Benny Hardjono
ABSTRACT
Simulators and software visualization tools can be useful for any research to progress. Similarly, in order to predict vehicle traffic or even to improve the use of existing highway, software visualization tools are also needed. In this research, a custom-made software visualization tool has been developed to obtain automatic vehicle Machine-Method count with better accuracy. The tool's interface design has been tailored to make various repetitive tests easier. For example, repetitive test by varying constants, parameter values and making resultant visualization (using two displays) of the detection available for further investigation. The tool can be started from either Windows or Linux operating system environment. The application's front-end uses both Electron and React. It communicates with the Python engine (which uses YOLO and OpenCV through a Python-shell). Playback feature with machine counting process label is also made available. A batch mode is made available to cater continuous counting vehicles from numerous videos or photos in subdirectories generated by CCTV along the highways. Consequently, survey results, such as standard deviations and other statistical tests are presented to show that the software tool has been successfully designed to satisfy ease-of-use in human-machine interface requirements.
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Index Terms
- Vehicle Counting Tool Interface Design For Machine Learning Methods
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