geo-deep-learning
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To many patches after tiling (for flood modelling interest)
After tiling, the destination folder contains all possible patches from the raster image, event when there is not ground truth (GT) labels matching (< min_annot_perc). Flood happens close to water bodies, and in general, flood extensions represents a small percent of surface from the original images. Therefore, majority of patch have no GT match. Should a cleaning process be implemented into DGL (automatically or not) or as an independent script?