SentToDevNull / TitanVision

The Northview Techno Titans FRC 2017 Vision System

TitanVision

What Is This Project?

This is our vision processing code for FIRST Robotics's 2017 FRC competition.

What This Repository Consists Of

• main.py - the main program; it uses multiple threads to handle serving camera streams and sending pertinent values out to SmartDashboard via NetworkTables
• processing.py - processes the camera objects passed through, except for camera_three, the driver station camera
• feed_server.py - serves the feeds from camera objects passed to its constructor
• hsltest.py - this is an interactive HSL filtering program to aid in finding which values should be filtered
• hsl_auto.py - calibrates the HSL values used for filtering
• load_hsl_values.py - loads calibrated HSL values into processing code
• target_processing.py - performs target-specific processing; it filters out everything but reflective tape on both treams, then calculates the centers of both strips, decreasing confidence values if the filtered image is not oriented correctly
• whichinterface.sh - shell script that ensures you are only connected to only one network (presumably the robot's) and returns the network interface your network traffic is routed through
• rcinit - this is the script installed at /etc/rc.local to start the main program at bootup
• Makefile - this is the Makefile for pushing the code to the RasPi; it also handles dependency resolution on Debian-based clients as well as many other things

Dealing With the Code

To push the code to the RasPi, connect it to the network and run make. If you are using different RasPis than the ones we set up, you'll have to update the MAC addresses in the Makefile.

The Makefile was designed so that you manage both RasPis at the same time and keep their code in sync. There are make targets for the individual RasPis if you need to access only one or the other.

If you are running a Debian-based system and you wish to install all the dependencies needed to run this program, run make deps.

Testing HSL Values

To test HSL values for filtering, run python hsltest.py locally to start the graphical filtering program.

Automatically Calibrating HSL Values

To automatically calibrate HSL values, run python hsl_auto.py --test locally to use the test image in the repository, python hsl_auto.py --test --test-img-src=x.jpg to use your own image, where your own image is "x.jpg", and python hsl_auto.py --debug-level 1 to use view all debug information and images. Running python hsl_auto.py --help will give you a complete list of possible commands.