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Abstract

This project harnesses YOLOv8 technology, specifically tailored for precise identification and counting of bolts at fixed distances along a designated track, as well as for estimating odometer readings and vehicle speed calculations. It incorporates a test video stored within the /video directory of a Docker container, with the outcomes of these tests saved in the /result directory, subsequently relayed to the host machine's home directory via Docker mechanisms. Furthermore, the system offers real-time visualization of these processes through a WebUI accessible at http://127.0.0.1:5000 within the local network.

Install

PyPI(recommend)

pip install jetson-examples

Linux (github trick)

curl -fsSL https://raw.githubusercontent.com/Seeed-Projects/jetson-examples/main/install.sh | sh

Github (for Developer)

git clone https://github.com/Seeed-Projects/jetson-examples
cd jetson-examples
pip install .

Quickstart

reComputer run yolov8-rail-inspection

Note

The display feature of the WebUI is experimental. Opening the WebUI visualization requires waiting for loading time of less than one minute. Optimization for this issue will be addressed in future updates.

FAQs

  1. The project has been tested on the Jetson Orin platform, and its execution entails the use of Docker; therefore, it is essential to ensure that all necessary Docker components are fully installed and functional.
  2. During program execution, you may encounter an ERROR: Could not open requirements file. This error message does not impact the normal operation of the program and can be safely ignored.
  3. The ultimate visualization of the results is presented through a web interface. Upon executing the command to run the reComputer yolov8-rail-inspection, the terminal will output the URL for the visualization webpage. Upon clicking the link, you may need to wait a few seconds for the program to initialize and commence operation.