object detection Object Detection Dataset and Pre-Trained Model by Henujan

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Explore Dataset

Here are a few use cases for this project:

Traffic Monitoring: The object detection model can be used in traffic control systems to automate the process of identifying motorbike riders, differentiating bikers with helmets from those without, thereby encouraging safety regulations.
Law Enforcement: They can be used by traffic police to swiftly identify traffic rule violators such as motorbike riders without a helmet or to detect and track specific number plates.
Accident Analysis: In case of road accidents, investigators can use this model to analyze CCTV footage to determine whether the motorbike riders were wearing helmets at the time of an accident.
Advanced Driver-Assistance Systems (ADAS): Companies developing ADAS or self-driving technologies can use this model to detect and classify motorbikes and relevant sub-classes to ensure safe navigation.
License Plate Recognition Systems: This model could aid parking authorities or toll booths in identifying the number plates of motorbikes quickly and accurately.

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{
                            object-detection-vxyo1_dataset,
                            title = { object detection Dataset },
                            type = { Open Source Dataset },
                            author = { Henujan },
                            howpublished = { \url{ https://universe.roboflow.com/henujan/object-detection-vxyo1 } },
                            url = { https://universe.roboflow.com/henujan/object-detection-vxyo1 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-04-23 },
                            }