burrow-pi-img

History

Peter Johnson c85fd9f33c Revamp image to build dependencies as part of stages (#83 ) Fixes #17. Stage 2 is fairly minimal, stage 3 builds/installs OpenCV and WPILib et al, and stage 4 builds/installs the FRCVision webdash and adds the vision examples. Other changes: - OpenCV compiled with ffmpeg, OpenBLAS, and libgtk (fixes #79, fixes #80) - OpenBLAS added to image (fixes #65) - C++ Makefile is more easily extensible (fixes #71) - Sources for everything are bundled into image into /usr/src - README updated (fixes #16) - pkg-config files for wpilibc et al are now installed and C++ Makefile uses them (if compiled local to Pi) - Both dynamic and static libs are included in image The only downside of all these changes (particularly the ffmpeg, OpenBLAS, and libgtk inclusion) is the image size is now over 3GB (800MB compressed). The previous image didn't quite fit on a 2GB card however.		2019-02-02 23:37:18 -08:00
..
main.cpp	Fix ordering between CameraServer.getInstance and UsbCamera creation (#69 )	2019-01-13 21:23:44 -08:00
Makefile	Revamp image to build dependencies as part of stages (#83 )	2019-02-02 23:37:18 -08:00
README.txt	Update example README.txt files (#57 )	2019-01-11 13:21:20 -08:00
runCamera	Add java, cpp, and python examples	2018-12-08 00:45:27 -08:00

README.txt

=======================
Building locally on rPi
=======================

1) Run "make"
2) Run "make install" (replaces /home/pi/runCamera)
3) Run "./runInteractive" in /home/pi or "sudo svc -t /service/camera" to
   restart service.


===================
Building on desktop
===================

--------------
One time setup
--------------

Install the Raspbian compiler [1] as well as GNU make [2].

[1]: https://github.com/wpilibsuite/raspbian-toolchain/releases
[2]: (windows) http://gnuwin32.sourceforge.net/packages/make.htm

--------
Building
--------

Run "make"

---------
Deploying
---------

On the rPi web dashboard:

1) Make the rPi writable by selecting the "Writable" tab
2) In the rPi web dashboard Application tab, select the
   "Uploaded C++ executable" option for Application
3) Click "Browse..." and select the "multiCameraServerExample" executable in
   your desktop project directory
4) Click Save

The application will be automatically started.  Console output can be seen by
enabling console output in the Vision Status tab.