annotate5 Object Detection Dataset and Pre-Trained Model by Nandhini Elangovan

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Explore Dataset

Here are a few use cases for this project:

Pedestrian Traffic Management: "annotate5" can be used to monitor and analyze pedestrian traffic flow in urban areas or public places like shopping malls, parks, or airports. The collected data could inform decisions about infrastructure planning and upgrades.
Personal Security Applications: This model can assist in the development of personal safety apps that alert users to the presence of nearby pedestrians, potentially preventing collisions or accidents.
Autonomous Vehicles: It can be used to train autonomous vehicles to identify pedestrians to ensure safer driving and prevent accidents.
Smart City Applications: The "annotate5" model can become an integral part of smart city planning, helping to optimize pedestrian pathways or identify crowded areas and bottlenecks.
Health and Social Studies: The model can also be used in studies related to public health or sociology, such as examining physical activity levels in different neighborhoods or understanding patterns of social interaction in public spaces.

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{
                            annotate5_dataset,
                            title = { annotate5 Dataset },
                            type = { Open Source Dataset },
                            author = { Nandhini Elangovan },
                            howpublished = { \url{ https://universe.roboflow.com/nandhini-elangovan-cx4s3/annotate5 } },
                            url = { https://universe.roboflow.com/nandhini-elangovan-cx4s3/annotate5 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-06-26 },
                            }