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 data and target


COVID-19: Face Mask Detection Using Deep Learning and OpenCV

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The data and targets are then split into training, and testing data be keeping 10% of data as testing and 90% as training data. A checkpoint is created, which will save the model, which will have the minimum validation loss. Then the training data is then fitted in the model so that predictions can be made in the future.