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Add logic to nonrigid(_lowrank) to break down a large dataset into roughly equally sized chips, later stitching the results of those chip runs back together. This should provide roughly equal results to running the algorithm on the whole dataset, since the nonrigid should allow bending past certain scales.
PDAL has a internal chipper that does about what we want. However, it would be nice to not add big dependency like that. We could extract the chipper for our own purposes, or use some other point-count splitting algorithm.
The text was updated successfully, but these errors were encountered:
Add logic to nonrigid(_lowrank) to break down a large dataset into roughly equally sized chips, later stitching the results of those chip runs back together. This should provide roughly equal results to running the algorithm on the whole dataset, since the nonrigid should allow bending past certain scales.
PDAL has a internal chipper that does about what we want. However, it would be nice to not add big dependency like that. We could extract the chipper for our own purposes, or use some other point-count splitting algorithm.
The text was updated successfully, but these errors were encountered: