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<!DOCTYPE html>
<htmllang="en" data-content_root="./" data-theme="auto">
<head>
<metacharset="utf-8" />
<metaname="viewport" content="width=device-width, initial-scale=1.0" /><metaname="viewport" content="width=device-width, initial-scale=1" />
<metaproperty="og:title" content="Database Format" />
<metaproperty="og:type" content="website" />
<metaproperty="og:url" content="https://colmap.github.io/database.html" />
<metaproperty="og:site_name" content="COLMAP" />
<metaproperty="og:description" content="COLMAP stores all extracted information in a single SQLite database file. The database can be accessed with the database management toolkit in the COLMAP GUI, the provided C++ database API (see src..." />
<metaproperty="og:image" content="https://colmap.github.io/_static/og-image.png" />
<metaproperty="og:image:alt" content="COLMAP — Structure-from-Motion & Multi-View Stereo" />
<metaname="description" content="COLMAP stores all extracted information in a single SQLite database file. The database can be accessed with the database management toolkit in the COLMAP GUI, the provided C++ database API (see src..." />
<metaname="twitter:card" content="summary_large_image" />
<title>Database Format — COLMAP</title>
<scriptdata-cfasync="false">
document.documentElement.dataset.mode=localStorage.getItem("mode")||"auto";
document.documentElement.dataset.theme=localStorage.getItem("theme")||"auto";
</script>
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this give us a css class that will be invisible only if js is disabled
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<style>
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<linkhref="_static/styles/theme.css?digest=90905a2f556bf617f1a9" rel="stylesheet" />
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<scriptsrc="_static/design-tabs.js?v=f930bc37"></script>
<script>DOCUMENTATION_OPTIONS.pagename='database';</script>
<script>DOCUMENTATION_OPTIONS.search_as_you_type=false;</script>
<scriptsrc="_static/install_selector.js?v=af4a3e9b"></script>
<scriptsrc="_static/external_links.js?v=cd4e6f29"></script>
<linkrel="canonical" href="https://colmap.github.io/database.html" />
<linkrel="icon" href="_static/favicon.svg"/>
<linkrel="index" title="Index" href="genindex.html" />
<linkrel="search" title="Search" href="search.html" />
<linkrel="next" title="Camera Models" href="cameras.html" />
<linkrel="prev" title="Feature Extraction and Matching" href="features.html" />
<metaname="viewport" content="width=device-width, initial-scale=1"/>
<metaname="docsearch:language" content="en"/>
<metaname="docsearch:version" content="4.2.0.dev0 | 77da2b8 (2026-08-18)" />
<scriptsrc="_static/searchtools.js"></script>
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</head>
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<iclass="fa-solid fa-arrow-up"></i>Back to top</button>
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<formclass="bd-search d-flex align-items-center"
action="search.html"
method="get">
<iclass="fa-solid fa-magnifying-glass"></i>
<inputtype="search"
class="form-control"
name="q"
placeholder="Search the docs ..."
aria-label="Search the docs ..."
autocomplete="off"
autocorrect="off"
autocapitalize="off"
spellcheck="false"/>
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<aclass="navbar-brand logo" href="index.html">
<imgsrc="_static/colmap-logo.svg" class="logo__image only-light" alt=""/>
<imgsrc="_static/colmap-logo-dark.svg" class="logo__image only-dark pst-js-only" alt=""/>
<pclass="title logo__title">COLMAP</p>
</a></div>
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<nav>
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<aclass="nav-link nav-internal" href="install.html">
Installation
</a>
</li>
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Tutorial
</a>
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Key Concepts
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3D Viewer
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Feature Extraction and Matching
</a>
</li>
<liclass=" current active">
<aclass="nav-link dropdown-item nav-internal" href="#">
Database Format
</a>
</li>
<liclass="">
<aclass="nav-link dropdown-item nav-internal" href="cameras.html">
Camera Models
</a>
</li>
<liclass="">
<aclass="nav-link dropdown-item nav-internal" href="rigs.html">
Rig Support
</a>
</li>
<liclass="">
<aclass="nav-link dropdown-item nav-internal" href="format.html">
Output Format
</a>
</li>
<liclass="">
<aclass="nav-link dropdown-item nav-internal" href="datasets.html">
Datasets
</a>
</li>
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</a>
</li>
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<aclass="nav-link dropdown-item nav-internal" href="cli.html">
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</a>
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<aclass="nav-link dropdown-item nav-internal" href="pycolmap/index.html">
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</a>
</li>
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</a>
</li>
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<aclass="nav-link dropdown-item nav-internal" href="bibliography.html">
Bibliography
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<spanclass="search-button__kbd-shortcut"><kbdclass="kbd-shortcut__modifier">Ctrl</kbd>+<kbdclass="kbd-shortcut__modifier">K</kbd></span>
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Key Concepts
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3D Viewer
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Feature Extraction and Matching
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Database Format
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Camera Models
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Rig Support
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Output Format
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Datasets
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PyCOLMAP
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<sectionid="database-format">
<spanid="id1"></span><h1>Database Format<aclass="headerlink" href="#database-format" title="Link to this heading">#</a></h1>
<p>COLMAP stores all extracted information in a single SQLite database file. The
database can be accessed with the database management toolkit in the COLMAP GUI,
the provided C++ database API (see <codeclass="docutils literal notranslate"><spanclass="pre">src/colmap/scene/database.h</span></code>), or using
Python with pycolmap.</p>
<p>The database contains the following tables:</p>
<ulclass="simple">
<li><p>rigs</p></li>
<li><p>cameras</p></li>
<li><p>frames</p></li>
<li><p>images</p></li>
<li><p>keypoints</p></li>
<li><p>descriptors</p></li>
<li><p>matches</p></li>
<li><p>two_view_geometries</p></li>
</ul>
<p>To initialize an empty SQLite database file with the required schema, you can
either create a new project in the GUI or run the <codeclass="docutils literal notranslate"><spanclass="pre">colmap</span><spanclass="pre">database_creator</span></code> command.</p>
<sectionid="rigs-and-sensors">
<h2>Rigs and Sensors<aclass="headerlink" href="#rigs-and-sensors" title="Link to this heading">#</a></h2>
<p>The relation between rigs and sensors (cameras, etc.) is 1-to-N with one sensor
being chosen as the reference sensor to define the origin of the rig. Each sensor
must only be part of one rig.</p>
</section>
<sectionid="rigs-and-frames">
<h2>Rigs and Frames<aclass="headerlink" href="#rigs-and-frames" title="Link to this heading">#</a></h2>
<p>The relation between rigs and frames is 1-to-N, where a frame defines a specific
instance of the rig with all or a subset of sensors exposed at the same time.</p>
</section>
<sectionid="cameras-and-images">
<h2>Cameras and Images<aclass="headerlink" href="#cameras-and-images" title="Link to this heading">#</a></h2>
<p>The relation between cameras and images is 1-to-N. This has important
implications for Structure-from-Motion, since one camera shares the same
intrinsic parameters (focal length, principal point, distortion, etc.), while
every image has separate extrinsic parameters (orientation and location).</p>
<p>The intrinsic parameters of cameras are stored as contiguous binary blobs in
<codeclass="docutils literal notranslate"><spanclass="pre">float64</span></code>, ordered as specified in <codeclass="docutils literal notranslate"><spanclass="pre">src/colmap/sensor/models.h</span></code>. COLMAP only
uses cameras that are referenced by images, all other cameras are ignored.</p>
<p>The <codeclass="docutils literal notranslate"><spanclass="pre">name</span></code> column in the images table is the unique relative path in the image
folder. As such, the database file and image folder can be moved to different
locations, as long as the relative folder structure is preserved.</p>
<p>When manually inserting images and cameras into the database, make sure
that all identifiers are positive and non-zero, i.e. <codeclass="docutils literal notranslate"><spanclass="pre">image_id</span><spanclass="pre">></span><spanclass="pre">0</span></code>
and <codeclass="docutils literal notranslate"><spanclass="pre">camera_id</span><spanclass="pre">></span><spanclass="pre">0</span></code>.</p>
</section>
<sectionid="keypoints-and-descriptors">
<h2>Keypoints and Descriptors<aclass="headerlink" href="#keypoints-and-descriptors" title="Link to this heading">#</a></h2>
<p>The detected keypoints are stored as row-major <codeclass="docutils literal notranslate"><spanclass="pre">float32</span></code> binary blobs, where the
first two columns are the X and Y locations in the image, respectively. COLMAP
uses the convention that the upper left image corner has coordinate <codeclass="docutils literal notranslate"><spanclass="pre">(0,</span><spanclass="pre">0)</span></code> and
the center of the upper left most pixel has coordinate <codeclass="docutils literal notranslate"><spanclass="pre">(0.5,</span><spanclass="pre">0.5)</span></code>. If the
keypoints have 4 columns, then the feature geometry is a similarity and the
third column is the scale and the fourth column the orientation of the feature
(according to SIFT conventions). If the keypoints have 6 columns, then the
feature geometry is an affinity and the last 4 columns encode its affine shape
(see <codeclass="docutils literal notranslate"><spanclass="pre">src/colmap/feature/types.h</span></code> for details).</p>
<p>The extracted descriptors are stored as row-major binary blobs, where each row
describes the feature appearance of the corresponding entry in the keypoints
table. The data type and dimensionality depend on the feature extractor:</p>
<ulclass="simple">
<li><p><strong>SIFT</strong>: <codeclass="docutils literal notranslate"><spanclass="pre">uint8</span></code> descriptors with 128 dimensions (128 bytes per feature).</p></li>
<li><p><strong>ALIKED</strong>: <codeclass="docutils literal notranslate"><spanclass="pre">float32</span></code> descriptors with 128 dimensions (512 bytes per feature).</p></li>
<li><p><strong>LOMA_B</strong>: <codeclass="docutils literal notranslate"><spanclass="pre">float32</span></code> descriptors with 256 dimensions (1024 bytes per
feature).</p></li>
<li><p><strong>LOMA_B128</strong>: <codeclass="docutils literal notranslate"><spanclass="pre">float32</span></code> descriptors with 128 dimensions (512 bytes per
feature).</p></li>
</ul>
<p>The <codeclass="docutils literal notranslate"><spanclass="pre">cols</span></code> column in the descriptors table specifies the number of bytes per
descriptor row. For <codeclass="docutils literal notranslate"><spanclass="pre">uint8</span></code> descriptors, this equals the descriptor dimension.
For <codeclass="docutils literal notranslate"><spanclass="pre">float32</span></code> descriptors, this equals <codeclass="docutils literal notranslate"><spanclass="pre">4</span><spanclass="pre">*</span><spanclass="pre">dimension</span></code>.</p>
<p>In both tables, the <codeclass="docutils literal notranslate"><spanclass="pre">rows</span></code> table specifies the number of detected features per
image, while <codeclass="docutils literal notranslate"><spanclass="pre">rows=0</span></code> means that an image has no features. For feature matching
and geometric verification, every image must have a corresponding keypoints and
descriptors entry. Note that only vocabulary tree matching with fast spatial
verification requires meaningful values for the local feature geometry, i.e.,
only X and Y must be provided and the other keypoint columns can be set to zero.
The rest of the reconstruction pipeline only uses the keypoint locations.</p>
</section>
<sectionid="matches-and-two-view-geometries">
<h2>Matches and two-view geometries<aclass="headerlink" href="#matches-and-two-view-geometries" title="Link to this heading">#</a></h2>
<p>Feature matching stores its output in the <codeclass="docutils literal notranslate"><spanclass="pre">matches</span></code> table and geometric
verification in the <codeclass="docutils literal notranslate"><spanclass="pre">two_view_geometries</span></code> table. COLMAP only uses the data in
<codeclass="docutils literal notranslate"><spanclass="pre">two_view_geometries</span></code> for reconstruction. Every entry in the two tables stores
the feature matches between two unique images, where the <codeclass="docutils literal notranslate"><spanclass="pre">pair_id</span></code> is the
row-major, linear index in the upper-triangular match matrix, generated as
follows:</p>
<divclass="highlight-default notranslate"><divclass="highlight"><pre><span></span><spanclass="k">def</span><spanclass="w"></span><spanclass="nf">image_ids_to_pair_id</span><spanclass="p">(</span><spanclass="n">image_id1</span><spanclass="p">,</span><spanclass="n">image_id2</span><spanclass="p">):</span>
<spanclass="k">if</span><spanclass="n">image_id1</span><spanclass="o">></span><spanclass="n">image_id2</span><spanclass="p">:</span>
<spanclass="k">return</span><spanclass="mi">2147483647</span><spanclass="o">*</span><spanclass="n">image_id2</span><spanclass="o">+</span><spanclass="n">image_id1</span>
<spanclass="k">else</span><spanclass="p">:</span>
<spanclass="k">return</span><spanclass="mi">2147483647</span><spanclass="o">*</span><spanclass="n">image_id1</span><spanclass="o">+</span><spanclass="n">image_id2</span>
</pre></div>
</div>
<p>and image identifiers can be uniquely determined from the <codeclass="docutils literal notranslate"><spanclass="pre">pair_id</span></code> as:</p>
<divclass="highlight-default notranslate"><divclass="highlight"><pre><span></span><spanclass="k">def</span><spanclass="w"></span><spanclass="nf">pair_id_to_image_ids</span><spanclass="p">(</span><spanclass="n">pair_id</span><spanclass="p">):</span>
<spanclass="n">image_id2</span><spanclass="o">=</span><spanclass="n">pair_id</span><spanclass="o">%</span><spanclass="mi">2147483647</span>
<spanclass="n">image_id1</span><spanclass="o">=</span><spanclass="p">(</span><spanclass="n">pair_id</span><spanclass="o">-</span><spanclass="n">image_id2</span><spanclass="p">)</span><spanclass="o">/</span><spanclass="mi">2147483647</span>
<spanclass="k">return</span><spanclass="n">image_id1</span><spanclass="p">,</span><spanclass="n">image_id2</span>
</pre></div>
</div>
<p>The <codeclass="docutils literal notranslate"><spanclass="pre">pair_id</span></code> enables efficient database queries, as the matches tables may
contain several hundred millions of entries. This scheme limits the maximum
number of images in a database to 2147483647 (maximum value of signed 32-bit
integers), i.e. <codeclass="docutils literal notranslate"><spanclass="pre">image_id</span></code> must be smaller than 2147483647.</p>
<p>The binary blobs in the matches tables are row-major <codeclass="docutils literal notranslate"><spanclass="pre">uint32</span></code> matrices, where
the left column are zero-based indices into the features of <codeclass="docutils literal notranslate"><spanclass="pre">image_id1</span></code> and the
second column into the features of <codeclass="docutils literal notranslate"><spanclass="pre">image_id2</span></code>. The column <codeclass="docutils literal notranslate"><spanclass="pre">cols</span></code> must be 2 and
the <codeclass="docutils literal notranslate"><spanclass="pre">rows</span></code> column specifies the number of feature matches.</p>
<p>The F, E, H blobs in the <codeclass="docutils literal notranslate"><spanclass="pre">two_view_geometries</span></code> table are stored as 3x3 matrices
in row-major <codeclass="docutils literal notranslate"><spanclass="pre">float64</span></code> format. The meaning of the <codeclass="docutils literal notranslate"><spanclass="pre">config</span></code> values are documented
in the <codeclass="docutils literal notranslate"><spanclass="pre">src/colmap/estimators/two_view_geometry.h</span></code> source file.</p>
</section>
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