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<h1>torchvision<a class="headerlink" href="#torchvision" title="Permalink to this headline">¶</a></h1>
<p>The <a class="reference internal" href="#module-torchvision" title="torchvision"><code class="xref py py-mod docutils literal notranslate"><span class="pre">torchvision</span></code></a> package consists of popular datasets, model
architectures, and common image transformations for computer vision.</p>
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<span class="target" id="module-torchvision"></span><dl class="function">
<dt id="torchvision.get_image_backend">
<code class="sig-prename descclassname">torchvision.</code><code class="sig-name descname">get_image_backend</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torchvision.html#get_image_backend"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.get_image_backend" title="Permalink to this definition">¶</a></dt>
<dd><p>Gets the name of the package used to load images</p>
</dd></dl>
<dl class="function">
<dt id="torchvision.set_image_backend">
<code class="sig-prename descclassname">torchvision.</code><code class="sig-name descname">set_image_backend</code><span class="sig-paren">(</span><em class="sig-param">backend</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torchvision.html#set_image_backend"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.set_image_backend" title="Permalink to this definition">¶</a></dt>
<dd><p>Specifies the package used to load images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>backend</strong> (<em>string</em>) – Name of the image backend. one of {‘PIL’, ‘accimage’}.
The <code class="xref py py-mod docutils literal notranslate"><span class="pre">accimage</span></code> package uses the Intel IPP library. It is
generally faster than PIL, but does not support as many operations.</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="torchvision.set_video_backend">
<code class="sig-prename descclassname">torchvision.</code><code class="sig-name descname">set_video_backend</code><span class="sig-paren">(</span><em class="sig-param">backend</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torchvision.html#set_video_backend"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.set_video_backend" title="Permalink to this definition">¶</a></dt>
<dd><p>Specifies the package used to decode videos.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>backend</strong> (<em>string</em>) – <p>Name of the video backend. one of {‘pyav’, ‘video_reader’}.
The <code class="xref py py-mod docutils literal notranslate"><span class="pre">pyav</span></code> package uses the 3rd party PyAv library. It is a Pythonic</p>
<blockquote>
<div><p>binding for the FFmpeg libraries.</p>
</div></blockquote>
<dl class="simple">
<dt>The <code class="xref py py-mod docutils literal notranslate"><span class="pre">video_reader</span></code> package includes a native c++ implementation on</dt><dd><p>top of FFMPEG libraries, and a python API of TorchScript custom operator.
It is generally decoding faster than pyav, but perhaps is less robust.</p>
</dd>
</dl>
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