People counting Object Detection Dataset and Pre-Trained Model by BusPas

Here are a few use cases for this project:

Crowd monitoring: The model can be used to count heads during public events, concerts, or festivals. This could help event organizers plan better for crowd control, emergency evacuations, or understanding attendee engagement.
Transportation planning: The model can be used to determine the average number of people at bus stops at specific times. This could aid in creating efficient bus schedules and ensuring that public transportation is appropriately staffed.
Commercial establishment monitoring: Retail stores or restaurants could use the model to track the number of customers during different times of the day to optimize working schedules, manage inventory, and improve customer service.
Security Systems: The model can be used in security surveillance to count the number of people in certain areas at particular times, potentially identifying unusual gatherings or anomalies.
Smart City Planning: Used in conjunction with other models, this People Counting model could help create smart cities by monitoring and managing the flow of people and public transportation vehicles, thus enabling efficient urban planning.

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{
                            people-counting-wk5f5_dataset,
                            title = { People counting Dataset },
                            type = { Open Source Dataset },
                            author = { BusPas },
                            howpublished = { \url{ https://universe.roboflow.com/buspas/people-counting-wk5f5 } },
                            url = { https://universe.roboflow.com/buspas/people-counting-wk5f5 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-06-30 },
                            }