Creating the GRIP pipeline

GRIP is well documented, with guides available from both FIRST and WPI:

• 2017 FRC Control System / Vision Processing / GRIP / Introduction to GRIP
• 2017 FRC Control System / Vision Processing / GRIP / Processing images from the 2017 FRC Game
• GRIP README.md
• GRIP source code on GitHub (The ultimate documentation)

To get started, experiment with a GRIP vision processing pipeline:

• Install GRIP on a desktop or laptop computer
• Download previously captured images to process with GRIP
  • 2017 sample images from FIRST
• Use the GRIP documentation mentioned above to create an initial vision processing pipeline
• The last steps should be to find or filter contours

The next step is to test your pipeline with live input from a webcam:

• Complete the Intel Galileo setup steps
• Connect an ethernet cable between your laptop and the Galileo and power it up
• Attach a webcam to a USB port on the Galileo
• Mount a light ring or flashlight next to the webcam
• Log into the Galileo
• Start the video streaming server in the background
  • mjpg-streamer ... &
• On the laptop, switch your GRIP input to the video stream
  • Type: Network camera
  • URL: http://galileo.local:1181/?action=stream
• On the Galileo, adjust the webcam exposure until the target stands out but isn't washed out to a solid white
  • v4l2-ctl -L
  • v4l2-ctl -c ...
  • v4l2-ctl -c ... 156

When the pipeline is working correctly, export automatically-generated C++ source code:

• On the GRIP "Tools" menu, choose "?"