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INSTALL.md

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Installation

This is the suggested way to install the dependencies on Ubuntu 14.04+:

  • NVIDIA CUDA 7.0+
  • NVIDIA cuDNN v4
  • Torch

Requirements

  • NVIDIA GPU with compute capability 3.5 or above

Install CUDA

  1. Install the build-essential package:
sudo apt-get install build-essential
  1. If you are using a Virtual Machine (like Amazon EC2 instances), install:
sudo apt-get update
sudo apt-get install linux-generic

  1. Download the CUDA .deb file for Linux Ubuntu 14.04 64-bit from: https://developer.nvidia.com/cuda-downloads. The file will be named something like cuda-repo-ubuntu1404-7-5-local_7.5-18_amd64.deb

  2. Install CUDA from the .deb file:

sudo dpkg -i cuda-repo-ubuntu1404-7-5-local_7.5-18_amd64.deb
sudo apt-get update
sudo apt-get install cuda
echo "export PATH=/usr/local/cuda/bin/:\$PATH; export LD_LIBRARY_PATH=/usr/local/cuda/lib64/:\$LD_LIBRARY_PATH; " >>~/.bashrc && source ~/.bashrc
  1. Restart your computer

Install cuDNN v4

  1. Download cuDNN v4 from https://developer.nvidia.com/cuDNN (requires registration). The file will be named something like cudnn-7.0-linux-x64-v4.0-rc.tgz.

  2. Extract the file to /usr/local/cuda:

tar -xvf cudnn-7.0-linux-x64-v4.0-rc.tgz
sudo cp cuda/include/*.h /usr/local/cuda/include
sudo cp cuda/lib64/*.so* /usr/local/cuda/lib64

Install Torch

  1. Install the Torch dependencies:
curl -sk https://raw.githubusercontent.com/torch/ezinstall/master/install-deps | bash -e
  1. Install Torch in a local folder:
git clone https://github.com/torch/distro.git ~/torch --recursive
cd ~/torch; ./install.sh

If you want to uninstall torch, you can use the command: rm -rf ~/torch

Install the Torch cuDNN v4 bindings

git clone -b R4 https://github.com/soumith/cudnn.torch.git
cd cudnn.torch; luarocks make

Install the HDF5 Libraries

sudo apt-get update
sudo apt-get install -y libhdf5-serial-dev hdf5-tools
git clone https://github.com/davek44/torch-hdf5.git
cd torch-hdf5
luarocks make

Download our NYU-Depth-V2 and KITTI datasets

The RGB and depth images have been properly preprocessed (including synchronization and projection of depths to RGB image planes) for both NYU-Depth-V2 and KITTI datasets. They are stored in HDF5 formats, with each file containing one RGB-depth image pair. This might take an hour or so.

cd data
wget http://datasets.lids.mit.edu/sparse-to-dense/data/kitti.tar.gz
tar -xvf kitti.tar.gz && rm -f kitti.tar.gz
wget http://datasets.lids.mit.edu/sparse-to-dense/data/nyudepthv2.tar.gz 
tar -xvf nyudepthv2.tar.gz && rm -f nyudepthv2.tar.gz 
cd ..

Download Sparse-to-Depth

git clone https://github.com/fangchangma/sparse-to-dense.git
cd sparse-to-dense