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Dependencies

OpenMVS relies on a number of open source libraries, some optional, which are managed automatically by vcpkg. For details on customizing the build process, see the build instructions.

  • Eigen version 3.4 or higher
  • OpenCV version 2.4 or higher
  • Ceres version 1.10 or higher (optional)
  • CGAL version 4.2 or higher
  • Boost version 1.56 or higher
  • VCG
  • CUDA (optional)
  • GLFW (optional)

Build instructions

Required tools:

  • CMake
  • git
  • C/C++ compiler like Visual Studio 2019, GCC or Clang

The dependencies can be fetched and built automatically using vcpkg on all major platform, by setting the environment variable VCPKG_ROOT to point to its path or by using the cmake parameter -DCMAKE_TOOLCHAIN_FILE=[path to vcpkg]/scripts/buildsystems/vcpkg.cmake.

The latest pre-built stable binaries can be download from here.

#Clone OpenMVS
git clone --recurse-submodules https://github.com/cdcseacave/openMVS.git

#Make build directory:
cd openMVS
mkdir make
cd make

#Run CMake:
cmake ..

#Build:
cmake --build . -j4

#Install OpenMVS library (optional):
cmake --install .

Library usage

In order to use OpenMVS as a third-party library in your project, first compile it as described above or simply use vcpgk:

vcpkg install openmvs

Inside your project CMake script, use:

find_package(OpenMVS)
if(OpenMVS_FOUND)
	include_directories(${OpenMVS_INCLUDE_DIRS})
	add_definitions(${OpenMVS_DEFINITIONS})
endif()

add_executable(your_project source_code.cpp)
target_link_libraries(your_project PRIVATE OpenMVS::MVS)

Python API

The Python API can be enable by setting the OpenMVS_USE_PYTHON option to ON when running cmake. The Python API is built as a shared library and can be used in any Python project. Example:

import pyOpenMVS
    
def run_mvs():
    # set the working folder; all files used next are relative to this folder (optional)
    pyOpenMVS.set_working_folder("folder/containing/the/scene")
    # create an empty scene
    scene = pyOpenMVS.Scene()
    # load a MVS scene from a file
    if not scene.load("scene.mvs"):
        print("ERROR: scene could not be loaded")
        return
    # estimate depth-maps and fuse them into a point-cloud
    if not scene.dense_reconstruction():
        print("ERROR: could not dense reconstruct the scene")
        return
    scene.save_pointcloud("pointcloud.ply")
    # reconstruct a mesh from the point-cloud
    if not scene.reconstruct_mesh():
        print("ERROR: could not reconstruct the mesh for this scene")
        return
    scene.save_mesh("mesh.ply")
    # refine the mesh using gradient descent optimization (optional)
    if not scene.refine_mesh():
        print("ERROR: could not refine the mesh for this scene")
        return
    scene.save_mesh("refined_mesh.ply")
    # texture the mesh using the input images
    if not scene.texture_mesh():
        print("ERROR: could not texture the mesh for this scene")
        return
    scene.save_mesh("textured_mesh.ply")

if __name__ == "__main__":
    run_mvs()