Implementation method of YOLOV3-based target detection algorithm on embedded equipment

Abstract

The invention discloses an implementation method of a YOLOV3-based target detection algorithm on the embedded equipment in the field of computer vision image processing, which aims to solve the problems that traditional large-scale image processing equipment is difficult to deploy in an actual application scene, the data acquisition period is long and the real-time performance of image data processing is poor. The method comprises the following steps of activating a development board to enable the development board to have a usable operating system; installing the toolkit; preparing an operating environment DARKNET framework file of YOLOV3, and storing the operating environment DARKNET framework file in a darknet folder; modifying parameters in a configuration file Makefile under the darknet folder to enable the parameters to be matched with hardware configuration of the development board; compiling and installing a darknet; downloading and storing the weight file; running and testing.The method can be realized on the embedded equipment convenient to install and use, is suitable for different scenes, and has very high target detection accuracy.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an implementation method of a target detection algorithm based on YOLOV3 on an embedded device. Background technique [0002] Traditional target detection algorithms are generally based on large-scale equipment, and using large-scale equipment for image processing is to process video images collected by cameras in offices and laboratories. Although the speed is fast and the accuracy is high, it is difficult for these equipment to Deployment in actual application scenarios is limited to office use. The process of obtaining data takes a long time, and the real-time efficiency of image data processing is very low. [0003] With the rapid development of computer vision and image processing technology, computer vision technology can be used to efficiently process and analyze images captured by cameras, and detect targets in images, and use portable and embedded devices for im...

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Problems solved by technology

[0004] The purpose of the present invention is to provide an implementation method of a target detection algorithm based on YOLOV3 on an embedded device, so as to solve the problem that large-scale image processing devices in the prior art are difficult to deploy in actual application scenarios, and the data acquisition period is long and the processing time is long. The problem of poor real-time performance of image data

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