The Vitis AI Library is a set of high-level libraries and APIs built for efficient AI inference with the Deep-Learning Processor Unit (DPU). It is built based on the Vitis AI Runtime with unified APIs, and it fully supports XRT 2021.1.
The Vitis AI Library provides an easy-to-use and unified interface by encapsulating many efficient and high-quality neural networks. This simplifies the use of deep-learning neural networks, even for users without knowledge of deep-learning or FPGAs. The Vitis AI Library allows you to focus more on the development of your applications, rather than the underlying hardware.
For the intended audience for the Vitis AI Library, refer to the About this Document section.
The Vitis AI library contains four parts: the base libraries, the model libraries, the library test samples, and the application demos.
The base libraries provide the operation interface with the DPU and the post-processing module of each model. dpu_task is the interface library for DPU operations. xnnpp is the post-processing library of each model, with built-in modules such as optimization and acceleration.
The model libraries implement most of the neural network deployment which are open source. They include common types of networks, such as classification, detection, segmentation, and others. These libraries provide an easy-to-use and fast development method with a unified interface, which are applicable to the Xilinx models or custom models. The library test samples are used to quickly test and evaluate the model libraries. The application demos show you how to use the Vitis AI Library to develop applications. The Vitis AI Library block diagram is shown in the following figure.