Related Libraries
The following Vitis™ AI Libraries are related to this document.
| No | Package Name | Version |
|---|---|---|
| 1 | vitis_ai_library_r3.0.0_image.tar.gz | r3.0.0 |
| 2 | vitis_ai_library_r3.0.0_video.tar.gz | r3.0.0 |
| 3 | vitis-ai-runtime-3.0.0.tar.gz | r3.0.0 |
| 4 | vitis_ai_2022.2-r3.0.0.tar.gz | r3.0.0 |
| 5 | alveo_xclbin-3.0.0.tar.gz | r3.0.0 |
| 6 | sdk-2022.2.0.0.sh | 2022.2 |
Intended Audience
The target users of Vitis AI Libraries are as follows:
- Users who want to use pre-trained Xilinx models to quickly build applications.
- Users who use their own models that are trained with their own datasets under the Vitis AI Library support network list.
- Users who have custom models, similar to models supported by the Vitis AI Libraries, and use the Vitis AI post-processing library.
Note: If you have custom models
that are completely different from the models supported by the Vitis AI Library or have specialized post-processing
requirements, you can use the Vitis AI Library
implementations for reference.
Document Navigation
This document describes how to install, use, and develop applications with the Vitis AI Library.
- Introduction provides a high-level overview of the Vitis AI Library. This chapter provides a clear understanding of the Vitis AI Library in general, its framework, supported networks, and supported hardware platforms.
- Installation describes how to install the Vitis AI Library and run the examples. The information in this chapter will help you quickly set up the host and target environments, compile, and execute the Vitis AI Library-related examples.
- Libraries and Samples describes each model library supported by the Vitis AI Library. This chapter provides an understanding of the model libraries supported by the Vitis AI Library, the purpose of each library, how to test the library with images or videos, and how to test the performance of the library.
-
Programming Examples describes how to develop
applications with the Vitis AI Library. This
chapter provides an understanding of the following:
- Developing applications using the Vitis API
- Developing applications using your models
- Customizing pre-processing
- Using the configuration file as pre-processing and post-processing parameters
- Using the post-processing library in the Vitis AI Library
- Implementing your post-processing code
- Using the xdputil tool for DPU and xmodel debug
- Implementing and registering custom operators
- Application Demos describes how to set up a test environment and run the application demos. There are two application demos provided with the Vitis AI Library.
- Programming APIs describes how to find the programming APIs.
- Performance describes the performance of the Vitis AI Library on different boards.