Smoker Detection Classification Dataset

Smoker Detection Classification Dataset

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Smoker Detection Classification Dataset

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Smoker Detection Classification

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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.

Smoker Detection Classification Dataset

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.

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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.

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