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<h1>Contribute<a class="headerlink" href="#contribute" title="Permalink to this headline">¶</a></h1>
<div class="section" id="general-contribution-guidelines">
<h2>General contribution guidelines<a class="headerlink" href="#general-contribution-guidelines" title="Permalink to this headline">¶</a></h2>
<ol class="simple">
<li><p>Fork the repository on <a class="reference external" href="https://github.com/cosanlab/feat">GitHub</a>.</p></li>
<li><p>Install Feat on your machine.</p></li>
<li><p>Install <code class="docutils literal notranslate"><span class="pre">pytest</span></code> with <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">pytest</span></code> then run the tests in the repository with <code class="docutils literal notranslate"><span class="pre">pytest</span></code> or <code class="docutils literal notranslate"><span class="pre">pytest/feat/tests/</span></code>. Confirm that all tests pass on your system. If some tests fail, try to find out why they are failing. Common issues may be not having downloaded model files or missing dependencies.</p></li>
<li><p>Create your feature.</p></li>
<li><p>Add tests to <code class="docutils literal notranslate"><span class="pre">feat/tests/</span></code>.</p></li>
<li><p>Run the tests again with <code class="docutils literal notranslate"><span class="pre">pytest</span> <span class="pre">tests/</span></code> to make sure everything still passes, including your new feature. If you broke something, edit your feature so that it doesn’t break existing code.</p></li>
<li><p>Create a pull request to the main repository’s <code class="docutils literal notranslate"><span class="pre">master</span></code> branch!</p></li>
</ol>
</div>
<div class="section" id="model-contribution-guidelines">
<h2>Model contribution guidelines<a class="headerlink" href="#model-contribution-guidelines" title="Permalink to this headline">¶</a></h2>
<p>There are three key steps to adding a model.</p>
<ol class="simple">
<li><p>Create a folder for the model you are building in the appropriate model type directory.
If you are contributing an Action Unit detection model and calling it <code class="docutils literal notranslate"><span class="pre">mynewmodel</span></code>, create a folder in <code class="docutils literal notranslate"><span class="pre">feat/feat/au_detectors/</span></code>. If it’s an Emotion detection model, add a folder <code class="docutils literal notranslate"><span class="pre">feat/feat/emo_detectors/</span></code>.</p></li>
<li><p>Add your model architecture.
Your model files could contained in a single (e.g. <code class="docutils literal notranslate"><span class="pre">feat/emo_detectors/ResMaskNet/resmasknet_test.py</span></code>) or they could be separated in to a model file (e.g. <code class="docutils literal notranslate"><span class="pre">/au_detectors/JAANet/JAA_model</span></code>) and a test file (e.g. <code class="docutils literal notranslate"><span class="pre">/au_detectors/JAANet/JAA_test</span></code>).</p></li>
<li><p>Your model should be a class that has the appropriate method that the <code class="docutils literal notranslate"><span class="pre">Detector</span></code> can call it.
For example, AU detectors should have the function <code class="docutils literal notranslate"><span class="pre">mynewmodel.detect_au()</span></code> that can be called.</p></li>
<li><p>Add model to list of models in the <code class="docutils literal notranslate"><span class="pre">Detector</span></code> class in <code class="docutils literal notranslate"><span class="pre">feat/detector.py</span></code>.</p></li>
<li><p>Upload your trained model weights to an accessible locations (e.g. Google Drive).</p></li>
<li><p>Add tests to make sure your model is working.</p></li>
<li><p>Create a pull request to the main repository’s <code class="docutils literal notranslate"><span class="pre">master</span></code> branch!</p></li>
</ol>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span>
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