Pytorch Points 3D Files

Pytorch framework for doing deep learning on point clouds

This is an exact mirror of the Pytorch Points 3D project, hosted at https://github.com/torch-points3d/torch-points3d. SourceForge is not affiliated with Pytorch Points 3D. For more information, see the SourceForge Open Source Mirror Directory.

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Name	Modified	Size	InfoDownloads / Week
Parent folder
1.2.0.tar.gz	2020-12-18	88.6 MB	0
1.2.0.zip	2020-12-18	88.7 MB	0
README.md	2020-12-18	1.8 kB	0
Totals: 3 Items		177.3 MB	0

Added

Support for the IRALab benchmark (https://arxiv.org/abs/2003.12841), with data from the ETH, Canadian Planetary, Kaist and TUM datasets. (thanks @simone-fontana)
Added Kitti for semantic segmentation and registration (first outdoor dataset for semantic seg)
Possibility to load pretrained models by adding the path in the confs for finetuning.
Lottery transform to use randomly selected transforms for data augmentation
Batch size campling function to ensure that batches don't get too large
TorchSparse backend for sparse convolutions
Possibility to build sparse convolution networks with Minkowski Engine or TorchSparse
PVCNN model for semantic segmentation (thanks @CCInc)

Bug fix

Dataset configurations are saved in the checkpoints so that models can be created without requiring the actual dataset
Trainer was giving a warning for models that could not be re created when they actually could
BatchNorm1d fix (thanks @Wundersam)
Fix process hanging when processing scannet with multiprocessing (thanks @zetyquickly)
wandb does not log the weights when set in private mode (thanks @jamesjiro)
Fixed VoteNet loss definitions and data augmentation parameters (got up to 59.2% mAP25)

Changed

More general API for Minkowski with support for Bottleneck blocks and Squeeze and excite.
Docker images tags on dockerhub are now latest-gpu and latest-cpu for the latest CPU adn GPU images.

Removed

Removed VoteNet from the API because it was not up to date. You can still use the models defined there

Source: README.md, updated 2020-12-18

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