You can either download one of the pre-built binaries or build the source code manually. Executables for Windows and Mac and other resources can be downloaded from Executables for Linux/Unix/BSD are available at Note that the COLMAP packages in the default repositories for Linux/Unix/BSD do not come with CUDA support, which requires manual compilation but is relatively easy on these platforms.

COLMAP can be used as an independent application through the command-line or graphical user interface. Alternatively, COLMAP is also built as a reusable library, i.e., you can include and link COLMAP against your own source code, as described further below.

Pre-built Binaries


For convenience, the pre-built binaries for Windows contain both the graphical and command-line interface executables. To start the COLMAP GUI, you can simply double-click the COLMAP.bat batch script or alternatively run it from the Windows command shell or Powershell. The command-line interface is also accessible through this batch script, which automatically sets the necessary library paths. To list the available COLMAP commands, run COLMAP.bat -h in the command shell cmd.exe or in Powershell.


The pre-built application package for Mac contains both the GUI and command-line version of COLMAP. To open the GUI, simply open the application and note that COLMAP is shipped as an unsigned application, i.e., when your first open the application, you have to right-click the application and select Open and then accept to trust the application. In the future, you can then simply double-click the application to open COLMAP. The command-line interface is accessible by running the packaged binary To list the available COLMAP commands, run -h.

Build from Source

COLMAP builds on all major platforms (Linux, Mac, Windows) with little effort. First, checkout the latest source code:

git clone

On Linux and Mac it is generally recommended to follow the installation instructions below, which use the system package managers to install the required dependencies. Alternatively, there is a Python build script that builds COLMAP and its dependencies locally. This script is useful under Windows and on a (cluster) system if you do not have root access under Linux or Mac.


Recommended dependencies: CUDA (at least version 7.X)

Dependencies from the default Ubuntu repositories:

sudo apt-get install \
    git \
    cmake \
    ninja-build \
    build-essential \
    libboost-program-options-dev \
    libboost-filesystem-dev \
    libboost-graph-dev \
    libboost-system-dev \
    libeigen3-dev \
    libflann-dev \
    libfreeimage-dev \
    libmetis-dev \
    libgoogle-glog-dev \
    libgtest-dev \
    libsqlite3-dev \
    libglew-dev \
    qtbase5-dev \
    libqt5opengl5-dev \
    libcgal-dev \

Configure and compile COLMAP:

git clone
cd colmap
mkdir build
cd build
cmake .. -GNinja
sudo ninja install


colmap -h
colmap gui

To compile with CUDA support, also install Ubuntu’s default CUDA package:

sudo apt-get install -y \
    nvidia-cuda-toolkit \

Or, manually install latest CUDA from NVIDIA’s homepage. During CMake configuration specify CMAKE_CUDA_ARCHITECTURES as “native”, if you want to run COLMAP on your current machine only, “all”/”all-major” to be able to distribute to other machines, or a specific CUDA architecture like “75”, etc.

Under Ubuntu 16.04/18.04, the CMake configuration scripts of CGAL are broken and you must also install the CGAL Qt5 package:

sudo apt-get install libcgal-qt5-dev

Under Ubuntu 22.04, there is a problem when compiling with Ubuntu’s default CUDA package and GCC, and you must compile against GCC 10:

sudo apt-get install gcc-10 g++-10
export CC=/usr/bin/gcc-10
export CXX=/usr/bin/g++-10
export CUDAHOSTCXX=/usr/bin/g++-10
# ... and then run CMake against COLMAP's sources.


Dependencies from Homebrew:

brew install \
    cmake \
    ninja \
    boost \
    eigen \
    flann \
    freeimage \
    metis \
    glog \
    googletest \
    ceres-solver \
    qt5 \
    glew \
    cgal \

Configure and compile COLMAP:

git clone
cd colmap
export PATH="/usr/local/opt/qt@5/bin:$PATH"
mkdir build
cd build
cmake ..  -GNinja -DQt5_DIR=/usr/local/opt/qt/lib/cmake/Qt5
sudo ninja install

If you have Qt 6 installed on your system as well, you might have to temporarily link your Qt 5 installation while configuring CMake:

brew link qt5
cmake configuration (from previous code block)
brew unlink qt5


colmap -h
colmap gui


Recommended dependencies: CUDA (at least version 7.X), Visual Studio 2019

On Windows, the recommended way is to build COLMAP using vcpkg:

git clone
cd vcpkg
.\vcpkg install colmap[cuda,tests]:x64-windows

To compile CUDA for multiple compute architectures, please use:

.\vcpkg install colmap[cuda-redist]:x64-windows

Please refer to the next section for more details.

Visual Studio 2022 has some known compiler bugs that crash when compiling COLMAP’s source code.


COLMAP ships as part of the vcpkg distribution. This enables to conveniently build COLMAP and all of its dependencies from scratch under different platforms. Note that VCPKG requires you to install CUDA manually in the standard way on your platform. To compile COLMAP using VCPKG, you run:

git clone
cd vcpkg
./vcpkg install colmap:x64-linux

VCPKG ships with support for various other platforms (e.g., x64-osx, x64-windows, etc.). To compile with CUDA support and to build all tests:

./vcpkg install colmap[cuda,tests]:x64-linux

The above commands will build the latest release version of COLMAP. To compile the latest commit in the dev branch, you can use the following options:

./vcpkg install colmap:x64-linux --head

To modify the source code, you can further add --editable --no-downloads. Or, if you want to build from another folder and use the dependencies from vcpkg, first run ./vcpkg integrate install and then configure COLMAP as:

cd path/to/colmap
mkdir build
cd build
cmake .. -DCMAKE_TOOLCHAIN_FILE=path/to/vcpkg/scripts/buildsystems/vcpkg.cmake
cmake --build . --config release --target colmap_main --parallel 24


If you want to include and link COLMAP against your own library, the easiest way is to use CMake as a build configuration tool. After configuring the COLMAP build and running ninja/make install, COLMAP automatically installs all headers to ${CMAKE_INSTALL_PREFIX}/include/colmap, all libraries to ${CMAKE_INSTALL_PREFIX}/lib/colmap, and the CMake configuration to ${CMAKE_INSTALL_PREFIX}/share/colmap.

For example, compiling your own source code against COLMAP is as simple as using the following CMakeLists.txt:

cmake_minimum_required(VERSION 3.10)


find_package(colmap REQUIRED)
# or to require a specific version: find_package(colmap 3.4 REQUIRED)

target_link_libraries(hello_world colmap::colmap)

with the source code

#include <cstdlib>
#include <iostream>

#include <colmap/controllers/option_manager.h>
#include <colmap/util/string.h>

int main(int argc, char** argv) {

    std::string message;
    colmap::OptionManager options;
    options.AddRequiredOption("message", &message);
    options.Parse(argc, argv);

    std::cout << colmap::StringPrintf("Hello %s!", message.c_str()) << std::endl;

    return EXIT_SUCCESS;

Then compile and run your code as:

mkdir build
cd build
export colmap_DIR=${CMAKE_INSTALL_PREFIX}/share/colmap
cmake .. -GNinja
./hello_world --message "world"

The sources of this example are stored under doc/sample-project.


If you want to build COLMAP with address sanitizer flags enabled, you need to use a recent compiler with ASan support. For example, you can manually install a recent clang version on your Ubuntu machine and invoke CMake as follows:

CC=/usr/bin/clang CXX=/usr/bin/clang++ cmake .. \

Note that it is generally useful to combine ASan with debug symbols to get meaningful traces for reported issues.


You need Python and Sphinx to build the HTML documentation:

cd path/to/colmap/doc
sudo apt-get install python
pip install sphinx
make html
open _build/html/index.html

Alternatively, you can build the documentation as PDF, EPUB, etc.:

make latexpdf
open _build/pdf/COLMAP.pdf