hugoledoux / DSOPP

Reimplementation of Direct Sparse Odometry

DSO++

Reimplementation of Direct Sparse Odometry, J. Engel, V. Koltun, D. Cremers, In arXiv:1607.02565, 2016 (https://github.com/JakobEngel/dso)

if used in a publication please consider citing: Upcoming publication

for commercial use and additional functionality contact Roadly ([e-mail])

Building DSOPP

You need to clone this repositor first.

git clone [e-mail]:RoadlyInc/DSOPP.git
cd DSOPP

Dependencies installation

Without Docker [Not recommended]

Note that this is not a recommended way to build this code. Even if you want to extend it and take part in a development process, many modern IDEs give you an opportunity to develp inside a docker contatiner. This section is more of an outline of the build process. If you encounter any problems please open an issue.

Be sure that python3 is installed on your machine.

Using python virtual evironment [recommended]

It is recommended to exploit python virtual environments for each external project not to mess up your system's python dependecies. To install virtualenv package:

pip3 install virtualenv 

To create a virtual environment run the following command

python3 -m venv dsopp_venv

And to activate:

source dsopp_venv/bin/activate

Now depending on your shell settings, you might see (e) dsopp_venv in your terminal line.

Installing python dependencies

From the root of this repository run:

pip3 install -r requirements.txt

system dependencies

If you are on ubuntu or debian system:

apt install cmake libboost-all-dev graphviz doxygen libgl1-mesa-dev libglew-dev 
apt install git-lfs libprotobuf-dev protobuf-compiler libhdf5-dev libfreetype6-dev
apt install libtbb-dev openexr libavcodec-dev libavformat-dev libswscale-dev 
apt install libavutil-dev clang sed gawk clang-10 zlib1g clang-format-10 ninja-build
apt install wget ffmpeg libeigen3-dev libsuitesparse-dev lcov python2

Note: This package names are valid for ubuntu 18.04 and 20.04.

To use clang-format-10 as clang-format add following to your .bashrc file:

alias clang-format='clang-fromat-10'

For installation on other systems, please find the alternative name of each package above in your package manager.

g++-10 compiler

You need to install at least g++-10 compiler. For ubuntu it could be done via:

sudo add-apt-repository ppa:ubuntu-toolchain-r/test -y
sudo apt-get update
sudo apt -y install g++-10

You would need to pass -DCMAKE_CXX_COMPILER=g++-10 to cmake

Recent cmake version

It is recommended ot use one of recent cmake versions. It could be installed via:

wget https://cmake.org/files/v3.17/cmake-3.17.0-Linux-x86_64.tar.gz
tar xvf cmake-3.17.0-Linux-x86_64.tar.gz
cd cmake-3.17.0-Linux-x86_64 
sudo cp -r bin /usr/
sudo cp -r share /usr/
sudo cp -r doc /usr/share/
sudo cp -r man /usr/share/
cd ..
rm -rf cmake*

Note that this would overwrite you system's cmake. As an alternative you can us it directly from untared directory.

Docker [recommended]

Docker is a great way to run a code within specific environment on any machine. To install docker on ubuntu or debian:

sudo apt install docker

After installation docker group should be created and added to user.

sudo groupadd docker
sudo usermod -aG docker $USER

Log out after running the above commands. Now cd to docker/ubuntu/ and run the following command to build an image

docker image build -t dsopp:main --build-arg USER_ID=$(id -u) --build-arg GROUP_ID=$(id -g) .

To connect to dsopp:main image and use gui docker should be added to xhost

xhost local:docker

And following command to open shell inside dsopp:main image in the current directory:

docker run --rm -it -v /tmp/.X11-unix:/tmp/.X11-unix -e HOME=$HOME --net=host -e DISPLAY=$DISPLAY -w $(pwd) -v $HOME:$HOME --device=/dev/dri:/dev/dri -it dsopp:main bash

Build

Using virtualenv or form docker image in root directory of this repo:

mkdir build;
cd build;
cmake .. -DCMAKE_BUILD_TYPE=Release;
make -j;

Remember passing -DCMAKE_CXX_COMPILER=g++-10 to cmake if your default compiler version is less than 10.

Download test data

To run tests test data should be downloaded

navigate to ./test
sh download_test_data.sh

Tests

cd build;
ctest .;

Running on test sequence

To run on synthetic sequence (./test/test_data/track30seconds/)

./build/src/application/dsopp_main

To run on TUMMONO dataset:

naviagate to ./test/test_data/tummono/
sh download_data.sh (sequence id)

navigate to .
./build/src/application/dsopp_main --config_file_path ./test/test_data/tummono/sequence_<id>/<standart/fast/dense>.yaml

dsopp_main outputs track.bin file. This is the whole track output with points and all frame poses. To view it use viewer_main application

./build/src/application/viewer_main track.bin

Running on own dataset

Development notes

Extending DSOPP

DSOPP python utils