Merge pull request #84 from sentinel-hub/develop

Release 1.7.2

Author: zigaLuksic

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
       - id: end-of-file-fixer
       - id: requirements-txt-fixer
@@ -13,18 +13,18 @@ repos:
       - id: debug-statements
 
   - repo: https://github.com/psf/black
-    rev: 23.1.0
+    rev: 23.12.1
     hooks:
       - id: black
         language_version: python3
 
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: "v0.0.269"
+    rev: "v0.1.11"
     hooks:
       - id: ruff
 
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.6.3
+    rev: 1.7.1
     hooks:
       - id: nbqa-black
       - id: nbqa-ruff

pyproject.toml

@@ -35,7 +35,7 @@ classifiers = [
 ]
 dependencies = [
     "lightgbm>=2.0.11",
-    "numpy>=1.13.3",
+    "numpy>=1.13.3,<2",
     "opencv-python-headless",
     "sentinelhub>=3.9.0",
     "typing_extensions",

s2cloudless/__init__.py

@@ -4,4 +4,4 @@
 from .pixel_classifier import PixelClassifier
 from .utils import download_bands_and_valid_data_mask
 
-__version__ = "1.7.1"
+__version__ = "1.7.2"

s2cloudless/cloud_detector.py

@@ -1,4 +1,5 @@
 """Module for pixel-based classification on Sentinel-2 L1C imagery."""
+
 from __future__ import annotations
 
 import os

s2cloudless/pixel_classifier.py

@@ -1,4 +1,5 @@
 """Module for pixel-based classifiers."""
+
 from __future__ import annotations
 
 from typing import Any, Protocol
@@ -75,8 +76,8 @@ def image_predict_proba(self, data: np.ndarray, **kwargs: Any) -> np.ndarray:
         pixels = data.reshape((-1, data.shape[-1]))
 
         if isinstance(self.classifier, Booster):
-            probabilities = self.classifier.predict(pixels, **kwargs)
-            probabilities = np.vstack((1.0 - probabilities, probabilities)).transpose()
+            proba = self.classifier.predict(pixels, **kwargs)
+            probabilities = np.vstack([1.0 - proba, proba]).transpose()  # type: ignore[operator, list-item]
         else:
             probabilities = self.classifier.predict_proba(pixels, **kwargs)
 

s2cloudless/utils.py

@@ -76,6 +76,6 @@ def download_bands_and_valid_data_mask(
 
 def cv2_disk(radius: int) -> np.ndarray:
     """Recreates the disk structural element from skimage.morphology using OpenCV."""
-    return cv2.circle(
+    return cv2.circle(  # type: ignore[call-overload]
         np.zeros((radius * 2 + 1, radius * 2 + 1), dtype=np.uint8), (radius, radius), radius, color=1, thickness=-1
     )

tests/test_utils.py

@@ -1,5 +1,6 @@
+from __future__ import annotations
+
 import datetime as dt
-from typing import Tuple
 
 import numpy as np
 import pytest
@@ -46,7 +47,7 @@
     ],
 )
 @pytest.mark.sh_integration()
-def test_download_bands_and_valid_data_mask(test_input: dict, expected_shape: Tuple[int, int, int]) -> None:
+def test_download_bands_and_valid_data_mask(test_input: dict, expected_shape: tuple[int, int, int]) -> None:
     bands, mask = download_bands_and_valid_data_mask(**test_input)
     assert bands.shape == expected_shape
     assert bands.dtype == np.float32