200
        rospy.loginfo("Publishing the CV2 Image. Use RViz to visualize.")

    def callback(self, msg):
        """
        A callback function that converts the ROS image to a CV2 image and goes
        through the Canny Edge filter in OpenCV for edge detection. Then publishes
        that filtered image to be visualized in RViz.
        :param self: The self reference.
        :param msg: The ROS image message type.
        """
        try:
            image = self.bridge.imgmsg_to_cv2(msg, 'bgr8')
        except CvBridgeError as e:
            rospy.logwarn('CV Bridge error: {0}'.format(e))

        image = cv2.Canny(image, self.lower_thres, self.upper_thres)
        image_msg = self.bridge.cv2_to_imgmsg(image, 'passthrough')
        image_msg.header = msg.header
        self.pub.publish(image_msg)

if __name__ == '__main__':
	rospy.init_node('edge_detection', argv=sys.argv)
	EdgeDetection()
	rospy.spin()

The Code Explained

Since that there are similarities in the capture image node, we will only breakdown the different components of the edge detection node.

self.lower_thres = 100
self.upper_thres = 200

Define lower and upper bounds of the Hysteresis Thresholds.

image = cv2.Canny(image, self.lower_thres, self.upper_thres)

Run the Canny Edge function to detect edges from the cv2 image.

image_msg = self.bridge.cv2_to_imgmsg(image, 'passthrough')

Convert the cv2 image back to a ROS image so it can be published.

image_msg.header = msg.header
self.pub.publish(image_msg)

Publish the ROS image with the same header as the subscribed ROS message.