bus_photos Object Detection Dataset and Pre-Trained Model by Zatoichi

Images

4525 images

Explore Dataset

Here are a few use cases for this project:

Public Transportation Tracker: Integrate "bus_photos" with traffic cameras or user-submitted images in real-time to track the movement and location of buses in a city, helping transportation departments and passengers to monitor bus schedules and improve the overall public transit system.
Accessibility and Navigation Assistance: Use the "bus_photos" model in conjunction with GPS-based apps for people with visual impairments, enabling them to identify bus numbers and receive real-time information about approaching buses at a bus stop, thus enhancing their independence and mobility.
Traffic Management and Analytics: Employ "bus_photos" in combination with other traffic monitoring models to analyze the flow of city buses, identify congestion patterns, suggest alternate routes or schedule adjustments, and ultimately optimize urban transportation networks.
Bus Fleet Maintenance: Facilitate the tracking and management of individual buses within a transportation company's fleet, using the "bus_photos" model to identify specific bus numbers in images and videos, allowing for more efficient organization and maintenance schedules.
Advertising Performance Analysis: Utilize "bus_photos" model in combination with ad recognition software to track the exposure and visibility of advertisements placed on buses. This can help advertisers and marketers assess the effectiveness of their ad campaigns and make data-driven decisions on advertising locations and strategies.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            bus_photos_dataset,
                            title = { bus_photos Dataset },
                            type = { Open Source Dataset },
                            author = { Zatoichi },
                            howpublished = { \url{ https://universe.roboflow.com/zatoichi-elw9y/bus_photos } },
                            url = { https://universe.roboflow.com/zatoichi-elw9y/bus_photos },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-04-26 },
                            }