studycafe Object Detection Dataset and Pre-Trained Model by studycafe

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Explore Dataset

Here are a few use cases for this project:

Occupancy Monitoring: "studycafe" can be used in a library, cafe, or any co-working spaces to monitor seat availability. It can count the number of persons and chairs, providing real-time data on how many seats are currently available or occupied.
Crowd Management: In a larger setting like a conference or lecture hall, this model can calculate how many people are present and how many seats are left. It assists in managing crowd and avoiding over-occupancy.
Surveillance System: For security purposes, "studycafe" can identify if a person is present in a restricted zone. If a person is detected in a place where there should only be chairs, the system could alert security.
Assisting in Study Environment Setup: This model can analyze images of study environments and help set up a perfect study space according to the user's preference (for instance, the ratio of persons-to-chairs, or identifying images where spaces aren't too crowded).
Furniture Retail and Manufacturing: Stores or manufacturers can use the model to see how their chairs look and fit with the presence of a person. This can assist in aesthetically designing spaces, marketing their products, or in ergonomics studies.

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{
                            studycafe_dataset,
                            title = { studycafe Dataset },
                            type = { Open Source Dataset },
                            author = { studycafe },
                            howpublished = { \url{ https://universe.roboflow.com/studycafe/studycafe } },
                            url = { https://universe.roboflow.com/studycafe/studycafe },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-04-27 },
                            }