OpenCV and ROS

The purpose of this lab is to gain experience incorporating vision code into ROS nodes and making use of depth data from the Kinect.

Resources

• cv_bridge Python Tutorial
• cv_bridge Python API

Exercises

• Clone the three_d_vision package from github. This package has the following contents:

  three_d_vision/
      package.xml
      CMakeLists.txt
      rviz/             
          vision.rviz
          depth.rviz
      launch/           
          view_vision.launch
          view_depth.launch
      scripts/          
          kinect_vision_demo.py
          kinect_depth_demo.py
  
  

• Read over the code in scripts/kinect_vision_demo.py . Note that the implementation of find_reddest_pixel_fast is missing. Add your version, or add a statement to import it from your completed detected_red.py file.
• Launch view_vision.launch and look at the published image topic. You can look at the topic in rviz, or by starting an image_view node:

    $ rosrun image_view image_view image:=/red_marked_image
  

• Read over the code in scripts/kinect_depth_demo.py. Again, you need to incorporate your version of find_reddest_pixel_fast.
• Launch view_depth.launch and look at the published topics in rviz. You should be able to see the location in space of the red pixel relative to the robot.