A Masked and Unmasked Face Dataset

Description

A Masked and Unmasked Face Dataset is a collection of a face without medical mask (unmasked face) images and a face with medical mask (masked face) images. Based on the Deep Learning approach, this dataset can be used to build a model to predict the original face (unmasked face) from a masked face image. The dataset is organized into two main folders: the Original and Cropped folders. The Original folder for the original file of face images with the size of the image (height x width) 1080 x 1920 pixels (both masked and unmasked). On the other hand, the Cropped folder contains images focusing only on the face area (both masked and unmasked); the size of the images varies depending on the size of the detected face area. Each main folder consists of two subfolders, i.e., Masked and Unmasked subfolders. The Masked subfolder consists of face images with a medical mask; on the other hand, the Unmasked subfolder consists of face images without a medical mask. There are 330 images in each subfolder.

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