A deep learning CNN model to identify and classify and check if a person is wearing a mask or not.

Overview

Face Mask Detection

The Model is designed to check if any human is wearing a mask or not.

Dataset Description

The Dataset contains a total of 11,792 images divided in three folders

  • Test (992 images),
  • Train (10,000 images),
  • Valid (800 images),

Each of these folders has sub-folders :

  • Test

    • WithMask
    • WithoutMask
  • Train

    • WithMask
    • WithoutMask
  • Valid

    • WithMask
    • WithoutMask

you can download the dataset here

Convolution Base (VGG19)

image

to import the model, run

  from tensorflow.keras.applications import VGG19

Model Parameters

The total number of parameters of the model are 22,122,049 image

Result

__results___17_0

The training stablized due to early stopping after achieving the following parametrs

Accuracy in percentage
Training Accuracy 99.62
Validation Accuracy 99.75
Testing Accuracy 1.0
Loss in decimal
Training loss 0.0213
Validation loss 0.0760
Testing loss 5.9828e-04

The model trained for 16 epochs before early stopping conditions were met.

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