Yolo v5 Object Detection Dataset and Pre-Trained Model by Akash Medishetty

Images

868 images

Explore Dataset

Here are a few use cases for this project:

Traffic Monitoring and Analysis: Yolo v5 can be used to analyze traffic patterns, identify peak hours, and estimate traffic density on highways or in urban areas. The model's ability to distinguish between cars, bikes, and bicycles can help determine which modes of transportation are the most prevalent and optimize traffic flow management strategies.
Parking and Mobility Solutions: The model can be utilized in managing parking lots, ensuring efficient usage of available parking spaces, identifying illegally parked vehicles or optimizing bicycle parking areas. Additionally, it can help improve urban planning by analyzing demand for bike lanes or dedicated bicycle parking.
Advanced Driver Assistance Systems (ADAS): Yolo v5 can be integrated into vehicle ADAS technology to enhance driver awareness and safety by detecting surrounding cars, bikes, and bicycles. This can help in avoiding potential collisions, lane change assistance, and maintaining safe distances while driving.
Smart Security Cameras and Surveillance: The model can assist in maintaining traffic law enforcement by detecting traffic violations like speeding or driving in bicycle lanes, helping officials identify and track offenders. Additionally, it can analyze street layouts and inform planners about potential accident-prone areas.
Autonomous Vehicle Development: Yolo v5 can be incorporated into autonomous vehicle systems, helping to identify and track nearby vehicles and bicycles more accurately, thus ensuring safe navigation, obstacle avoidance, and improved decision-making capabilities for self-driving cars.

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{
                            yolo-v5-gzohs_dataset,
                            title = { Yolo v5 Dataset },
                            type = { Open Source Dataset },
                            author = { Akash Medishetty },
                            howpublished = { \url{ https://universe.roboflow.com/akash-medishetty/yolo-v5-gzohs } },
                            url = { https://universe.roboflow.com/akash-medishetty/yolo-v5-gzohs },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { apr },
                            note = { visited on 2024-05-07 },
                            }