StreetscapeCV Computer Vision Project
Updated a year ago
Here are a few use cases for this project:
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Urban Planning: "StreetscapeCV" could be utilised by urban planners and architects to assess the placement or frequency of bus-stop features such as seating, shelters, and trash cans within a city or suburb. Moreover, identifying signage can help analyze the effectiveness of public communication.
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Accessibility Study: This tool can be used to analyze the inclusivity and accessibility of public transportation facilities. This includes whether seating is sufficiently provided, if signage is perceptible and if shelters are present for protection against the elements.
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Maintenance and Refurbishment: City councils or municipal corporations could deploy this model to identify areas needing maintenance or upgrades - detecting faulty or old signage, damaged seating areas, or overfilled trash cans.
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Research and Academic Projects: Scholars performing studies on urban design or public transportation could use "StreetscapeCV" as a tool for collecting quantifiable data to use in their research.
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Intelligent Transportation Systems: Developers could integrate this computer vision model within an AI-based transportation system to provide real-time information about bus stop conditions and features to both transport authorities and commuters.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
streetscapecv_dataset,
title = { StreetscapeCV Dataset },
type = { Open Source Dataset },
author = { ProjectSidewalk },
howpublished = { \url{ https://universe.roboflow.com/projectsidewalk/streetscapecv } },
url = { https://universe.roboflow.com/projectsidewalk/streetscapecv },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jul },
note = { visited on 2024-11-17 },
}