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https://github.com/robotcasserole1736/casserolebbbvisiontest

Quick work for testing vision processing on Beaglebone Black
https://github.com/robotcasserole1736/casserolebbbvisiontest

Last synced: 3 months ago
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Quick work for testing vision processing on Beaglebone Black

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README 

        
# CasseroleBBBVisionTest

Quick work for testing vision processing on Beaglebone Black



Many many many thanks to FRC2481 for their simple instructions on getting this started.



Their awesome work can be found [here](https://github.com/Frc2481/paul-bunyan).



##Basic Setup



### Logging in via SSH



We will use the default angstrom linux distro.



For first setup, the BBB must be connected to a network with internet access.



On a brand new BBB, ssh into it using your favorite ssh utility. I use [putty](http://www.chiark.greenend.org.uk/~sgtatham/putty/download.html) because of reasons. You will likely have to look up the IP address by looking at the router setup page, and determining what DHCP address was assigned to the BBB.



When prompted, login with:



    user: root

    password: 

    

Yes it's bad to do stuff as root. But also easier. Just don't do silly things. Never run "rm -rf /", no matter how cool you think it will make you look in front of your friends.



### Installing Prerequisites on the BBB



Update the time so SSL certificate validation occurs ok:



    ntpdate -b -s -u pool.ntp.org



Now install all the python utilities needed:



    opkg update

    opkg install python-pip

    opkg install python-setuptools

    opkg install python-opencv

    opkg install python-misc

    opkg install python-modules

    pip install http://pypi.python.org/packages/source/p/pynetworktables/pynetworktables-2015.3.1.tar.gz

    pip install psutil

   



Get this repo onto the BBB:



    cd ~

    git clone https://github.com/RobotCasserole1736/CasseroleBBBVisionTest

    

Checkout your favorite release. Probably latest on master should be correct.



### Static IP Setup



Now that all the dependencies are installed, the unit should be moved and placed on the robot network (probably no internet access).

Once this is done, log back in.



Set a static IP address of 10.17.36.20, with the default gateway pointing to the router (usually 10.17.36.1)



    ls -la /var/lib/connman/

    cd /var/lib/connman/ethernet_[xx]

    more settings

    cd /usr/lib/connman/test

    ./set-ipv4-method ethernet_[xx]_cable manual 10.17.36.20 255.255.255.0 10.17.36.1

    reboot

    

Once the BBB boots again, you should be able to connect via the set up static IP address.



To start the vision processing manually, run the "runVision.sh" script in the root of the repo.

More instructions to come on how to set this up to go automatically at boot.



### Creating a Service for the Vision Processing Script



A "service" is a linux-OS mechanism for running background tasks, automatically. By creating and installing a service for our vision processing algorithm, we can have the OS start it at boot, and restart it if it crashes.



Copy the service definition file to its proper home on the in the OS system files.

    

    cp CasseroleVisionCoprocessor.service /lib/systemd/system/

    

Instruct the OS to run this at Boot:

   

    systemctl enable CasseroleVisionCoprocessor

    

Then reboot the system to test:

   

    reboot

    

Once the next boot happens, the vision processing script should start up right away. Anything which was printed to console may be viewed in the system logs (grepped for relevant lines, since _many many many_ things in the OS get dumped here):



    journalctl | grep python



If you've changed the python script and want the system to reload your updates, you can restart the service



    systemctl restart CasseroleVisionCoprocessor

    

If you want to just manually run the script and not have it going in the background for some reason, you can temporarily stop it or start it back up:

 

    systemctl stop CasseroleVisionCoprocessor

    systemctl start CasseroleVisionCoprocessor

    

Finally, if you need it to not run at boot for debugging reasons, you can also uninstall the service:



    systemctl disable CasseroleVisionCoprocessor

    

Remember to re-run enable before you go to competition!



# Deploying Changes from Development PC



To Be completed....



## Development Process



## GRIP Code generation



## Deploy Process



# Script Design



## Overall

As is, the script is set up to maintain a robust connection with the IP camera,

process frames as they come in, and post the processing results to NetworkTables

(or just print them out, as it does now)



The psutil library is used to monitor CPU and memory loading. 



The exact data processed out of the image will change year to year. Some

possibiilities include:



* Total time from reciving the image to posting the processing results

* For each target:

  * X/Y position within the image

  * Information for acessing the validity of the target

    * Bounding Box Size/Area

    * Infill percentage

    * Skew



## Network Connectivity

The read and connect routines have fairly short timeouts, but will attempt to 

reconnect indefinitely if the connection is ever lost. There's been some basic

desktop testing to prove out that there are no race conditions between starting

the camera and starting the BBB. 



## Status LED

To indicate status, the usual status LED is overwritten. During BBB boot sequence,

the status LED will follow the default on-for-boot, then heartbeat until the

vision processing script starts.



Once the vision processing script has started, the LED will turn off fully. 

As long as the script is waiting for a connection, the LED will remain dark. Once

valid image frames are getting processed, the LED will turn back on to be mostly

solid (occasional pulse off). If the LED ever goes off, it means the script is

not actively processing frames. Usually this is due to lack of a network connetion

to the IP camera



# Notes on Cameras & Settings



To get good images for processing, it's usually best to try to get a dark image. 

The only lit-up pixels should be the target in question.



This usually means



* Fixed (non-automatic) white balance

* Exposure turned down to minimum

* Brightness turned down to minimum

* All auto-adjustement disabled

    

Note that I've been testing with an axis M1013, which is a horrible camera choice

since it is impossible to disable all brightness compensation. M1011 is better 

for vision processing, I think... But, basicallly, we wouldn't ever want to use the M1013.



[This](http://wpilib.screenstepslive.com/s/4485/m/24194/l/288984-camera-settings) is a good resource on this sort of thing.



#Remote Desktop Connections



x11vnc is installed and runable on the BBB. It's not recommended to have it always on since it can soak up processor cycles, which are very valuable. However, for some vision debugging, it's nice to have.



To remote desktop, first ssh into the BBB as described above. Then run the following magic incantation:



    x11vnc -bg -o %HOME/.x11vnc.log.%VNCDISPLAY -auth /var/run/gdm/auth-for-gdm*/database -display :0  -forever

    

Then connect to it using any VNC utility. For windows, I like [this one](https://www.realvnc.com/download/viewer/).



To adjust the screen resolution, sadly this all has to be done on the server (BBB) side, and only after the 

connection has been started. To do this, open the Terminal application under Applications->System, and run the following command:



    xrandr --fb 1600x900

    

Of course, resolution may be adjusted to suit.



All these things can be put into .sh scripts if desired to speed setup