diff --git a/README.md b/README.md
index c71966c..5a5250b 100644
--- a/README.md
+++ b/README.md
@@ -71,7 +71,7 @@ The easiest way to install ukis-csmask is through pip. The default installation
 pip install ukis-csmask
 ```
 
-To install ukis-csmask with GPU support run the following instead. This requires that you have a GPU with CUDA runtime libraries (CUDA 10.2 and cuDNN 8.0.3) installed on the system.
+To install ukis-csmask with GPU support run the following instead. This requires that you have a GPU with CUDA runtime libraries installed on the system.
 
 ```shell
 pip install ukis-csmask[gpu]
diff --git a/requirements.txt b/requirements.txt
index 92dd0ac..372aba6 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,3 @@
 numpy
-onnxruntime
+onnxruntime>=1.13
 scipy
diff --git a/tests/test_mask.py b/tests/test_mask.py
index fe65aba..f5c1853 100644
--- a/tests/test_mask.py
+++ b/tests/test_mask.py
@@ -70,8 +70,8 @@ def test_csmask_valid(data):
     csmask = CSmask(img=data["img"], band_order=["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"])
     y_pred = csmask.valid
     y_true = reclassify(data["msk"], {"reclass_value_from": [0, 1, 2, 3, 4], "reclass_value_to": [0, 1, 1, 1, 0]})
-    y_true_inverted = ~y_true.astype(np.bool)
-    y_true = (~ndimage.binary_dilation(y_true_inverted, iterations=4).astype(np.bool)).astype(np.uint8)
+    y_true_inverted = ~y_true.astype(bool)
+    y_true = (~ndimage.binary_dilation(y_true_inverted, iterations=4).astype(bool)).astype(np.uint8)
     y_true = y_true.ravel()
     y_pred = y_pred.ravel()
     kappa = round(cohen_kappa_score(y_true, y_pred), 2)
diff --git a/ukis_csmask/mask.py b/ukis_csmask/mask.py
index 9572776..53d2e81 100644
--- a/ukis_csmask/mask.py
+++ b/ukis_csmask/mask.py
@@ -118,8 +118,8 @@ def _valid(self, invalid_buffer):
 
         # dilate the inverse of the binary valid pixel mask (invalid=0)
         # this effectively buffers the invalid pixels
-        valid_i = ~valid.astype(np.bool)
-        valid = (~ndimage.binary_dilation(valid_i, iterations=invalid_buffer).astype(np.bool)).astype(np.uint8)
+        valid_i = ~valid.astype(bool)
+        valid = (~ndimage.binary_dilation(valid_i, iterations=invalid_buffer).astype(bool)).astype(np.uint8)
 
         if self.nodata_value is not None:
             # add image nodata pixels to valid pixel mask