Detecting whether a person is wearing a mask or not in real-time using Python, Keras, OpenCV, TensorFlow, NumPy, etc. The folder consists of 1900 masked images and unmasked images.

1. Created 2 lists – data [] and labels []
   
2. In data [], arrays of all the images will be appended and in labels [], arrays of "with_mask" and "without_mask" which is converted using LabelBinarizer from the scikit learn library is appended
   
3. All the images are listed using load_img function from Keras library, and then attached corresponding labels to it
   
4. The target size is set to 224*224(width and height) so that model is perfect
   
5. Using img_to_array from Keras, all the images are converted to arrays.
   
6. MobileNet is applied so preprocess_input is used.
   
7. Train Test split is done.
   

image

The below graph summarizes the training image
There is a reduction in loss as the number of epochs increases

Using deploy .prototxt and res10_300x300_ssd_iter_140000.caffemodel face is detected and using our deep learning model mask is detected. Please refer to the "Detect Mask Video.ipynb" for the code.