How to properly and efficiently read and filter a .las file to memory in chunks using laspy
I’m working on a number of large .las files (>300M points) from LiDAR scans where I have to perform some calculations on a subset of the points in those files. Reading the files all at once is problematic due to the large memory use when reading all the data into memory, making the processing extremely slow. I’m not looking for a solution that writes the files to disk (e.g. chunk writing), but rather something that returns a LasData object with the same dimensions/point format as the original .las file, but with a subset of the points.
How to properly and efficiently read and filter a .las file to memory in chunks using laspy
I’m working on a number of large .las files (>300M points) from LiDAR scans where I have to perform some calculations on a subset of the points in those files. Reading the files all at once is problematic due to the large memory use when reading all the data into memory, making the processing extremely slow. I’m not looking for a solution that writes the files to disk (e.g. chunk writing), but rather something that returns a LasData object with the same dimensions/point format as the original .las file, but with a subset of the points.
How to properly and efficiently read and filter a .las file to memory in chunks using laspy
I’m working on a number of large .las files (>300M points) from LiDAR scans where I have to perform some calculations on a subset of the points in those files. Reading the files all at once is problematic due to the large memory use when reading all the data into memory, making the processing extremely slow. I’m not looking for a solution that writes the files to disk (e.g. chunk writing), but rather something that returns a LasData object with the same dimensions/point format as the original .las file, but with a subset of the points.
How to properly and efficiently read and filter a .las file to memory in chunks using laspy
I’m working on a number of large .las files (>300M points) from LiDAR scans where I have to perform some calculations on a subset of the points in those files. Reading the files all at once is problematic due to the large memory use when reading all the data into memory, making the processing extremely slow. I’m not looking for a solution that writes the files to disk (e.g. chunk writing), but rather something that returns a LasData object with the same dimensions/point format as the original .las file, but with a subset of the points.
How to properly and efficiently read and filter a .las file to memory in chunks using laspy
I’m working on a number of large .las files (>300M points) from LiDAR scans where I have to perform some calculations on a subset of the points in those files. Reading the files all at once is problematic due to the large memory use when reading all the data into memory, making the processing extremely slow. I’m not looking for a solution that writes the files to disk (e.g. chunk writing), but rather something that returns a LasData object with the same dimensions/point format as the original .las file, but with a subset of the points.