Typo and docstring fix
@@ -340,18 +340,21 @@ class AddMultiCloudMaskTask(EOTask):
"""Constructor.
:param mono_classifier: Classifier used for mono-temporal cloud detection (`s2cloudless` or equivalent).
- Default value: None (s2cloudless is used)
- :type mono_classifier: sklearn Estimator that works on the 10 selected reflectance bands
+ Must work on the 10 selected reflectance bands as features
(`B01`, `B02`, `B04`, `B05`, `B08`, `B8A`, `B09`, `B10`, `B11`, `B12`)
+ Default value: None (s2cloudless is used)
+ :type mono_classifier: sklearn Estimator
:param multi_classifier: Classifier used for multi-temporal cloud detection.
- Default value: None (SSIM-based model is used)
- :type multi_classifier: sklearn Estimator that works on the 90 multi-temporal features:
+ Must work on the 90 multi-temporal features:
- raw reflectance value in the target frame,
- average value within a spatial window in the target frame,
- maximum, mean and standard deviation of the structural similarity (SSIM)
- indices between a spatial window in the target frame and every other,
- minimum and mean reflectance of all available time frames,
- - maximum and mean difference in reflectances between the target frame and every other.
+ - maximum and mean difference in reflectances between the target frame
+ and every other.
+ Default value: None (SSIM-based model is used)
+ :type multi_classifier: sklearn Estimator
:param data_feature: Name of the key in the `eopatch.data` dictionary, which stores raw reflectance data.
Default value: `'BANDS-S2-L1C'`.
:type data_feature: str
@@ -488,7 +491,7 @@ class AddMultiCloudMaskTask(EOTask):
sigma = 1.0
elif service_type == ServiceType.WCS:
- hr_res_x, hr_res_y = float(meta_info['size_x'].strip('m')), int(meta_info['size_y'].strip('m'))
+ hr_res_x, hr_res_y = float(meta_info['size_x'].strip('m')), float(meta_info['size_y'].strip('m'))
if self.processing_resolution is not None:
proc_res = float(self.processing_resolution.strip('m'))
