Function get_training_inputs returns labels. These values are meant to be identification values for the pixel in the training data so that groups of pixels sharing the same label value can be grouped together for things like K-fold cross-validation. Currently, however, there are two problems:
labels is too specific. The training data classification label, is a label, so this should be more specific to what it actually means
Could instead be, for example, roi_id, roi_label, etc.
Nothing becomes of these labels! The SpatialKFold generators both use labels so that individuals from the same label are not mixed in the training / testing splits, but the labels are generated using scipy.ndimage.label instead of giving the user the ability to specify these labels via their ROI image.
Function
get_training_inputsreturnslabels. These values are meant to be identification values for the pixel in the training data so that groups of pixels sharing the samelabelvalue can be grouped together for things like K-fold cross-validation. Currently, however, there are two problems:labelsis too specific. The training data classification label, is alabel, so this should be more specific to what it actually meansroi_id,roi_label, etc.SpatialKFoldgenerators both use labels so that individuals from the same label are not mixed in the training / testing splits, but the labels are generated usingscipy.ndimage.labelinstead of giving the user the ability to specify these labels via their ROI image.