Awesome

Install Instructions

• Prepare Host System (Ubuntu)

sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt install g++-9
g++-9 --version # Should Print Version 9.4.0 or higher

• Create Conda Environment

./create_env.sh

• Install Pytorch

./install_pytorch_precompiled.sh

• Compile NeAT

conda activate neat

export CONDA=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
export CC=gcc-9
export CXX=g++-9
export CUDAHOSTCXX=g++-9

mkdir build
cd build
cmake -DCMAKE_PREFIX_PATH="${CONDA}/lib/python3.8/site-packages/torch/;${CONDA}" ..
make -j10

Run Instructions

• Get Pepper dataset from here: https://repository.kaust.edu.sa/handle/10754/676019
• Extract datasets
• Update the main() of nikon2neat.cpp to point to the downloaded dataset directory (the output should be into NeAT/scenes)
• Preprocess data using our nikon2neat programm:

mkdir scenes
cd NeAT
export LD_LIBRARY_PATH=~/anaconda3/envs/neat/lib
./build/bin/nikon2neat

• Update configuration file in configs/
• Run reconstruction

cd NeAT
export LD_LIBRARY_PATH=~/anaconda3/envs/neat/lib
./build/bin/reconstruct configs/pepper.ini

• The result will be written to NeAT/Experiments
• Use tensorboard for easy visualization:

conda activate neat
cd NeAT
tensorboard --logdir Experiments/ --samples_per_plugin images=100