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seems the local threshold in the paper is implemented as global (=13) in tools/segmentation.py:
does it indeed? if so, how much effort is required to make it locally adaptive?
thanks!
The text was updated successfully, but these errors were encountered:
only that threshold optimization should probably account for overlapping between correct and incorrect text regions: precision matters more while overlapping whereas recall matters more while there is no overlapping.
seems the local threshold in the paper is implemented as global (=13) in tools/segmentation.py:
does it indeed? if so, how much effort is required to make it locally adaptive?
thanks!
The text was updated successfully, but these errors were encountered: