The model has been trained with google teachable machine with data collected by Asutosh Pati. Just put the mask_validator.py in your project directory to use it and import the file in your main program to use it. You can use the example file and image to test the program.

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numpy==1.19.5

opencv-contrib-python==4.5.1.48

opencv-python==4.5.1.48

tensorflow-gpu==2.5.0

import cv2
import mask_validator

img = cv2.imread('test_image.jpg')
# use cropped face image
print(mask_validator.validate_mask(img))

This function predicts the whether mask is present in cropped face image or not. It returns the prediction label (Without Mask/With Mask) & confidence (in 0 to 1) of prediction.

Parameter

• image: numpy.ndarray
    Cropped face image as numpy array.

Returns

• op_class: string
    Output class label of predicted image.
• op_factor: float
    Output confidence (percentage) of prediction ranges in 0 to 1.