GstCUDA - Building and Installation Guide
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This page describes the GstCUDA building and installation steps.
Getting the Code
GstCUDA is an add-on to RidgeRun's professional SDK. You can purchase GstCUDA, with full source code, from the RidgeRun Store or using the Shopping Cart:
Contact support@ridgerun.com with any questions.
Dependencies
It is important to recall that GstCUDA is only supported on Tegra X1/X2 platforms. So, the below dependencies and provided guides to meet them corresponds to Tegra platform.
The following packages are needed in order to build and use GstCUDA:
- GStreamer 1.8.0.1 version or greater:
- gstreamer-1.0
- gstreamer-plugins-base-1.0
- gstreamer-base-1.0
- gstreamer-check-1.0
- gstreamer-video-1.0
- gstreamer-controller-1.0
- CUDA 8.0 version or greater
- Mesa EGL
GStreamer
The GStreamer packages are likely already installed in your Tegra Ubuntu OS distribution. In case you want to double check and install the missing packages, run the following commands.
sudo apt install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev gstreamer1.0-plugins-base
CUDA L4T package
Below are the required steps to install CUDA L4T pacakage on Tegra. The Jetpack default installation will flash and install all the necessary CUDA packages, but in case that a CUDA L4T installation is required the below steps should be followed.
Installation guide:
- Copy the CUDA L4T package into your Tegra file system
- For this guide we are using: cuda-repo-l4t-8-0-local_8.0.34-1_arm64.deb.
- You can find the CUDA L4T package under the jetpack_download directory.
- Under the Tegra command line run the following commands:
- sudo dpkg -i cuda-repo-l4t-8-0-local_8.0.34-1_arm64.deb
- sudo apt-get update
- sudo apt-get install cuda-toolkit-8-0
** Note: If you are using Ubuntu 16.04 or later it will warn about the signature of the package, you can ignore this.
$ sudo apt-get update Get:1 file:/var/cuda-repo-8-0-local InRelease Ign:1 file:/var/cuda-repo-8-0-local InRelease Get:2 file:/var/cuda-repo-8-0-local Release [574 B] Get:2 file:/var/cuda-repo-8-0-local Release [574 B] Hit:4 http://ports.ubuntu.com/ubuntu-ports xenial InRelease Hit:5 http://ports.ubuntu.com/ubuntu-ports xenial-updates InRelease Hit:6 http://ports.ubuntu.com/ubuntu-ports xenial-security InRelease Reading package lists... Done W: file:///var/cuda-repo-8-0-local/Release.gpg: Signature by key 889BEE522DA690103C4B085ED88C3D385C37D3BE uses weak digest algorithm (SHA1)
Mesa EGL
Run the following command to install the Mesa EGL package:
sudo apt install libegl1-mesa-dev
GTK-Doc
Run the following command to install the GTK-Doc package:
sudo apt install gtk-doc-tools
Building the project
It is important to recall that GstCUDA is only supported on Tegra X1/X2 platforms. So, the GstCUDA package must be built natively on the Tegra.
In order to build the project run the following commands. Note that the libdir variable corresponds to the Tegra X1/X2 system.
./autogen.sh --prefix=/usr/ --libdir=/usr/lib/aarch64-linux-gnu/ make
The autogen.sh script will automatically run the configure script. In case a more complex configuration is needed, the configure step may be executed manually:
./autogen.sh --noconfigure ./configure --prefix=/usr/ --libdir=/usr/lib/aarch64-linux-gnu/ <additional advanced options> make
Finally, the status of the current version may be checked by running the unit tests:
make check
Installing the plugin
The plugin is installed to the GStreamer's default plug-in location in the file system by running:
sudo make install
To verify that the plug-in was correctly installed, you should run:
gst-inspect-1.0 cuda Plugin Details: Name cuda Description Allows frames to be processed by the GPU using a custom CUDA library algorithm Filename /usr/lib/aarch64-linux-gnu/gstreamer-1.0/libgstcuda.so Version 0.3.0.1 License Proprietary Source module gst-cuda Source release date 2017-11-20 23:12 (UTC) Binary package GStreamer CUDA Plug-in Origin URL Unknown package origin cudafilter: cudafilter 1 features: +-- 1 elements
Important Note
After installing GstCUDA and all its dependencies, the Tegra must be rebooted before running a GStreamer pipeline that uses GstCUDA.
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