Giter Club home page Giter Club logo

demon's Introduction

Modified by WANG Kaixuan

DeMoN: Depth and Motion Network

License

DeMoN is a ConvNet architecture for solving structure from motion from two views. It estimates the depth and relative camera motion for pairs of images.

Teaser

If you use this code for research please cite:

@InProceedings{UZUMIDB17,
  author       = "B. Ummenhofer and H. Zhou and J. Uhrig and N. Mayer and E. Ilg and A. Dosovitskiy and T. Brox",
  title        = "DeMoN: Depth and Motion Network for Learning Monocular Stereo",
  booktitle    = "IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
  month        = " ",
  year         = "2017",
  url          = "http://lmb.informatik.uni-freiburg.de//Publications/2017/UZUMIDB17"
}

See the project website for the paper and other material.

Requirements

Building and using requires the following libraries and programs

tensorflow 1.0.0
cmake 3.5.1
python 3.5
cuda 8.0.44 (required for gpu support)
VTK 7.1 with python3 interface (required for visualizing point clouds)

The versions match the configuration we have tested on an ubuntu 16.04 system.

There is no binary package available for VTK with python3 interface and therefore it needs to be built from source.

The network also depends on our lmbspecialops library which is included as a submodule.

Build instructions

The following describes how to install tensorflow and demon into a new virtualenv and run the example. We will use pew (pip install pew) to manage a new virtualenv named demon_venv in the following:

# create virtualenv
pew new demon_venv

The following commands all run inside the virtualenv:

# install python module dependencies
pip install tensorflow-gpu # or 'tensorflow' without gpu support
pip install pillow # for reading images
pip install matplotlib # required for visualizing depth maps
# clone repo with submodules
git clone --recursive https://github.com/lmb-freiburg/demon.git

# build lmbspecialops
DEMON_DIR=$PWD/demon
mkdir $DEMON_DIR/lmbspecialops/build
cd $DEMON_DIR/lmbspecialops/build
cmake .. # add '-DBUILD_WITH_CUDA=OFF' to build without gpu support
# (optional) run 'ccmake .' here to adjust settings for gpu code generation
make
pew add $DEMON_DIR/lmbspecialops/python # add to python path

# download weights
cd $DEMON_DIR/weights
./download_weights.sh

# run example
cd $DEMON_DIR/examples
python3 example.py # opens a window with the depth map (and the point cloud if vtk is available)

License

DeMoN is under the GNU General Public License v3.0

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.