= Vision Framework = == Objective == Create a reprogrammable module in which a Raspberry Pi 3, protective case, power cable, light ring, and camera are self contained and execute a base program on startup. The base code of the module continuously reads the camera feed (subscribes to camera) and publishes corresponding data via the Pi's serial output (located on the Pi's GPIO connector). This data can then be fairly simply read by the RoboRIO. We hope that this will make implementing a vision subsystem a more simple proposition, allowing more teams to do so. == Materials == * Clear Case * Raspberry Pi 3 * Micro SD card * Usb Keyboard * Usb Mouse * HDMI cable * Monitor (that accepts HDMI input, or use an HDMI to VGA adapter) * Ribbon Cable Camera * Micro USB Cable * Adafruit NeoPixel Light Ring * 3 individual male to female PWM wires * 3 individual female to female PWM wires == Raspberry Pi Setup == === Raspbian Lite === Install [https://sourceforge.net/projects/win32diskimager/ Win32 Disk Imager][[BR]] Install [https://downloads.raspberrypi.org/raspbian_lite_latest Raspian Lite] onto MicroSD card via Win32 Disk Imager Load Raspberry Pi 3 (rpi) with the newly imaged MicroSD {{{ username: pi password: raspberry }}} connect to wifi by adding the following to the /etc/network/interfaces file: {{{ auto wlan0 iface wlan0 inet dhcp wpa-ssid "your-ssid" wpa-psk "your-password" }}} reboot the pi: {{{ sudo shutdown -r now }}} update with the following commands: {{{ sudo apt-get update sudo apt-get upgrade sudo apt-get dist-upgrade sudo apt-get clean }}} set localization configuration options: {{{ sudo raspi-config }}} reboot: {{{ sudo shutdown -r now }}} ---- ---- ---- === X server === Install Xorg and Xinit: {{{ sudo apt-get install --no-install-recommends xserver-xorg sudo apt-get install --no-install-recommends xinit }}} Install the MATE GUI: {{{ sudo apt-get install mate-desktop-environment-core }}} Install LightDM login manager: {{{ sudo apt-get install lightdm }}} reboot: {{{ sudo shutdown -r now }}} login to MATE[[BR]] At the top left:[[BR]] navigate to {{{preferences -> hardware -> keyboard shortcuts}}} to set Run a Terminal to {{{Ctrl + Alt + T}}} or the like open a terminal[[BR]] navigate to {{{Edit -> Profile Preferences -> Colors}}} to deselect {{{Use colors from system theme}}}[[BR]] select {{{Built-in schemas: White on black}}} ---- ---- ---- === Development Tools === ==== Java 8 ==== Now that the terminal color scheme is not killing you, we are going to start off by installing java: {{{ sudo apt-get install oracle-java8-jdk }}} test the java installation (output should include "1.8.0_65" and should not include "openjdk"): {{{ java -version }}} Let's also set the JAVA_HOME variable to be exported on startup: {{{ echo "export JAVA_HOME=/usr/lib/jvm/jdk-8-oracle-arm32-vfp-hflt" >> ~/.bashrc source ~/.bashrc }}} Finally, let's install ANT: {{{ sudo apt-get install ant }}} ---- ---- ==== Pi4J (Java-GPIO Interface) ==== Now we can install [http://pi4j.com/install.html pi4j], a Java interface for the pi GPIO: {{{ curl -s get.pi4j.com | sudo bash }}} ---- ---- ==== rpi_ws281x (NeoPixel Control Library) ==== Then we can use the rpi_ws281x library for controlling the [https://www.adafruit.com/category/168 Adafruit NeoPixel lightring][[BR]] But first, let's install some tools and dependencies: {{{ sudo apt-get install build-essential python-dev git scons swig }}} Now we can install the rpi_ws281x library: {{{ git clone https://github.com/jgarff/rpi_ws281x.git cd rpi_ws281x scons }}} ---- ---- ==== OpenCV ==== First of all, order some pizza or something because this is going to take about 3 hours (if you are lucky). '''EDIT: we have tried with a heatsink as well. It doesn't work. You need to water cool your pi. Please skip to the WATER COOLING section.'''[[BR]] Also, you need a heatsink for your processor before building OpenCV. If you see this overheating symbol, you will die. Straight up.[[BR]] [[Image(https://i.imgur.com/kYydNgVm.jpg)]][[BR]] If you don't have a heatsink on hand, tape some pennies to the CPU like we did:[[BR]] [[Image(https://i.imgur.com/KqWLvKJm.jpg)]][[BR]][[BR]][[BR]] '''================WATER COOLING================'''[[BR]][[BR]] If this still doesn't work, it may be necessary to water cool your pi:[[BR]] [[Image(https://i.imgur.com/DPOazIJm.jpg)]][[BR]] Make sure to change the ice cube at least once every half hour. Also, only single bag the ice cube.[[BR]][[BR]][[BR]] Now we are going to install OpenCV and its dependencies.[[BR]] We only install OpenCV for C++ and Java, not for Python (we ain't scrubs): {{{ sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev cd git clone https://github.com/opencv/opencv.git cd opencv mkdir build cd build cmake .. make -j $[$(nproc)+1] sudo make install }}} This builds a single shared object file (libopencv_java320.so), a jar file (opencv-320.jar) and a ton of static libraries (*.a)[[BR]] It copies the shared object file and the jar file to the install directory: {{{/usr/local/share/OpenCV/java/...}}}[[BR]] NOTE: we could not get the java wrapper to work with ffmpeg enabled (we ran into a Segmentation fault with opencv libs 3.2.0, 3.3.0, and 3.3.1). We gave up and disabled it.[[BR]] If you do not want to git clone the master opencv repository, download a zipped version: [https://github.com/opencv/opencv/archive/3.2.0.zip opencv-3.2.0.zip][[BR]] ---- ---- ---- === Java Projects with OpenCV === ==== Enable VideoCapture ==== First, to allow OpenCV VideoCapture to access the ribbon cable camera, execute the following: {{{ echo "sudo modprobe bcm2835-v4l2" >> ~/.bashrc source ~/.bashrc }}} ===== Compiling ===== {{{ javac -d -classpath /*.java }}} where: * {{{build_path = directory to store class files}}} * {{{external_jars = string specifying individual jar dependencies (such as OpenCV and Pi4J) with delimiters as follows:}}} * {{{:/path_to_jars/jar1.jar:/path_to_jars/jar2.jar}}} * {{{souce_path = directory containing all of your java files to be compiled}}} We recommend creating a {{{libs}}} folder in which you store all of your external jars such as the {{{opencv-320.jar}}} and all the Pi4J jars rather than having your libraries scattered all over your machine. ===== Running ===== {{{ sudo java -Djava.library.path= -Dpi4j.debug -Dpi4j.linking=dynamic -classpath }}} where: * {{{external_jars = same string that you used in the Compilation step}}} * {{{Main_class = name of the class file with main method}}} * For example, where {{{Vision.class}}} is the class file, {{{Main_class = Vision}}} ---- ---- ---- === C++ Projects with OpenCV === '''NOTE: our performance doubled when we transitioned to C++ from Java'''[[BR]][[BR]] '''With C++, we can process (capture and segment) 640x480 frames at 66 fps and 1080x720 frames at 28 fps'''[[BR]][[BR]] '''With Java, we could only get about 30 fps with 640x480 frames''' Let's install an IDE so we do not have to keep writing in vi/vim/nano: {{{ sudo apt-get install codeblocks }}} We experienced a bug that constantly crashed CodeBlocks:[[BR]] To prevent crashing, navigate to: {{{Settings -> Editor -> Code completion -> Symbols browser}}} and check {{{Disable symbols browser}}}[[BR]] (the {{{Code completion}}} tab is on the west panel of the configure editor.) Navigate to: {{{File -> New -> Project -> Console Application}}} And fill in the fields that come up. If your {{{Management}}} tab is not visible, open it by selecting: {{{View -> Manager}}}[[BR]] Also, if your {{{Logs & others}}} tab is not open already, select {{{View -> Logs}}} Now right click your project in the {{{Management}}} tab and navigate to: {{{Build options... -> Linker settings}}} Under the {{{Link libraries}}} panel, select {{{Add}}} and select all OpenCV shared object (.so) files located in {{{/home/pi/opencv/build/lib/*.so}}}[[BR]] (You can [ctrl + left-click] multiple *.so] files to add them all at once) Now let's navigate to: {{{Search directories -> Linker}}}[[BR]] In the {{{Linker}}} tab, select {{{Add}}} and add the path to your opencv lib: {{{/home/pi/opencv/build/lib}}} ===== Tricks and Tips ===== Using OpenCV with the Raspberry Pi 3 ribbon cable camera is a little cumbersome because you cannot use many of the VideoCapture.set(char*,int) functions.[[BR]] Instead, we use system commands to set camera settings via the v4l2-ctl library. For FRC retroreflective tape segmentation, use the following system commands to prevent auto adjustment features such as {{{auto exposure}}}, {{{white balance}}}, and {{{exposure time}}}: * v4l2-ctl --set-ctrl=auto_exposure=1 * v4l2-ctl --set-ctrl=white_balance_auto_preset=0 * v4l2-ctl --set-ctrl=auto_exposure_bias=0 * v4l2-ctl --set-ctrl=exposure_time_absolute=100 Make your C++ program set these options by using the {{{stdlib.h}}} {{{system(char*)}}} command which simply takes a string command as input.[[BR]] Alternatively you could add these options to your {{{bashrc}}} file like we did with the modprobe, but you may want to tweak these options or experiment with them, so putting them into your C++ program makes it a little easier to manipulate.