Face Mask Wearing Image Dataset: Correct vs. Incorrect Usage
Description
The Face Mask Wearing Image Dataset is a comprehensive collection of images focused on different types of face masks and their usage. This dataset has been meticulously organized and divided into two main folders: "Correct" and "Incorrect," representing instances of face masks being worn properly and improperly, respectively. Correct: This folder contains images of individuals wearing face masks correctly. It comprises four subfolders, each representing a specific type of face mask: Bandana: Images of individuals wearing bandana-style face masks correctly. Cotton: Images of individuals wearing cloth or cotton face masks correctly. N95: Images of individuals wearing N95 respirators correctly. Surgical: Images of individuals wearing surgical masks correctly. Incorrect: This folder contains images of individuals wearing face masks improperly. Like the "Correct" folder, it also comprises four subfolders corresponding to the different types of face masks: Bandana: Images of individuals wearing bandana-style face masks incorrectly. Cotton: Images of individuals wearing cloth or cotton face masks incorrectly. N95: Images of individuals wearing N95 respirators incorrectly. Surgical: Images of individuals wearing surgical masks incorrectly. Within each of the above subfolders, there are three additional subfolders based on gender: Child: Images of children wearing the specific type of face mask (correctly or incorrectly). Male: Images of males wearing the specific type of face mask (correctly or incorrectly). Female: Images of females wearing the specific type of face mask (correctly or incorrectly). The dataset is designed to cover a diverse range of scenarios and variations in face mask usage across different mask types, age groups, and genders. Total Images: The dataset contains a total of 24,916 images. Usage: The Face Mask Wearing Image Dataset can be used for various research purposes, such as developing and evaluating machine learning algorithms for face mask detection and classification. Researchers can utilize this dataset to train models that can identify and differentiate between correct and incorrect face mask usage, contributing to public health initiatives, and promoting proper mask-wearing behavior.