diff --git a/_sources/install.rst.txt b/_sources/install.rst.txt index 5d0f951..b988606 100644 --- a/_sources/install.rst.txt +++ b/_sources/install.rst.txt @@ -4,16 +4,17 @@ Installation ============ 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 https://demuc.de/colmap/. Executables for Linux/Unix/BSD are available at -https://repology.org/metapackage/colmap/versions. 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. +manually. Pre-built binaries and other resources can be downloaded from +https://demuc.de/colmap/. An overview of system packages for Linux/Unix/BSD +distributions are available at https://repology.org/metapackage/colmap/versions. +Note that the COLMAP packages in the default repositories for Linux/Unix/BSD do +not come with CUDA support, which requires a manual build from source. 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. +library, i.e., you can include and link COLMAP against your own C++ source code, +as described further below. Furthermore, you can use most of COLMAP's +functionality with :ref:`PyCOLMAP ` in Python. ------------------ Pre-built Binaries @@ -28,13 +29,17 @@ 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 command shell ``cmd.exe`` or in Powershell. The first time you run COLMAP, +Windows defender may prompt you with a security warning, because the binaries +are not officially signed. The provided COLMAP binaries are automatically built +from GitHub Actions CI machines. If you do not trust them, you can build from +source as described below. Mac --- 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 +version of COLMAP. To open the GUI, simply open the application. 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 @@ -52,15 +57,16 @@ First, checkout the latest source code:: git clone https://github.com/colmap/colmap -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. +Under Linux and Mac, it is generally recommended to follow the installation +instructions below, which use the respective system package managers to install +the required dependencies. Alternatively, the instructions for VCPKG can be used +to compile the required dependencies from scratch on more exotic systems with +limited system packages. The VCPKG approach is also the method of choice under +Windows, compute clusters, or if you do not have root access under Linux or Mac. -Linux ------ +Debian/Ubuntu +------------- *Recommended dependencies:* CUDA (at least version 7.X) @@ -89,6 +95,17 @@ Dependencies from the default Ubuntu repositories:: libcgal-dev \ libceres-dev +To compile with **CUDA support**, also install Ubuntu's default CUDA package:: + + sudo apt-get install -y \ + nvidia-cuda-toolkit \ + nvidia-cuda-toolkit-gcc + +Or, manually install the latest CUDA from NVIDIA's homepage. During CMake +configuration, specify `-DCMAKE_CUDA_ARCHITECTURES=native`, if you want to run +COLMAP only on your current machine (default), "all"/"all-major" to be able to +distribute to other machines, or a specific CUDA architecture like "75", etc. + Configure and compile COLMAP:: git clone https://github.com/colmap/colmap.git @@ -104,24 +121,13 @@ Run COLMAP:: colmap -h colmap gui -To compile with **CUDA support**, also install Ubuntu's default CUDA package:: - - sudo apt-get install -y \ - nvidia-cuda-toolkit \ - nvidia-cuda-toolkit-gcc - -Or, manually install the 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 (default), "all"/"all-major" to be able to distribute to other -machines, or a specific CUDA architecture like "75", etc. - Under **Ubuntu 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:: +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 @@ -154,22 +160,17 @@ Configure and compile COLMAP:: git clone https://github.com/colmap/colmap.git cd colmap - export PATH="/usr/local/opt/qt@5/bin:$PATH" mkdir build cd build - cmake .. -GNinja -DQt5_DIR=/usr/local/opt/qt/lib/cmake/Qt5 + cmake .. -GNinja -DCMAKE_PREFIX_PATH="$(brew --prefix qt@5)" ninja sudo ninja install -On Macs with ARM the brew paths are different so you need this - - cmake .. -GNinja -DCMAKE_PREFIX_PATH="/opt/homebrew/opt/flann;/opt/homebrew/opt/metis;/opt/homebrew/opt/suite-sparse;/opt/homebrew/opt/qt@5;/opt/homebrew/opt/freeimage" - 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) + cmake ... (from previous code block) brew unlink qt5 Run COLMAP:: @@ -183,7 +184,7 @@ Windows *Recommended dependencies:* CUDA (at least version 7.X), Visual Studio 2019 -On Windows, the recommended way is to build COLMAP using vcpkg:: +On Windows, the recommended way is to build COLMAP using VCPKG:: git clone https://github.com/microsoft/vcpkg cd vcpkg @@ -200,7 +201,7 @@ Please refer to the next section for more details. VCPKG ----- -COLMAP ships as part of the vcpkg distribution. This enables to conveniently +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:: diff --git a/_sources/pycolmap/index.rst.txt b/_sources/pycolmap/index.rst.txt index eb849a2..73803f2 100644 --- a/_sources/pycolmap/index.rst.txt +++ b/_sources/pycolmap/index.rst.txt @@ -34,11 +34,11 @@ Some features, such as cost functions, require that `PyCeres `_ is installed in the same manner as PyCOLMAP, so either from PyPI or from source. -Usage +API ----- .. toctree:: :maxdepth: 2 - api + pycolmap cost_functions diff --git a/_sources/pycolmap/api.rst.txt b/_sources/pycolmap/pycolmap.rst.txt similarity index 69% rename from _sources/pycolmap/api.rst.txt rename to _sources/pycolmap/pycolmap.rst.txt index 335a90d..7a9ac4a 100644 --- a/_sources/pycolmap/api.rst.txt +++ b/_sources/pycolmap/pycolmap.rst.txt @@ -1,6 +1,6 @@ -.. _pycolmap/api: +.. _pycolmap/pycolmap: -API +pycolmap ============ .. automodule:: pycolmap diff --git a/changelog.html b/changelog.html index 9806fa5..14bfcf5 100644 --- a/changelog.html +++ b/changelog.html @@ -347,7 +347,7 @@

COLMAP 3.9 (01/06/2024)

Add EstimateGeneralizedAbsolutePose by @sarlinpe in https://github.com/colmap/colmap/pull/2174

  • Fix bug in ReconstructionManagerWidget::Update by @whuaegeanse in https://github.com/colmap/colmap/pull/2186

  • Fix missing retrieval dependency by @ahojnnes in https://github.com/colmap/colmap/pull/2189

    • -

  • Removing clustering_options_ and mapper_options_ in Hierarchical Mapper Controller by @Serenitysmk in https://github.com/colmap/colmap/pull/2193

    • +

  • Removing clustering_options and mapper_options in Hierarchical Mapper Controller by @Serenitysmk in https://github.com/colmap/colmap/pull/2193

  • Publish docker image to docker hub by @ahojnnes in https://github.com/colmap/colmap/pull/2195

  • Fix Cuda architecture in docker build by @ahojnnes in https://github.com/colmap/colmap/pull/2196

  • Fix all-major cuda arch missing in CMake < 3.23 by @ahojnnes in https://github.com/colmap/colmap/pull/2197

    • diff --git a/genindex.html b/genindex.html index 3b8a86f..a77672f 100644 --- a/genindex.html +++ b/genindex.html @@ -117,97 +117,99 @@

    Index

    A

    - +
    @@ -215,69 +217,69 @@

    A

    B

    @@ -285,185 +287,189 @@

    B

    C

    + -
    @@ -471,75 +477,77 @@

    C

    D

    @@ -547,115 +555,115 @@

    D

    E

    @@ -663,85 +671,95 @@

    E

    F

    @@ -749,41 +767,49 @@

    F

    G

    @@ -791,65 +817,65 @@

    G

    H

    @@ -857,155 +883,159 @@

    H

    I

    @@ -1013,17 +1043,17 @@

    I

    K

    @@ -1031,55 +1061,55 @@

    K

    L

    @@ -1087,287 +1117,293 @@

    L

    M

    @@ -1376,183 +1412,189 @@

    M

    N

    @@ -1560,31 +1602,31 @@

    N

    O

    @@ -1592,107 +1634,115 @@

    O

    P

    @@ -2048,125 +2104,127 @@

    S

    T

    @@ -2174,29 +2232,31 @@

    T

    U

    @@ -2204,71 +2264,71 @@

    U

    V

    @@ -2276,49 +2336,55 @@

    V

    W

    @@ -2326,11 +2392,11 @@

    W

    X

    diff --git a/install.html b/install.html index 8593372..4092d91 100644 --- a/install.html +++ b/install.html @@ -56,7 +56,7 @@
  • Build from Source
      -
    • Linux
      • +
    • Debian/Ubuntu
    • Mac
    • Windows
    • VCPKG
      • @@ -109,15 +109,16 @@

      Installation

      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 https://demuc.de/colmap/. Executables for Linux/Unix/BSD are available at -https://repology.org/metapackage/colmap/versions. 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.

      +manually. Pre-built binaries and other resources can be downloaded from +https://demuc.de/colmap/. An overview of system packages for Linux/Unix/BSD +distributions are available at https://repology.org/metapackage/colmap/versions. +Note that the COLMAP packages in the default repositories for Linux/Unix/BSD do +not come with CUDA support, which requires a manual build from source.

      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.

      +library, i.e., you can include and link COLMAP against your own C++ source code, +as described further below. Furthermore, you can use most of COLMAP’s +functionality with PyCOLMAP in Python.

      Pre-built Binaries

      @@ -128,12 +129,16 @@

      Windows 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 command shell cmd.exe or in Powershell. The first time you run COLMAP, +Windows defender may prompt you with a security warning, because the binaries +are not officially signed. The provided COLMAP binaries are automatically built +from GitHub Actions CI machines. If you do not trust them, you can build from +source as described below.

      Mac

      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 +version of COLMAP. To open the GUI, simply open the application. 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 @@ -149,13 +154,14 @@

      Build from Source
      git clone https://github.com/colmap/colmap
      -

      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.

      -
      -

      Linux

      +

      Under Linux and Mac, it is generally recommended to follow the installation +instructions below, which use the respective system package managers to install +the required dependencies. Alternatively, the instructions for VCPKG can be used +to compile the required dependencies from scratch on more exotic systems with +limited system packages. The VCPKG approach is also the method of choice under +Windows, compute clusters, or if you do not have root access under Linux or Mac.

      +
      +

      Debian/Ubuntu

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

      Dependencies from the default Ubuntu repositories:

      sudo apt-get install \
@@ -182,6 +188,16 @@ 
      Linuxlibceres-dev
      +

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

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

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

      Configure and compile COLMAP:

      git clone https://github.com/colmap/colmap.git
 cd colmap
@@ -197,23 +213,13 @@ 
      Linuxcolmap gui
      -

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

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

      Or, manually install the 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 (default), “all”/”all-major” to be able to distribute to other -machines, or a specific CUDA architecture like “75”, etc.

      Under Ubuntu 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:

      +

      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
@@ -245,22 +251,17 @@ 
      MacConfigure and compile COLMAP:
      
 
      git clone https://github.com/colmap/colmap.git
 cd colmap
-export PATH="/usr/local/opt/qt@5/bin:$PATH"
 mkdir build
 cd build
-cmake .. -GNinja -DQt5_DIR=/usr/local/opt/qt/lib/cmake/Qt5
+cmake .. -GNinja -DCMAKE_PREFIX_PATH="$(brew --prefix qt@5)"
 ninja
 sudo ninja install
 
      
 
      
-
      On Macs with ARM the brew paths are different so you need this
      
-
      
-
      cmake .. -GNinja -DCMAKE_PREFIX_PATH=”/opt/homebrew/opt/flann;/opt/homebrew/opt/metis;/opt/homebrew/opt/suite-sparse;/opt/homebrew/opt/qt@5;/opt/homebrew/opt/freeimage”
      
-
      
 
      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)
+cmake ... (from previous code block)
 brew unlink qt5
 
      
 
      
@@ -273,7 +274,7 @@ 
      Mac
 
      Windows
      
 
      Recommended dependencies: CUDA (at least version 7.X), Visual Studio 2019
      
-
      On Windows, the recommended way is to build COLMAP using vcpkg:
      
+
      On Windows, the recommended way is to build COLMAP using VCPKG:
      
 
      git clone https://github.com/microsoft/vcpkg
 cd vcpkg
 .\bootstrap-vcpkg.bat
@@ -288,7 +289,7 @@ 
      Windows
 
      
 
      VCPKG
      
-
      COLMAP ships as part of the vcpkg distribution. This enables to conveniently
+
      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:
      
diff --git a/objects.inv b/objects.inv
index 0812067..b1737d2 100644
Binary files a/objects.inv and b/objects.inv differ
diff --git a/py-modindex.html b/py-modindex.html
index cdcabd6..1c3dc9e 100644
--- a/py-modindex.html
+++ b/py-modindex.html
@@ -103,7 +103,7 @@ 
      Python Module Index
      
        
        
-       pycolmap
+       pycolmap
        
      
        
diff --git a/pycolmap/cost_functions.html b/pycolmap/cost_functions.html
index 5005f56..08a5d3f 100644
--- a/pycolmap/cost_functions.html
+++ b/pycolmap/cost_functions.html
@@ -23,7 +23,7 @@
     
     
     
-     
+     
 
 
  
@@ -59,15 +59,16 @@
 
    • Command-line Interface
      • 
 
    • PyCOLMAP
        
 
      • Installation
        • 
-
      • Usage
          
-
        • API
          • 
+
        • API
@@ -108,71 +109,32 @@
              
   
          
 
          Cost Functions
          
-
          
-
          
-pycolmap.cost_functions.AbsolutePoseErrorCost(
-
-
          
-
          cam_from_world: pycolmap.Rigid3d,
          
-
          covariance_cam: numpy.ndarray[numpy.float64[6, 6]],
          
-
          
-
-) → ceres::CostFunction
          
-
          6-DoF error on the absolute pose.
          
-
          
-
-
          
-
          
-pycolmap.cost_functions.MetricRelativePoseErrorCost(
-
-
          
-
          i_from_j: pycolmap.Rigid3d,
          
-
          covariance_j: numpy.ndarray[numpy.float64[6, 6]],
          
-
          
-
-) → ceres::CostFunction
          
-
          6-DoF error between two absolute poses based on their relative pose.
          
-
          
-
-
          
-
          
-pycolmap.cost_functions.Point3dAlignmentCost(
-
-
          
-
          ref_point: numpy.ndarray[numpy.float64[3, 1]],
          
-
          covariance_point: numpy.ndarray[numpy.float64[3, 3]],
          
-
          
-
-) → ceres::CostFunction
          
-
          Error between 3D points transformed by a similarity transform.
          
-
          
-
 
          
 
          
 pycolmap.cost_functions.ReprojErrorCost(*args, **kwargs)
          
 
          Overloaded function.
          
 
            
-
          1. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> ceres::CostFunction
            2. 
+
          2. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error.
          
 
            
-
          1. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> ceres::CostFunction
            2. 
+
          2. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error with 2D detection noise.
          
 
            
-
          1. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, cam_from_world: pycolmap.Rigid3d, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> ceres::CostFunction
            2. 
+
          2. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, cam_from_world: pycolmap.Rigid3d, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error with constant camera pose.
          
 
            
-
          1. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, cam_from_world: pycolmap.Rigid3d, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> ceres::CostFunction
            2. 
+
          2. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, cam_from_world: pycolmap.Rigid3d, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error with constant camera pose and 2D detection noise.
          
 
            
-
          1. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, point2D: numpy.ndarray[numpy.float64[2, 1]], point3D: numpy.ndarray[numpy.float64[3, 1]]) -> ceres::CostFunction
            2. 
+
          2. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, point2D: numpy.ndarray[numpy.float64[2, 1]], point3D: numpy.ndarray[numpy.float64[3, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error with constant 3D point.
          
 
            
-
          1. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, point2D: numpy.ndarray[numpy.float64[2, 1]], point3D: numpy.ndarray[numpy.float64[3, 1]]) -> ceres::CostFunction
            2. 
+
          2. ReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, point2D: numpy.ndarray[numpy.float64[2, 1]], point3D: numpy.ndarray[numpy.float64[3, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error with constant 3D point and 2D detection noise.
          
 
          
@@ -182,19 +144,19 @@
 pycolmap.cost_functions.RigReprojErrorCost(*args, **kwargs)
 
          Overloaded function.
          
 
            
-
          1. RigReprojErrorCost(camera_model_id: pycolmap.CameraModelId, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> ceres::CostFunction
            2. 
+
          2. RigReprojErrorCost(camera_model_id: pycolmap.CameraModelId, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error for camera rig.
          
 
            
-
          1. RigReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> ceres::CostFunction
            2. 
+
          2. RigReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error for camera rig with 2D detection noise.
          
 
            
-
          1. RigReprojErrorCost(camera_model_id: pycolmap.CameraModelId, cam_from_rig: pycolmap.Rigid3d, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> ceres::CostFunction
            2. 
+
          2. RigReprojErrorCost(camera_model_id: pycolmap.CameraModelId, cam_from_rig: pycolmap.Rigid3d, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error for camera rig with constant cam-from-rig pose.
          
 
            
-
          1. RigReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, cam_from_rig: pycolmap.Rigid3d, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> ceres::CostFunction
            2. 
+
          2. RigReprojErrorCost(camera_model_id: pycolmap.CameraModelId, stddev: float, cam_from_rig: pycolmap.Rigid3d, point2D: numpy.ndarray[numpy.float64[2, 1]]) -> pyceres.CostFunction
            3. 
 
          
 
          Reprojection error for camera rig with constant cam-from-rig pose and 2D detection noise.
          
 
          
@@ -208,17 +170,68 @@
 
          point2D2: numpy.ndarray[numpy.float64[2, 1]],
          
 
 
-) → ceres::CostFunction
+) → pyceres.CostFunction
 
          Sampson error for two-view geometry.
          
 
          
 
+
          
+
          
+pycolmap.cost_functions.AbsolutePoseErrorCost(
+
+
          
+
          cam_from_world: pycolmap.Rigid3d,
          
+
          covariance_cam: numpy.ndarray[numpy.float64[6, 6]],
          
+
          
+
+) → pyceres.CostFunction
          
+
          6-DoF error on the absolute pose.
          
+
          
+
+
          
+
          
+pycolmap.cost_functions.MetricRelativePoseErrorCost(
+
+
          
+
          i_from_j: pycolmap.Rigid3d,
          
+
          covariance_j: numpy.ndarray[numpy.float64[6, 6]],
          
+
          
+
+) → pyceres.CostFunction
          
+
          6-DoF error between two absolute poses based on their relative pose.
          
+
          
+
+
          
+
          
+pycolmap.cost_functions.Point3dAlignmentCost(
+
+
          
+
          ref_point: numpy.ndarray[numpy.float64[3, 1]],
          
+
          covariance_point: numpy.ndarray[numpy.float64[3, 3]],
          
+
          
+
+) → pyceres.CostFunction
          
+
          Error between 3D points transformed by a similarity transform.
          
+
          
+
+
          
+
          
+pycolmap.cost_functions.PositionPriorErrorCost(
+
+
          
+
          world_from_cam_position_prior: numpy.ndarray[numpy.float64[3, 1]],
          
+
          covariance: numpy.ndarray[numpy.float64[3, 3]],
          
+
          
+
+) → pyceres.CostFunction
          
+
          
+
 
          
 
 
            
      •
      -
      -

      Usage

      +
      +

      API

        -
      • API @@ -273,7 +274,7 @@

        Usage