This page provides instructions for building the Vitis-AI Library (v1.3.2) sample applications from source on a ZCU10x evaluation board or KV260 kit running Certified Ubuntu 20.04 LTS for Xilinx Devices.
Building the Vitis AI library sample applications is straightforward. The steps below provide an easy-to-follow set of steps to build them yourself.
Before building the sample applications, install the required dependency packages:
All of the source code is available on the Xilinx GitHub. After you clone the Vitis AI repository, switch to the v1.3.2 tag. Make sure you’re in your home directory before cloning.
Depending on which sample application you want to build, switch to the sample application directory and build it using the provided script build.sh.
In releases of the repository prior to version 1.4, the paths for opencv4 in the
For example, in order to build the
facedetect sample application:
The sample applications require a compatible machine learning model in order to run. Refer to the
readme file in the application directory to determine which models are compatible with each sample application. The models are available for download at http://xilinx.com as part of the Xilinx Model Zoo. To find download link for the model you need, use the table below:
Compatible with the OOB bitstreams provided with the Certified Ubuntu Images
Compatible with Accelerated Application firmware from the 2020.2.2 KV260 Release
The models for the KV260 are not documented in the Xilinx Model Zoo since they were not available at the time that the original set of v1.3.1 models was released.
For example, to download the densebox_640_360 model for the zcu102 and extract in the home directory:
The sample applications can take input from either a jpeg image or a USB Camera. HDMI input is not supported by the sample apps.
For help determining which /dev/videoX interface to use for the USB tests, you can use the following command:
There are three ways to specify the model
Place the model directory in
/usr/share/vitis_ai_libray/models/ and use the model name (ex: densebox_640_360)
Place the model directory in the current directory and use the model name
Directly reference the
.xmodel file (shown above)
For more information about the specific test applications supported for each sample, please refer to the readme in the
For more information about running the sample apps, please refer to https://github.com/Xilinx/Vitis-AI/blob/master/tools/Vitis-AI-Library/README.md#running-vitis-ai-library-examples
Vitis AI provides a test image archive that can be download to the target and used to run the tests above. To download the sample image package, and extract them to the samples directory in your home directory, use the following commands:
To use these images and file lists, change into the subdirectory of the test you want to run, and execute the test app from there. For example, to use the facedetect sample images, you should run your test from the ~/samples/facedetect directory.