Changelog
Version 2.0.0
Notable changes
torchis now used instead ofnumpyfor controlling the randomness intransforms.New LighthningModule
PCDLit, which supports customization for optimizer and scheduler.New storing scheme for point clouds, stored as plain
.npyfiles instead of a single.npzfile.
Added in version 2.0.0:
Support for visualizing a generic point cloud (#69).
Commands
aidsorb createandaidsorb preparenow support configuration files.Option for ignoring critical indices in
PointNetBackbone.forward().Support for visualizing
.npyfile withdraw_pcd_from_file()andaidsorb visualize.RandomSampleandRandomFliptransformations.Support for erasing a fraction of points and local patches in
RandomErase.Support for configuring activation function in
conv1d_block()anddense_block().Support to
.load_from_checkpointwithout arguments forPCDLitandPCDDataModule.Support for unlabeled data in
PCDDataset,PCDDataModuleandCollator.Option
drop_lastforPCDDataModule.PCDLitwhich supports customization for optimizer and scheduler (#25).center_pcd()as a functional interface ofCenter.
Changed in version 2.0.0:
Renamed
get_elements()toget_atom_names().Columns in
PCDDataset.Ynow follow the order specified by the user (#67).Renamed
litmodelstolitmodules(#63).Collatorandpad_pcds()now accept keyword-only arguments.get_names()now returnstupleinstead oflist.Bumped Lightning version to
>=2.5.0(#29).upsample_pcd()moved fromdatatotransformsand now raises error if target size is not greater than the original.split_pcd()moved fromutilstotransformsand no longer copies data.transformsnow usetorchinstead ofnumpy(#32).Removed defaults for
transformssince there is no consensus on “good” defaults.Point clouds are now stored as plain
.npyfiles under a directory files instead of a single.npz(#3).
Removed in version 2.0.0:
Jitter, useRandomJitterinstead.modelsto simplify codebase and improve project structure.PointLit, usePCDLitinstead.Identitysince it is equivalent totorch.nn.Identity(and thus redundant).
Version 1.0.0
🎂 First release for public usage.