Kria™ KV260 Vision AI Starter Kit
NLP SmartVision Tutorial

Customizing the AI Models used in the application

Customizing the AI Models used in the application


This document provide an overview of how to customize the NLP SmartVision application to use other AI models other than the default ones.


Other than the 3 models provided via keywords “up” & “down” as documented here,

  • facedetect (densebox_640_360)

  • object Detect (yolov2_voc_pruned_0_77)

  • plate Detect (plate_detect)

customization can be made to use other Vitis AI models or retrained model by the users of the same class.

Model Preparation

Note The design currently only supports Vitis AI 2.5.0

Note As described in the Hardware Accelerator section, the DPU integrated in the platform uses the B3136 configuration.

The arch.json used to compile the xmodel for B3136 DPU can be obtained by build the accelerator, but if you won’t build all from the start, you can save following code as arch.json


For detailed instructions on obtaining an alternative model from the Xilinx model zoo or training, pruning, quantizing, and compiling a new model, please refer to the Vitis AI documentation.



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