Detect license plates on NPU using YuNet TIM-VX.
By Laurent Ittiitti@usc.eduhttp://jevois.orgGPL v3
 Language: PythonSupports mappings with USB output: NoSupports mappings with NO USB output: No 
 Video Mapping:   JVUI 0 0 30.0 CropScale=RGB24@512x288:YUYV 1920 1080 30.0 JeVois PyLicensePlate
 Video Mapping:   JVUI 0 0 30.0 CropScale=RGB24@256x144:YUYV 1920 1080 30.0 JeVois PyLicensePlate

Module Documentation

This module runs on the JeVois-Pro NPU using a quantized deep neural network. It is derived from See LICENSE for license information.

Please note that the model is trained with Chinese license plates, so the detection results of other license plates with this model may be limited. See the screenshots of this module for examples, or search for "Chinese license plate" on the web for more images.

This module is mainly intended as a tutorial for how to run quantized int8 DNNs on the NPU using OpenCV and TIM-VX, here achieved through only small modifications of code from - in particular, the core class for this model, LPD_YuNet, was not modified at all, and only the demo code was edited to use the JeVois GUI Helper for fast OpenGL drawing as opposed to slow drawings into OpenCV images.

ParameterTypeDescriptionDefaultValid Values
This module exposes no parameter
Detailed docs:PyLicensePlate
Copyright:Copyright (C) 2022 by Laurent Itti, iLab and the University of Southern California
License:GPL v3
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Address:University of Southern California, HNB-07A, 3641 Watt Way, Los Angeles, CA 90089-2520, USA