Head_count Object Detection Dataset and Pre-Trained Model by CSE 499

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Explore Dataset

Here are a few use cases for this project:

Event Management: Head_count can be used by event planners and managers to monitor indoor and outdoor events, such as conferences, concerts, or sports games to estimate the number of attendees and ensure adherence to the venue's capacity limits.
Crowd Safety and Security: Public authorities and event organizers can use the Head_count model to analyze real-time video feeds at public gatherings and crowded areas, allowing them to detect overcrowding and manage crowd flow to mitigate potential safety and security risks.
Retail and Business Analytics: Owners of stores, shopping malls, and restaurants can use Head_count to analyze customer footfall, allowing them to assess customer behavior, optimize staff allocation, and make data-driven decisions to improve overall business performance.
Transportation Systems: Head_count can be employed by transportation networks such as airports, train stations, and bus stations to analyze the number of people waiting in queues, manage crowd control, and optimize resource scheduling and capacity planning.
Smart Cities and Urban Planning: Urban planners and city officials can utilize the Head_count model to obtain insights about pedestrian traffic patterns, enabling them to make better-informed decisions regarding infrastructure development, public space management, and overall 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{
                            head_count-66hcq_dataset,
                            title = { Head_count Dataset },
                            type = { Open Source Dataset },
                            author = { CSE 499 },
                            howpublished = { \url{ https://universe.roboflow.com/cse-499-ecvhx/head_count-66hcq } },
                            url = { https://universe.roboflow.com/cse-499-ecvhx/head_count-66hcq },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jun },
                            note = { visited on 2024-05-04 },
                            }