m0t0rcycl3 Object Detection Dataset and Pre-Trained Model by TIP m0+0r

Images

7859 images

Explore Dataset

Here are a few use cases for this project:

Traffic Surveillance and Safety: The m0t0rcycl3 model could be utilized in traffic surveillance systems to detect and classify various types of motorcycles and scooters in real-time, helping to monitor traffic flow, identify traffic violations, and intervene in dangerous situations before accidents occur.
Shared Scooter Service Management: Companies that provide shared scooter or motorcycle services could use this model to identify whether a scooter is being used, is free or needs maintenance, aiding in better service management.
Augmented Reality Games/Apps: In AR games/apps that have missions or tasks involving motorcycles or scooters, the model might be used to recognize these vehicles in the players' real-world environment.
Vehicle Identification in Photos/Videos: For platforms where users share travel or lifestyle photos and videos, this model could be used to tag and classify media entries that contain different types of motorcycles or scooters. This would facilitate thematic searches and recommendations.
Autonomous Vehicles: In the domain of self-driving cars, the m0t0rcycl3 model could be used to accurately categorize and understand motorcycle classes, which could help in safer navigation and collision avoidance.

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{
                            m0t0rcycl3_dataset,
                            title = { m0t0rcycl3 Dataset },
                            type = { Open Source Dataset },
                            author = { TIP m0+0r },
                            howpublished = { \url{ https://universe.roboflow.com/tip-m0-0r/m0t0rcycl3 } },
                            url = { https://universe.roboflow.com/tip-m0-0r/m0t0rcycl3 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-04-28 },
                            }