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<!DOCTYPE html>


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<meta property="og:description" content="The command-line interface provides access to all of COLMAP’s functionality for automated scripting. Each core functionality is implemented as a command to the colmap executable. Run colmap -h to l..." />
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<meta property="og:image:alt" content="COLMAP — Structure-from-Motion & Multi-View Stereo" />
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  <section id="command-line-interface">
<span id="cli"></span><h1>Command-line Interface<a class="headerlink" href="#command-line-interface" title="Link to this heading">#</a></h1>
<p>The command-line interface provides access to all of COLMAP’s functionality for
automated scripting. Each core functionality is implemented as a command to the
<code class="docutils literal notranslate"><span class="pre">colmap</span></code> executable. Run <code class="docutils literal notranslate"><span class="pre">colmap</span> <span class="pre">-h</span></code> to list the available commands (or
<code class="docutils literal notranslate"><span class="pre">COLMAP.bat</span> <span class="pre">-h</span></code> under Windows). Note that if you run COLMAP from the CMake
build folder, the executable is located at <code class="docutils literal notranslate"><span class="pre">./src/colmap/exe/colmap</span></code>. To start the
graphical user interface, run <code class="docutils literal notranslate"><span class="pre">colmap</span> <span class="pre">gui</span></code>.</p>
<section id="example">
<h2>Example<a class="headerlink" href="#example" title="Link to this heading">#</a></h2>
<p>Assuming you stored the images of your project in the following structure:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>/path/to/project/...
+── images
│   +── image1.jpg
│   +── image2.jpg
│   +── ...
│   +── imageN.jpg
</pre></div>
</div>
<p>The command for the automatic reconstruction tool would be:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span># The project folder must contain a folder "images" with all the images.
$ DATASET_PATH=/path/to/project

$ colmap automatic_reconstructor \
    --workspace_path $DATASET_PATH \
    --image_path $DATASET_PATH/images
</pre></div>
</div>
<p>Note that any command lists all available options using the <code class="docutils literal notranslate"><span class="pre">-h,--help</span></code>
command-line argument. In case you need more control over the individual
parameters of the reconstruction process, you can execute the following sequence
of commands as an alternative to the automatic reconstruction command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span># The project folder must contain a folder "images" with all the images.
$ DATASET_PATH=/path/to/dataset

$ colmap feature_extractor \
   --database_path $DATASET_PATH/database.db \
   --image_path $DATASET_PATH/images

# Optionally replace intrinsics with learned single-view
# calibration (AnyCalib) before matching and geometric verification.
$ colmap single_view_calibrator \
   --database_path $DATASET_PATH/database.db \
   --image_path $DATASET_PATH/images

$ colmap exhaustive_matcher \
   --database_path $DATASET_PATH/database.db

$ mkdir -p $DATASET_PATH/sparse

$ colmap mapper \
    --database_path $DATASET_PATH/database.db \
    --image_path $DATASET_PATH/images \
    --output_path $DATASET_PATH/sparse

$ mkdir -p $DATASET_PATH/dense

$ colmap image_undistorter \
    --image_path $DATASET_PATH/images \
    --input_path $DATASET_PATH/sparse/0 \
    --output_path $DATASET_PATH/dense \
    --output_type COLMAP \
    --max_image_size 2000

$ colmap patch_match_stereo \
    --workspace_path $DATASET_PATH/dense \
    --workspace_format COLMAP \
    --PatchMatchStereo.geom_consistency true

$ colmap stereo_fusion \
    --workspace_path $DATASET_PATH/dense \
    --workspace_format COLMAP \
    --input_type geometric \
    --output_path $DATASET_PATH/dense/fused.ply

$ colmap poisson_mesher \
    --input_path $DATASET_PATH/dense/fused.ply \
    --output_path $DATASET_PATH/dense/meshed-poisson.ply

$ colmap delaunay_mesher \
    --input_path $DATASET_PATH/dense \
    --output_path $DATASET_PATH/dense/meshed-delaunay.ply

$ colmap advancing_front_mesher \
    --input_path $DATASET_PATH/dense \
    --output_path $DATASET_PATH/dense/meshed-advancing-front.ply

# Optionally simplify a dense mesh to reduce its size.
$ colmap mesh_simplifier \
    --input_path $DATASET_PATH/dense/meshed-poisson.ply \
    --output_path $DATASET_PATH/dense/meshed-poisson-simplified.ply \
    --MeshSimplification.target_face_ratio 0.25

# Optionally texture a mesh using the undistorted images.
$ colmap mesh_texturer \
    --workspace_path $DATASET_PATH/dense \
    --input_path $DATASET_PATH/dense/meshed-poisson.ply \
    --output_path $DATASET_PATH/dense/textured
</pre></div>
</div>
</section>
<section id="graceful-shutdown-and-resuming">
<h2>Graceful shutdown and resuming<a class="headerlink" href="#graceful-shutdown-and-resuming" title="Link to this heading">#</a></h2>
<p>The feature extraction and matching commands, <code class="docutils literal notranslate"><span class="pre">mapper</span></code>,
<code class="docutils literal notranslate"><span class="pre">pose_prior_mapper</span></code>, <code class="docutils literal notranslate"><span class="pre">bundle_adjuster</span></code>, <code class="docutils literal notranslate"><span class="pre">point_triangulator</span></code>,
<code class="docutils literal notranslate"><span class="pre">image_registrator</span></code>, <code class="docutils literal notranslate"><span class="pre">single_view_calibrator</span></code>, the image undistortion commands,
<code class="docutils literal notranslate"><span class="pre">patch_match_stereo</span></code>, and <code class="docutils literal notranslate"><span class="pre">stereo_fusion</span></code> handle <code class="docutils literal notranslate"><span class="pre">SIGINT</span></code> and <code class="docutils literal notranslate"><span class="pre">SIGTERM</span></code>
cooperatively. <code class="docutils literal notranslate"><span class="pre">automatic_reconstructor</span></code> supports graceful shutdown when
using the incremental mapper. The first signal stops work at a safe point and
writes any usable in-progress results. The process then exits with status 130
for <code class="docutils literal notranslate"><span class="pre">SIGINT</span></code> or 143 for <code class="docutils literal notranslate"><span class="pre">SIGTERM</span></code>. A second signal terminates immediately
and may interrupt an output write.</p>
<p>Feature extraction and matching can be resumed by rerunning the same command
against the same database. PatchMatch can likewise be rerun against the same
workspace; complete depth and normal maps are skipped. An interrupted
incremental reconstruction is written to its normal numbered model directory
and can be continued with <code class="docutils literal notranslate"><span class="pre">--input_path</span></code>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ colmap mapper \
    --database_path $DATASET_PATH/database.db \
    --image_path $DATASET_PATH/images \
    --input_path $DATASET_PATH/sparse/0 \
    --output_path $DATASET_PATH/sparse/0
</pre></div>
</div>
<p>Point triangulation, image registration, and bundle adjustment write their
usable partial results before exiting. Stereo fusion writes non-empty partial
results to a sibling path containing <code class="docutils literal notranslate"><span class="pre">.partial</span></code> so that an existing completed
result is not overwritten. Interrupted image undistortion can be restarted by
rerunning the same command. Ceres optimizations stop between iterations. The
Caspar bundle-adjustment backend can only stop after its current solver
invocation. The global mapper does not support graceful shutdown because its
intermediate reconstructions cannot currently be resumed.</p>
<p>The equivalent pycolmap functions automatically handle <code class="docutils literal notranslate"><span class="pre">SIGINT</span></code> (Ctrl-C) by
performing a graceful shutdown and raising <code class="docutils literal notranslate"><span class="pre">KeyboardInterrupt</span></code>. For other
termination events, they accept an optional <code class="docutils literal notranslate"><span class="pre">cancellation_token</span></code>. Explicit
cancellation finishes cleanup and then raises <code class="docutils literal notranslate"><span class="pre">InterruptedError</span></code>. This allows
applications to connect cloud-preemption signals (like <code class="docutils literal notranslate"><span class="pre">SIGTERM</span></code>) to the token
without pycolmap replacing the host application’s signal handlers. Automatic
<code class="docutils literal notranslate"><span class="pre">SIGINT</span></code> handling requires calling the pycolmap function from Python’s main
thread; use a cancellation token when calling it from another thread:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">signal</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">pycolmap</span>

<span class="n">token</span> <span class="o">=</span> <span class="n">pycolmap</span><span class="o">.</span><span class="n">CancellationToken</span><span class="p">()</span>
<span class="n">signal</span><span class="o">.</span><span class="n">signal</span><span class="p">(</span><span class="n">signal</span><span class="o">.</span><span class="n">SIGTERM</span><span class="p">,</span> <span class="k">lambda</span> <span class="o">*</span><span class="n">_</span><span class="p">:</span> <span class="n">token</span><span class="o">.</span><span class="n">cancel</span><span class="p">())</span>
<span class="n">pycolmap</span><span class="o">.</span><span class="n">incremental_mapping</span><span class="p">(</span>
    <span class="n">database_path</span><span class="p">,</span>
    <span class="n">image_path</span><span class="p">,</span>
    <span class="n">output_path</span><span class="p">,</span>
    <span class="n">cancellation_token</span><span class="o">=</span><span class="n">token</span><span class="p">,</span>
<span class="p">)</span>
</pre></div>
</div>
<p>To use the global SfM pipeline instead of the incremental mapper, replace the
<code class="docutils literal notranslate"><span class="pre">mapper</span></code> step with <code class="docutils literal notranslate"><span class="pre">global_mapper</span></code>. The global mapper depends on good focal
length priors, so if reliable intrinsics are not available (e.g., from EXIF or
lab calibration), you should run <code class="docutils literal notranslate"><span class="pre">view_graph_calibrator</span></code> first. This step is
optional but recommended to improve the quality of global SfM, as was always
the default in <a class="reference external" href="https://github.com/colmap/glomap">GLOMAP</a>. Alternatively,
<code class="docutils literal notranslate"><span class="pre">single_view_calibrator</span></code> can provide learned intrinsics from the images alone
before matching. Note that <code class="docutils literal notranslate"><span class="pre">view_graph_calibrator</span></code> modifies camera
intrinsics and two-view geometries in the database in-place, so it is
recommended to work on a copy of the database:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ colmap feature_extractor \
   --database_path $DATASET_PATH/database.db \
   --image_path $DATASET_PATH/images

$ colmap exhaustive_matcher \
   --database_path $DATASET_PATH/database.db

# Optional but often needed: calibrate intrinsics from the view graph.
# This modifies the database in-place, so work on a copy.
$ cp $DATASET_PATH/database.db $DATASET_PATH/database_global.db
$ colmap view_graph_calibrator \
    --database_path $DATASET_PATH/database_global.db

$ mkdir -p $DATASET_PATH/sparse

$ colmap global_mapper \
    --database_path $DATASET_PATH/database_global.db \
    --image_path $DATASET_PATH/images \
    --output_path $DATASET_PATH/sparse
</pre></div>
</div>
<p>If you want to run COLMAP on a computer without an attached display (e.g.,
cluster or cloud service), COLMAP automatically switches to use CUDA if
supported by your system. If no CUDA enabled device is available, you can
manually select to use CPU-based feature extraction and matching by setting the
<code class="docutils literal notranslate"><span class="pre">--FeatureExtraction.use_gpu</span> <span class="pre">0</span></code> and <code class="docutils literal notranslate"><span class="pre">--FeatureMatching.use_gpu</span> <span class="pre">0</span></code> options.</p>
</section>
<section id="help">
<h2>Help<a class="headerlink" href="#help" title="Link to this heading">#</a></h2>
<p>The available commands can be listed using the command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ colmap help

    Usage:
      colmap [command] [options]

    Documentation:
      https://colmap.github.io/

    Example usage:
      colmap help [ -h, --help ]
      colmap gui
      colmap gui -h [ --help ]
      colmap automatic_reconstructor -h [ --help ]
      colmap automatic_reconstructor --image_path IMAGES --workspace_path WORKSPACE
      colmap feature_extractor --image_path IMAGES --database_path DATABASE
      colmap exhaustive_matcher --database_path DATABASE
      colmap mapper --image_path IMAGES --database_path DATABASE --output_path MODEL
      ...

    Available commands:
      help
      gui
      automatic_reconstructor
      bundle_adjuster
      single_view_calibrator
      color_extractor
      database_cleaner
      database_creator
      database_merger
      delaunay_mesher
      exhaustive_matcher
      feature_extractor
      feature_importer
      geometric_verifier
      global_mapper
      guided_geometric_verifier
      hierarchical_mapper
      image_deleter
      image_filterer
      image_rectifier
      image_registrator
      image_undistorter
      image_undistorter_standalone
      mapper
      matches_importer
      mesh_simplifier
      mesh_texturer
      model_aligner
      model_analyzer
      model_clusterer
      model_comparer
      model_converter
      model_cropper
      model_merger
      model_orientation_aligner
      model_splitter
      model_transformer
      patch_match_stereo
      point_filtering
      point_triangulator
      pose_prior_mapper
      poisson_mesher
      project_generator
      rig_configurator
      rotation_averager
      sequential_matcher
      spatial_matcher
      stereo_fusion
      transitive_matcher
      view_graph_calibrator
      vocab_tree_builder
      vocab_tree_matcher
      vocab_tree_retriever
</pre></div>
</div>
<p>And each command has a <code class="docutils literal notranslate"><span class="pre">-h,--help</span></code> command-line argument to show the usage and
the available options, e.g.:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ colmap feature_extractor -h

    Options can either be specified via command-line or by defining
    them in a .ini project file passed to ``--project_path``.

        -h [ --help ]
        --default_random_seed arg (=0)
        --log_target arg (=stderr_and_file)   {stderr, stdout, file, stderr_and_file}
        --log_path arg
        --log_level arg (=0)
        --log_severity arg (=0)               {INFO = 0, WARNING = 1, ERROR = 2, FATAL = 3}
        --log_color arg (=1)
        --project_path arg
        --database_path arg
        --image_path arg
        --camera_mode arg (=-1)
        --image_list_path arg
        --descriptor_normalization arg (=L1_ROOT)
                                              {L1_ROOT, L2}
        --ImageReader.mask_path arg
        --ImageReader.camera_model arg (=SIMPLE_RADIAL)
                                              {SIMPLE_PINHOLE, PINHOLE, SIMPLE_RADIAL, RADIAL, OPENCV, OPENCV_FISHEYE,
                                              FULL_OPENCV, FOV, SIMPLE_RADIAL_FISHEYE, RADIAL_FISHEYE, THIN_PRISM_FISHEYE,
                                              RAD_TAN_THIN_PRISM_FISHEYE, SIMPLE_DIVISION, DIVISION, SIMPLE_FISHEYE, FISHEYE,
                                              EUCM, EQUIRECTANGULAR, SKEWED_PINHOLE}
        --ImageReader.single_camera arg (=0)
        --ImageReader.single_camera_per_folder arg (=0)
        --ImageReader.single_camera_per_image arg (=0)
        --ImageReader.existing_camera_id arg (=-1)
        --ImageReader.camera_params arg
        --ImageReader.default_focal_length_factor arg (=1.2)
        --ImageReader.camera_mask_path arg
        --FeatureExtraction.type arg (=SIFT)  {SIFT, ALIKED_N16ROT, ALIKED_N32, LOMA_B, LOMA_B128}
        --FeatureExtraction.max_image_size arg (=3200)
        --FeatureExtraction.num_threads arg (=-1)
        --FeatureExtraction.use_gpu arg (=1)
        --FeatureExtraction.gpu_index arg (=-1)
        --SiftExtraction.max_num_features arg (=8192)
        --SiftExtraction.first_octave arg (=-1)
        --SiftExtraction.num_octaves arg (=4)
        --SiftExtraction.octave_resolution arg (=3)
        --SiftExtraction.peak_threshold arg (=0.0066666666666666671)
        --SiftExtraction.edge_threshold arg (=10)
        --SiftExtraction.estimate_affine_shape arg (=0)
        --SiftExtraction.max_num_orientations arg (=2)
        --SiftExtraction.upright arg (=0)