yolov7_rev02 Instance Segmentation Dataset and Pre-Trained Model by labelingvehicles

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Explore Dataset

Here are a few use cases for this project:

Smart Traffic Management System: Implement yolov7_rev02 in a traffic management system to efficiently regulate traffic lights, ensuring pedestrian safety by detecting zebra crossings, motorbikes, cars, trucks, and traffic signs, leading to smoother traffic flow in urban areas.
Autonomous Vehicle Navigation: Integrate yolov7_rev02 into self-driving cars to accurately identify zebra crossings, motorbikes, cars, trucks, and traffic signs, leading to safer navigation and improved decision-making by the autonomous system.
Urban Planning & Infrastructure Analysis: Use yolov7_rev02 to analyze large-scale urban environments, assessing the placement of zebra crossings, the effectiveness of traffic signs, and the overall transportation infrastructure to guide city planners in developing safer and more efficient streets.
Accessibility & Mobility Improvements: Deploy yolov7_rev02 in mobility aids like visually impaired walking assistants or apps to help users identify zebra crossings, motorbikes, cars, trucks, and traffic signs, giving them added confidence for independent travel in urban environments.
Traffic Surveillance & Safety Monitoring: Utilize yolov7_rev02 in video surveillance systems near zebra crossings and crowded streets to identify potentially dangerous situations, such as a pedestrian in danger due to a motorbike, car, or truck not respecting the zebra crossing or traffic sign. This real-time information can enable quick response from traffic enforcement or emergency services.

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{
                            yolov7_rev02_dataset,
                            title = { yolov7_rev02 Dataset },
                            type = { Open Source Dataset },
                            author = { labelingvehicles },
                            howpublished = { \url{ https://universe.roboflow.com/labelingvehicles/yolov7_rev02 } },
                            url = { https://universe.roboflow.com/labelingvehicles/yolov7_rev02 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-04-26 },
                            }