terrace fusion Computer Vision Project
Updated 3 years ago
86
views2
downloadsMetrics
Here are a few use cases for this project:
-
"Public Safety Compliance" Use this model to monitor public spaces like parks, beaches, or shopping areas to ensure compliance with social distancing protocols. The nature of the images in the dataset could help identify instances where people are or aren't practicing safe distances and provide data on public adherence to guidelines.
-
"Event Management" Event organizers can integrate this model into their security system to enforce social distancing norms during festivals, concerts, games, or any other mass gathering. This will enable efficient crowd control without requiring extensive human effort.
-
"Retail Analytics" Retail stores could use this model to monitor customers' adherence to social distancing norms inside their stores. Understanding customer behavior with respect to these norms may provide insights for strategic decisions and operational efficiency.
-
"Urban Planning and Research" Researchers or urban planners can utilize this model to study the effectiveness of current social distancing policies and norms in different environments. This could help guide future policies or planning of city spaces.
-
"Education Sector" Schools, colleges, and universities can input live feeds or recorded footage to monitor student behavior regarding social-distancing norms. Providing real-time feedback, or periodic reports might help educational institutions in ensuring an appropriate level of safety on their campuses.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
![Supervision](/images/supervision-icon.png)
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
terrace-fusion_dataset,
title = { terrace fusion Dataset },
type = { Open Source Dataset },
author = { datasets connection },
howpublished = { \url{ https://universe.roboflow.com/datasets-connection/terrace-fusion } },
url = { https://universe.roboflow.com/datasets-connection/terrace-fusion },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { jun },
note = { visited on 2024-12-19 },
}