code: def get_cloud_masks(self, X):
          
  
          cloud_probs = self.get_cloud_probability_maps(X)
  
          return self.get_mask_from_prob(cloud_probs)
docs: Runs the cloud detection on the input images (dimension n_images x n x m x 10
          or n_images x n x m x 13) and returns the raster cloud mask (dimension n_images x n x m).
          Pixel values equal to 0 indicate pixels classified as clear-sky, while values
          equal to 1 indicate pixels classified as clouds.
  
          :param X: input Sentinel-2 image obtained with Sentinel-Hub's WMS/WCS request
                    (see https://github.com/sentinel-hub/sentinelhub-py)
          :type X: numpy array (shape n_images x n x m x 10 or n x m x 13)
          :return: raster cloud mask
          :rtype: numpy array (shape n_images x n x m)