How to use Gige camera with Raspberry Pi 3B+

This is a step by step guide to install the tiscamera software on a Raspberry Pi 3B+ and use it with opencv.

This guide is not complete yet.

install dependencies

sudo apt install autoconf aravis-tools glade cmake g++ git gstreamer1.0-plugins-bad gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-ugly gstreamer1.0-tools gstreamer1.0-x gtk-doc-tools intltool libqt5gstreamer-dev libaudit-dev libaudit1 libgirepository1.0-dev libglib2.0-dev libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev libnotify-dev libnotify4 libpcap-dev libpcap0.8 libtinyxml-dev libudev-dev libudev1 libusb-1.0-0-dev libxml2 libxml2-dev libzip-dev pkg-config python-setuptools python3-sphinx qtbase5-dev qtdeclarative5-dev uvcdynctrl  -y

pip3 install ninja

sudo apt install gstreamer1.0-tools -y

export PATH="$HOME/.local/bin:$PATH"

install tiscam

git clone --recursive https://github.com/TheImagingSource/tiscamera.git

cd tiscamera

mkdir build

cd build

cmake -DBUILD_ARAVIS=ON -DBUILD_GST_1_0=ON -DBUILD_TOOLS=ON -DBUILD_V4L2=ON -DCMAKE_INSTALL_PREFIX=/usr ..

make

sudo make install

start tcam service

sudo systemctl daemon-reload

sudo systemctl enable tcam-gige-daemon.service

sudo systemctl start tcam-gige-daemon.service

start gui

tcam-capture

install opencv with aravis

cd ~

git clone  https://github.com/opencv/opencv

cd opencv

mkdir build && cd build

cmake -D CMAKE_BUILD_TYPE=RELEASE -D INSTALL_C_EXAMPLES=OFF -D PYTHON_EXECUTABLE=/usr/bin/python/aravis_opencv/gige_py/bin/python -D WITH_GSTREAMER=ON  -D WITH_ARAVIS=ON  ..

make -j4

last 2 percent need lots of memory, you may need to increase swap temporarily, use make -j1 to save some memory for the last bit.

------ increase swap --------

sudo dphys-swapfile swapoff

sudo nano /etc/dphys-swapfile

CONF_SWAPSIZE=1024

sudo dphys-swapfile setup

sudo dphys-swapfile swapon

-----------------------------

sudo make install

export GI_TYPELIB_PATH="/usr/lib/x86_64-linux-gnu/girepository-1.0"

export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH

Install Aravis

sudo apt install meson ninja-build

sudo pip3 install meson

sudo ln -s /usr/local/bin/meson /usr/bin/meson

cd ~

wget https://github.com/AravisProject/aravis/releases/download/0.8.26/aravis-0.8.26.tar.xz

tar -xf aravis-0.8.26.tar.xz

cd aravis-0.8.26

meson --prefix /usr --buildtype=plain build

cd build

ninja

sudo ninja install

sudo ldconfig

Install opencv

pip install opencv-python==4.5.3.56

pip install --upgrade numpy

sudo apt install libatlas-base-dev

Run the python script

Get a live preview

python main.py

Get a single frame

python
import single_frame
width = 1920
height = 1080
exposure_us = 100000
# optional parameters
image = single_frame.get(width, height, exposure_us)