What's the use of precompute.py about lidar_snow_sim HOT 3 CLOSED

With precompute.py, you can compute the snowflake patterns, which are then stored on disk.
This process in its current implementation takes too much time to do on the fly while training your model.
During training, you can then load those snowflake patterns from the disk without computing them each time.

from lidar_snow_sim.

With precompute.py, you can compute the snowflake patterns, which are then stored on disk. This process in its current implementation takes too much time to do on the fly while training your model. During training, you can then load those snowflake patterns from the disk without computing them each time.

Thanks for your kind reply! Also I would like to know why do you use calibration of kitti dataset instead of dense dataset in precompute.py. Because you have said you

With precompute.py, you can compute the snowflake patterns, which are then stored on disk. This process in its current implementation takes too much time to do on the fly while training your model. During training, you can then load those snowflake patterns from the disk without computing them each time.

Thanks for your kind reply! Also, I would like to know why you use the calibration of kitti dataset instead of dense dataset in precompute.py. Because you have said that the code only implemented the snow simulation of dense dataset

from lidar_snow_sim.

We use the calibration file from the DENSE dataset.
It is compatible witht the KITTI calibration code.
So we just re-use the KITTI code, but not their calibration.

from lidar_snow_sim.