Smoker Detection Image Dataset

Smoker Detection Image Dataset

Datasets

Smoker Detection Image Dataset

File

Smoker Detection Image

Use Case

Smoker Detection Image

Description

Explore the Smoker Detection Image Dataset, featuring 1,120 meticulously curated images for developing advanced AI models. Perfect for automated detection, environmental surveillance, and smart city applications.

Smoker Detection Image Dataset

Description:

The Smoker Detection Image Dataset is an extensive collection designed to aid in the automated detection and screening of smokers, contributing to green environment initiatives and enhanced surveillance in smart cities. The dataset consists of 1,120 images, equally divided into two distinct classes:

  • Smoking (Smokers): 560 images
  • Not Smoking (Non-Smokers): 560 images
Download Dataset

Dataset Curation

This dataset was meticulously curated by utilizing various search engines with multiple keywords such as “cigarette smoking,” “smoker,” “person,” “coughing,” “taking inhaler,” “person on the phone,” and “drinking water.” The intent was to gather a versatile range of images that create a degree of inter-class confusion, thereby enhancing the robustness of machine learning models trained on this data.

Class Descriptions

  • Smoking Class: Contains images of individuals smoking from multiple angles and performing various gestures associated with smoking.
  • Not Smoking Class: Includes images of individuals engaging in activities with gestures similar to smoking, such as drinking water, using an inhaler, holding a mobile phone, and coughing. This intentional overlap aims to challenge and improve the model’s discriminative capabilities.

Image Specifications

  • All images are preprocessed and resized to a resolution of 250×250 pixels.
  • The dataset is divided with 80% of the images allocated for training and validation, and 20% for testing.

Usage and Applications

The Smoker Detection Image Dataset is a valuable resource for researchers and developers aiming to develop and refine deep learning algorithms for:

  • Automated Detection: Enhancing public health by identifying smokers in public spaces.
  • Environmental Surveillance: Supporting green initiatives through monitoring and reducing smoking-related pollution.
  • Smart City Implementations: Integrating with smart city infrastructure for improved surveillance and enforcement of no-smoking zones.

Contact Us

Please enable JavaScript in your browser to complete this form.
Technology

Quality Data Creation

Technology

Guaranteed TAT

Technology

ISO 9001:2015, ISO/IEC 27001:2013 Certified

Technology

HIPAA Compliance

Technology

GDPR Compliance

Technology

Compliance and Security

Let's Discuss your Data collection Requirement With Us

To get a detailed estimation of requirements please reach us.

Scroll to Top

Please provide your details to download the Dataset.