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flownet3d_pytorch

The pytorch implementation of flownet3d based on WangYueFt/dcp, sshaoshuai/Pointnet2.PyTorch and yanx27/Pointnet_Pointnet2_pytorch

Installation

Requirements

PyTorch>=1.0: https://pytorch.org

scipy>=1.2

numpy

h5py

tqdm

Install

Install this library by running the following command:

cd lib
python setup.py install
cd ../

Training

The processed Flyingthings3d data is provided here for download (total size ~11GB).

Then run the following command to train:

python flying_things_main.py --exp_name=flownet3d --dataset_path=xx/yy

where xx/yy is the dataset path

Attacking the model

python flying_things_main.py --exp_name=flownet3d --dataset_path=data/data_processed_maxcut_35_20k_2k_8192 --model_path=pretrained_model/model.best.t7

Performance comparison

All of the following experiments were tested on a TITAN RTX

  1. GPU memory usage:
batch size flownet3d(GB) flownet3d_pytorch(GB)
16 16.9 9.1
  1. Training time per epoch on Flyingthings3d dataset:
batch size flownet3d(min) flownet3d_pytorch(min)
16 6.7 3.4

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