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lib fix #3, update readme on scannet split Oct 16, 2019
models scannet preprocessing Oct 11, 2019
scripts Training scannet, script Oct 11, 2019
.gitignore init Oct 1, 2019
.style.yapf init Oct 1, 2019
README.md fix #3, update readme on scannet split Oct 16, 2019
config.py scannet preprocessing Oct 11, 2019
main.py Training scannet, script Oct 11, 2019
requirements.txt init Oct 1, 2019

README.md

Spatio-Temporal Segmentation

This repository contains the accompanying code for 4D-SpatioTemporal ConvNets: Minkowski Convolutional Neural Networks, CVPR'19.

ScanNet Training

  1. First, preprocess all scannet raw point cloud with the following command after you set the path correctly.
python -m lib.datasets.prepreocessing.scannet
  1. Download the v2 official splits from https://github.com/ScanNet/ScanNet/tree/master/Tasks/Benchmark and save them to the scannet preprocessed root directory.

  2. Create scannetv2_trainval.txt by concatenating scannetv2_train.txt and scannetv2_val.txt.

  3. Train the scannet network with

export BATCH_SIZE=N; ./scripts/train_scannet.sh 0 -default "--scannet_path /path/to/preprocessed/scannet"

The first argument is the GPU id and the second argument is the path postfix and the last argument is the miscellaneous arguments.

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