S2PixelCloudDetector can now calculate binary masks for previously cl…

…assified cloud probability maps (by applying convolution+dilation+threshold).

s2cloudless/S2PixelCloudDetector.py

@@ -114,6 +114,18 @@ def get_cloud_masks(self, X):
 
         cloud_probs = self.get_cloud_probability_maps(X)
 
+        return self.get_mask_from_prob(cloud_probs)
+
+    def get_mask_from_prob(self, cloud_probs):
+        """
+        Returns cloud mask by applying morphological operations -- convolution and dilation --
+        to input cloud probabilities.
+
+        :param cloud_probs: cloud probability map
+        :type cloud_probs: numpy array of cloud probabilities (shape n_images x n x m)
+        :return: raster cloud mask
+        :rtype: numpy array (shape n_images x n x m)
+        """
         if self.average_over:
             cloud_masks = np.asarray([convolve(cloud_prob, self.conv_filter) > self.threshold
                                       for cloud_prob in cloud_probs], dtype=np.int8)

setup.py

@@ -1,6 +1,6 @@
 from setuptools import setup, find_packages
 
-__version__ = '1.1.0'
+__version__ = '1.2.0'
 
 setup(name='s2cloudless',
       version=__version__,