What does the Smoker Detection Classification Dataset contain?

The dataset contains 1,120 images equally divided into two classes: Smoking (560) and Not Smoking (560). Images are standardized to 250×250 resolution and capture diverse scenarios to improve model training.

How was the dataset sourced and prepared?

Images were curated from search engines using diverse keywords. They were resized to 250×250 resolution, ensuring class balance. The Not Smoking class includes look-alike gestures such as drinking water or using an inhaler to avoid bias and improve model robustness.

What are the applications of the Smoker Detection Classification Dataset?

The dataset is ideal for training deep learning models for automated smoker detection, public health monitoring, environmental analytics, and smart city surveillance systems.

Smoker Detection Classification Dataset

Home » Dataset Download » Smoker Detection Classification Dataset

Smoker Detection Classification Dataset

Datasets

File

Smoker Detection Classification

Use Case

Smoker Detection Classification

Description

Discover a meticulously curated Smoker Detection Classification Dataset featuring 1120 high-quality images, balanced with 560 smoking and 560 non-smoking scenarios.

Description:

The dataset comprises 1120 images, equally divided into two classes: Smoking (560 images) and NotSmoking (560 images). It is designed to train models for detecting smokers in various settings.

Download Dataset

Details:

Class Balance: 560 images of smokers and 560 images of non-smokers.
Image Sourcing: Curated from search engines using diverse keywords.
Class Content:
- Smoking Class: Features images of people smoking from various angles and gestures.
- NotSmoking Class: Includes images of people in gestures similar to smoking, like drinking water or using an inhaler.
Purpose: Ideal for developing deep learning algorithms for automated smoker detection, environmental monitoring, and smart city surveillance.
Preprocessing: All images are resized to 250×250 resolution.

Key Features of the Dataset

Balanced dataset with equal class distribution
Diverse smoking and non-smoking gestures
Preprocessed images with fixed resolution
Suitable for classification and detection tasks
Real-world image variations for better model performance

Applications and Use Cases

The Smoking Detection Dataset can be used in several important areas. For example:

Smart City Surveillance: Detect smoking in restricted areas
Environmental Monitoring: Monitor smoking behavior in public spaces
AI Research: Develop image classification models
Healthcare and Safety Systems: Support smoke-free environment policies

Conclusion

The Smoking Detection Dataset is a valuable resource for developing automated smoker detection systems. Overall, it provides balanced and diverse image data for training machine learning models. More importantly, it supports research in surveillance, public safety, and smart monitoring applications

This dataset is sourced from Kaggle.

Contact Us

Let's Discuss your Data collection Requirement With Us

To get a detailed estimation of requirements please reach us.

Smoker Detection Classification Dataset