Orginal_V9_WithAug Object Detection Dataset and Pre-Trained Model by MYDATASET

Images

2007 images

Explore Dataset

Here are a few use cases for this project:

Traffic Management: The AU-INV-P model can be integrated with city traffic systems to automate traffic management by identifying different types of vehicles, thereby optimizing traffic signals and reducing congestion.
Parking Enforcement: This model can be used to automate parking enforcement by identifying vehicle types in specific parking zones. Authorities can easily manage parking lots designated specifically for cars, bikes, trucks, etc.
Transportation Business Analysis: Logistics and transportation companies can use this model to classify and count the number of each vehicle type present in a certain area or on a specific route to analyze business metrics and monitor cargo movement.
Road Safety Improvement: Authorities can use the AU-INV-P model to automize traffic rule enforcement such as cab, bus and truck restrictions in specific lanes or zones. This could help improve overall road safety.
Fleet Management: Rental companies, cab services, and other fleet business operators can use the model to monitor and segregate their vehicles effectively, which could improve operational efficiency.

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{
                            orginal_v9_withaug_dataset,
                            title = { Orginal_V9_WithAug Dataset },
                            type = { Open Source Dataset },
                            author = { MYDATASET },
                            howpublished = { \url{ https://universe.roboflow.com/mydataset-zvvd9/orginal_v9_withaug } },
                            url = { https://universe.roboflow.com/mydataset-zvvd9/orginal_v9_withaug },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { feb },
                            note = { visited on 2024-04-30 },
                            }