Drixter Hernandez

Drinking Dataset

Object Detection

Drinking Dataset Computer Vision Project


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Here are a few use cases for this project:

  1. Public Safety and Law Enforcement: Authorities could use the model to monitor public spaces for violations of smoking or drinking laws, aiding in maintaining public safety and enforcing laws more effectively.

  2. Social Studies Research: Researchers in fields like sociology or public health could use the data to study patterns in public drinking or smoking, contributing to future policy discussions or interventions.

  3. Surveillance System for Restricted Areas: This model could be employed in surveillance systems in specific areas such as parks, schools or hospitals, automatically detecting any violations and sending alerts to the concerned personnel.

  4. Smart Cities Initiative: In a smart city context, this dataset could be utilized to enforce municipal codes and improve the quality of life in urban areas by cracking down on public drinking or smoking where it's prohibited.

  5. Advertising Effectiveness: Businesses or marketing researchers could use the model to evaluate the effectiveness of anti-drinking or smoking campaigns in real-time and get useful insights to fine-tune their efforts.

Cite this Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ drinking-dataset_dataset,
    title = { Drinking Dataset Dataset },
    type = { Open Source Dataset },
    author = { Drixter Hernandez },
    howpublished = { \url{ https://universe.roboflow.com/drixter-hernandez/drinking-dataset } },
    url = { https://universe.roboflow.com/drixter-hernandez/drinking-dataset },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { jul },
    note = { visited on 2023-12-11 },

Find utilities and guides to help you start using the Drinking Dataset project in your project.

Last Updated

a year ago

Project Type

Object Detection




Public Smoking, Public-Drinking, ambiguous, non-violation

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CC BY 4.0