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<li class="toctree-l1 current"><a class="current reference internal" href="#">Feature Extraction and Matching</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#feature-extractor-types">Feature Extractor Types</a></li>
<li class="toctree-l2"><a class="reference internal" href="#feature-matcher-types">Feature Matcher Types</a></li>
<li class="toctree-l2"><a class="reference internal" href="#compatible-extractor-and-matcher-types">Compatible Extractor and Matcher Types</a></li>
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  <section id="feature-extraction-and-matching">
<span id="features"></span><h1>Feature Extraction and Matching<a class="headerlink" href="#feature-extraction-and-matching" title="Link to this heading"></a></h1>
<p>COLMAP supports multiple feature extraction and matching algorithms. This page
describes how to switch between them using the command-line interface or the
graphical user interface.</p>
<section id="feature-extractor-types">
<h2>Feature Extractor Types<a class="headerlink" href="#feature-extractor-types" title="Link to this heading"></a></h2>
<p>The following feature extractor types are available:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">SIFT</span></code>: Scale-Invariant Feature Transform (default). The classic and most
widely tested feature extractor. Produces 128-dimensional uint8 descriptors.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">ALIKED</span></code>: A Lighter Keypoint and Descriptor Extractor. A learned feature
extractor that produces floating-point descriptors. Requires ONNX support to
be enabled at build time (<code class="docutils literal notranslate"><span class="pre">-DONNX_ENABLED=ON</span></code>).</p></li>
</ul>
<p>To select a feature extractor type via the command-line:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ colmap feature_extractor \
    --database_path $DATASET_PATH/database.db \
    --image_path $DATASET_PATH/images \
    --FeatureExtraction.type ALIKED_N16ROT \
    --AlikedExtraction.max_num_features 2048
</pre></div>
</div>
<p>For SIFT (the default), you can omit the type or explicitly set it:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ colmap feature_extractor \
    --database_path $DATASET_PATH/database.db \
    --image_path $DATASET_PATH/images \
    --FeatureExtraction.type SIFT \
    --SiftExtraction.max_num_features 8192
</pre></div>
</div>
<p>In the GUI, open <code class="docutils literal notranslate"><span class="pre">Processing</span> <span class="pre">&gt;</span> <span class="pre">Feature</span> <span class="pre">extraction</span></code> and select the desired
tab (SIFT, ALIKED, etc.) before clicking Extract.</p>
</section>
<section id="feature-matcher-types">
<h2>Feature Matcher Types<a class="headerlink" href="#feature-matcher-types" title="Link to this heading"></a></h2>
<p>The following feature matcher types are available:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">SIFT_BRUTEFORCE</span></code>: Brute-force matching optimized for SIFT descriptors
(default). Uses L2 distance with ratio test.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">ALIKED_BRUTEFORCE</span></code>: Brute-force matching for ALIKED descriptors. Uses
cosine similarity. Requires ONNX support to be enabled at build time.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">SIFT_LIGHTGLUE</span></code>: Neural network-based matching using the LightGlue model
for SIFT descriptors. This typically produces more matches and higher inlier
ratios than brute-force matching, especially for challenging image pairs with
large viewpoint or illumination changes. Requires ONNX support to be enabled
at build time.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">ALIKED_LIGHTGLUE</span></code>: Neural network-based matching using the LightGlue model
for ALIKED descriptors. Requires ONNX support to be enabled at build time.</p></li>
</ul>
<p>To select a feature matcher type via the command-line:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ colmap exhaustive_matcher \
    --database_path $DATASET_PATH/database.db \
    --FeatureMatching.type ALIKED_BRUTEFORCE \
    --AlikedMatching.min_cossim 0.85
</pre></div>
</div>
<p>For SIFT matching (the default):</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ colmap exhaustive_matcher \
    --database_path $DATASET_PATH/database.db \
    --FeatureMatching.type SIFT_BRUTEFORCE \
    --SiftMatching.max_ratio 0.8
</pre></div>
</div>
<p>In the GUI, open <code class="docutils literal notranslate"><span class="pre">Processing</span> <span class="pre">&gt;</span> <span class="pre">Feature</span> <span class="pre">matching</span></code>, select any matching tab
(Exhaustive, Sequential, etc.), and choose the matcher type from the “Type”
dropdown in the shared options section.</p>
</section>
<section id="compatible-extractor-and-matcher-types">
<h2>Compatible Extractor and Matcher Types<a class="headerlink" href="#compatible-extractor-and-matcher-types" title="Link to this heading"></a></h2>
<p>The feature extractor and matcher types should be compatible:</p>
<ul class="simple">
<li><p>Use <code class="docutils literal notranslate"><span class="pre">SIFT</span></code> extraction with <code class="docutils literal notranslate"><span class="pre">SIFT_BRUTEFORCE</span></code> or <code class="docutils literal notranslate"><span class="pre">SIFT_LIGHTGLUE</span></code> matching.</p></li>
<li><p>Use <code class="docutils literal notranslate"><span class="pre">ALIKED_*</span></code> extraction with <code class="docutils literal notranslate"><span class="pre">ALIKED_BRUTEFORCE</span></code> or <code class="docutils literal notranslate"><span class="pre">ALIKED_LIGHTGLUE</span></code> matching.</p></li>
</ul>
<p>Mixing incompatible types (e.g., SIFT features with ALIKED matcher) will
result in a runtime error. Do not mix different feature extractor types
(e.g., SIFT and ALIKED) in the same database.</p>
</section>
<section id="aliked-model-variants">
<h2>ALIKED Model Variants<a class="headerlink" href="#aliked-model-variants" title="Link to this heading"></a></h2>
<p>ALIKED requires an ONNX model file. Several model variants are available with
different trade-offs between speed and accuracy:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">aliked-n16rot</span></code>: Faster and trained for some viewpoint invariance. 128-dim descriptors.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">aliked-n32</span></code>: More expensive but not explicitly trained for viewpoint invariance, 128-dim descriptors.</p></li>
</ul>
<p>Specify the model path using <code class="docutils literal notranslate"><span class="pre">--AlikedExtraction.*_model_path</span></code>. If the path is
a URL, COLMAP will automatically download and cache the model. You can download
different ALIKED models from the release page at <a class="reference external" href="https://github.com/colmap/colmap/releases/">https://github.com/colmap/colmap/releases/</a></p>
</section>
</section>


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