Face mask use is crucial for preventing and limiting the development of COVID-19 and other respiratory viral infections. Face masks can be used to shield healthy individuals or stop the spread of infection by sick people. A computer vision system and Deep Learning algorithm that are capable of performing this type of detection are required in order to determine whether or not a person is wearing a face mask. For the purposes of this study, photos of people wearing masks and those who are not are distinguished using a Deep Neural Network, more precisely a Convolutional Neural Network. On the training set, the CNN achieves an accuracy of 98.6%, and on the test set, 97.3%. Then, a real-time classification of mask or no mask is made using the stored weights of this CNN. To carry out this operation, the webcam captures the footage; the frames are then analyzed and sent to the model. The model operates effectively with no discernible delay between donning the mask and taking it off and displaying the forecast.