This package combines the Roboception convenience layer for images with the GenICam reference implementation and a GigE Vision transport layer. It is a self contained package that permits configuration and image streaming of GenICam / GigE Vision 2.0 compatible cameras like the Roboception rc_visard. The API is based on C++ 11 and can be compiled under Linux and Windows.
This package also provides some tools that can be called from the command line for discovering cameras, changing their configuration and streaming images.
Prebuilt binaries can be downloaded on the releases page.
- Minimum Requirements
- Compiling and Installing
- Description of Tools
- Definition of Device ID
- Finding the Transport Layer
- Network Optimization under Linux
- Linux x64 / i86: gcc >= 4.8
- ARMhf: gcc >= 4.9.4
- Linux AArch64: gcc >= 5.4
- Windows 10: Visual Studio >= VC140
Building follows the standard cmake build flow. Please make sure to set the install path before compiling. Otherwise it can happen that the transport layer is not found when calling the tools.
cd <main-directory>
mkdir build
cd build
cmake -DCMAKE_INSTALL_PREFIX=<install-directory> ..
make
make install
To install bash completion, configure cmake with -DINSTALL_COMPLETION=ON
A Debian package can be built with e.g.
cd <main-directory>
mkdir build
cd build
cmake -DCMAKE_INSTALL_PREFIX=/usr ..
make
make package
The main directory contains the script build_win.bar. Execute this script in the Visual Studio command line prompt for building the package. Alternatively, you can use cmake manually to generate a build project for compilation with your favorite compiler.
NOTE: For using the libraries in own projects, define the symbol
GENICAM_NO_AUTO_IMPLIB in your project file to avoid linker problems with the
GenICam libraries.
The tools do not offer a graphical user interface. They are meant to be called from a shell (e.g. Power Shell under Windows) or script and controlled by command line parameters. Calling the tools without any parameters prints a help text on the standard output.
NOTE: If any tool returns the error No transport layers found in path ...,
then read the section 'Transport Layer' below.
Lists all available systems (i.e. transport layers), interfaces and devices with some information. If a device ID is given on the command line, then the complete GenICam nodemap with all parameters and their current values are listed.
gc_info -h | -l | ([-o <xml-output-file>] [<interface-id>:]<device-id>[?<node>] [<key>=<value>] ...)
Provides information about GenICam transport layers, interfaces and devices.
Options:
-h Prints help information and exits
-l List all all available devices on all interfaces
-o Filename to store XML description from specified device
Parameters:
<interface-id> Optional GenICam ID of interface for connecting to the device
<device-id> GenICam device ID, serial number or user defined name of device
<node> Optional name of category or parameter to be reported
<key>=<value> Optional GenICam parameters to be changed in the given order before reporting
Can be used to list network specific information of GenICam compatible GigE Vision 2 cameras. The network settings as well as all other parameters provided via GenICam can be changed.
gc_config -h | -l | ([<interface-id>:]<device-id> <options> ...)
Configuration of a GigE Vision device via GenICam.
-h Prints help information and exits
-l Lists all available GigE Vision devices
Parameters:
<interface-id> Optional GenICam ID of interface for connecting to the device
<device-id> GenICam device ID, serial number or user defined name of device
Options:
-n <id> Set user defined id
-d 1|0 Switch DHCP on or off
-p 1|0 Switch persistent IP on or off
-t 1|0 Switch precision time protocol (ptp) on or off
-i <ip> Set persistent IP address
-s <ip> Set subnet mask for persistent IP address
-g <ip> Set default gateway for persistent IP address
--iponly Show current IP of device instead of full summary
<key>=<value> Optional GenICam parameters to be changed in the given order
This tool shows how to configure and stream images from a camera. GenICam features can be configured directly from the command line. Images will be stored in PGM or PPM format, depending on the image format.
Streams of the Roboception rc_visard can be enabled or disabled directly on the command line by setting the appropriate GenICam parameters. The following command enables intensity images, disables disparity images and stores 10 images:
gc_stream <ID> ComponentSelector=Intensity ComponentEnable=1 ComponentSelector=Disparity ComponentEnable=0 n=10
NOTE: Many image viewers can display PGM and PPM format. The sv tool of cvkit can also be used.
gc_stream -h | [-f <fmt>] [-t] [<interface-id>:]<device-id> [n=<n>] [<key>=<value>] ...
Stores images from the specified device after applying the given optional GenICam parameters.
Options:
-h Prints help information and exits
-t Testmode, which does not store images and provides extended statistics
-f pnm|png Format for storing images. Default is pnm
Parameters:
<interface-id> Optional GenICam ID of interface for connecting to the device
<device-id> GenICam device ID, serial number or user defined name of device
n=<n> Optional number of images to be received (default is 1)
<key>=<value> Optional GenICam parameters to be changed in the given order
This tool streams the left image, disparity, confidence and error from a Roboception rc_visard sensor. It takes the first set of time synchronous images, computes a colored point cloud and stores it in PLY ASCII format. This tool demonstrates how to synchronize different images according to their timestamps.
NOTE: PLY is a standard format for scanned 3D data that can be read by many programs. The plyv tool of cvkit can also be used for visualization.
gc_pointcloud -h | [-o <output-filename>] [<interface-id>:]<device-id>
Gets the first synchronized image set of the Roboception rc_visard, consisting
of left, disparity, confidence and error image, creates a point cloud and
stores it in ply ascii format.
Options:
-h Prints help information and exits
-o <file> Set name of output file (default is 'rc_visard_<timestamp>.ply')
Parameters:
<interface-id> Optional GenICam ID of interface for connecting to the device
<device-id> GenICam device ID, serial number or user defined name of device
This tool can be used to upload and download a file into the persistent user space of an industrial camera.
tools/gc_file -h | [<interface-id>:]<device-id> -f | (<device-file> [-w|-r <file>])
Downloading or uploading a file via GenICam.
-h Prints help information and exits
-f Lists names of files on the device
-w <file> Writes the given local file into the selected file on the device
-r <file> Reads the selected file on the device and stores it as local file
The selected file is printed on std out if none of -f, -w and -r are given.
There are multiple ways of specifying an ID to identify a device.
-
The serial number of the device serves as ID. Example:
02911931 -
The given ID can also be a user defined name. The user defined name is set to
rc_visardby default and can be changed with:gc_config <ID> -n <user-defined-name>This way of identifying a device can fail if there is more than one device with the same name. No device is returned in this case.
If the user defined name contains one or more colons, it must be preceded by a colon (e.g.
:my:name) or an interface ID (see below). -
The device ID of the GenTL producer (see
Transport Layersection below) may also be used. This ID is unique, but not persistent as it depends on the implementation of the GenTL producer. Thus, it can change after software updates. It often encodes the MAC address of the sensor in some way.Example:
00_14_2d_2c_6e_bb
All three options can be seen in the output of gc_config -l.
If the given ID contains a colon (i.e. :), the part before the (first)
colon is interpreted as interface ID and the part after the first colon is
treated as device ID. This is the format that gc_config -l shows. A device
with the given ID is only sought on the specified interface. This can be
useful if there are several ways to reach a device from a host computer,
e.g. via wireless and wired network connection, but a certain connection
type (e.g. wired) is preferred due to higher bandwidth and lower latency.
Examples: eth0:00_14_2d_2c_6e_bb, eth1:02911931 or wlan0:rc_visard
A colon at the beginning of the ID effectively defines an empty interface ID which triggers looking on all interfaces.
If the given ID does not contain a colon, the ID is interpreted as the device ID itself and is sought throughout all interfaces as well.
The communication to the device is done through a so called transport layer
(i.e. GenTL producer version 1.5 or higher). This package provides and installs
a default transport layer that implements the GigE Vision protocol for
connecting to the Roboception rc_visard. According to the GenICam
specification, the transport layer has the suffix '.cti'. The environment
variable GENICAM_GENTL32_PATH (for 32 bit applications) or GENICAM_GENTL64_PATH
(for 64 bit applications) must contain a list of paths that contain transport
layers. All transport layers are provided as systems to the application.
For convenience, if the environment variable is not defined or empty, it is internally defined with the install path of the provided transport layer (as known at compile time!). If the package is not installed, the install path is changed after compilation or the package is moved to another location after installation, then the transport layer may not be found. In this case, the tools shows an error like e.g.:
'No transport layers found in path /usr/lib/rc_genicam_api'
In this case, the corresponding environment variable (see above) must be set to the directory in which the transport layer (i.e. file with suffix '.cti') resides.
Under Windows, as second fall back additionally to the install path, the directory of the executable is also added to the environment variable. Thus, the install directory can be moved, as long as the cti file stays in the same directory as the executable.
When images are received at a lower rate than set/exepected the most likely problem is that this (user space) library cannot read the many UDP packets fast enough resulting in incomplete image buffers.
The net_perf_check.sh script performs some simple checks and should be run
while or after streaming images via GigE Vision.
./net_perf_check.sh --help
First of all increasing the UDP packet size (using jubo frames) is strongly recommended! Increase the MTU of your network interface to 9000, e.g.
sudo ifconfig eth0 mtu 9000
Also make sure that all network devices/switches between your host and the sensor support this.
There are several Linux sysctl options that can be modified to increase performance for the GigE Vision usecase.
These values can be changed during runtime with sysctl or written to
/etc/sysctl.conf for persistence across reboots.
If the number of UDP RcvbufErrors increases while streaming, increasing the socket receive buffer size usually fixes the problem.
Check the RcvbufErrors with net_perf_check.sh or
netstat -us | grep RcvbufErrors
Increase max receive buffer size:
sudo sysctl -w net.core.rmem_max=33554432
Changing these values is usually not necessary, but can help if the kernel is already dropping packets.
Check with net_perf_check.sh and increase the values if needed:
sudo sysctl -w net.core.netdev_max_backlog=2000
sudo sysctl -w net.core.netdev_budget=600