urbanlc.model.pipeline_transforms.OLITIRSTransformer

class urbanlc.model.pipeline_transforms.OLITIRSTransformer(means=[0.05244060772832586, 0.06419783589372872, 0.09355600224058667, 0.09683895508641474, 0.20228001018199623, 0.17475386334671822, 0.1299458739828, 295.2477865092859, 0.0, 0.0, 0.0], stds=[0.03056170518168943, 0.034643695523177205, 0.042781807483223834, 0.05637172934273404, 0.09086194854765857, 0.08659663887712442, 0.0762477946322169, 49.351306701659716, 1.0, 1.0, 1.0])

Input Preprocessor for Landsat data from OLI/TIRS sensor (Landsat 8 - 9).

Methods

calculate_statistics([root, filename_glob, ...])	Calculate mean and standard deviation statistics of the dataset.
transform(img, mask[, is_training, p_hflip, ...])	Apply transformations to the input Landsat image and land cover.