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<div class="section" id="torchvision-io">
<h1>torchvision.io<a class="headerlink" href="#torchvision-io" title="Permalink to this headline">¶</a></h1>
<p>The <code class="xref py py-mod docutils literal notranslate"><span class="pre">torchvision.io</span></code> package provides functions for performing IO
operations. They are currently specific to reading and writing video.</p>
<div class="section" id="video">
<h2>Video<a class="headerlink" href="#video" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt id="torchvision.io.read_video">
<code class="sig-prename descclassname">torchvision.io.</code><code class="sig-name descname">read_video</code><span class="sig-paren">(</span><em class="sig-param">filename</em>, <em class="sig-param">start_pts=0</em>, <em class="sig-param">end_pts=None</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torchvision/io/video.html#read_video"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.io.read_video" title="Permalink to this definition">¶</a></dt>
<dd><p>Reads a video from a file, returning both the video frames as well as
the audio frames</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>filename</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – path to the video file</p></li>
<li><p><strong>start_pts</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a><em>, </em><em>optional</em>) – the start presentation time of the video</p></li>
<li><p><strong>end_pts</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a><em>, </em><em>optional</em>) – the end presentation time</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p><ul class="simple">
<li><p><strong>vframes</strong> (<em>Tensor[T, H, W, C]</em>) – the <cite>T</cite> video frames</p></li>
<li><p><strong>aframes</strong> (<em>Tensor[K, L]</em>) – the audio frames, where <cite>K</cite> is the number of channels and <cite>L</cite> is the
number of points</p></li>
<li><p><strong>info</strong> (<em>Dict</em>) – metadata for the video and audio. Can contain the fields video_fps (float)
and audio_fps (int)</p></li>
</ul>
</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="torchvision.io.read_video_timestamps">
<code class="sig-prename descclassname">torchvision.io.</code><code class="sig-name descname">read_video_timestamps</code><span class="sig-paren">(</span><em class="sig-param">filename</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torchvision/io/video.html#read_video_timestamps"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.io.read_video_timestamps" title="Permalink to this definition">¶</a></dt>
<dd><p>List the video frames timestamps.</p>
<p>Note that the function decodes the whole video frame-by-frame.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>filename</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – path to the video file</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p><ul class="simple">
<li><p><strong>pts</strong> (<em>List[int]</em>) – presentation timestamps for each one of the frames in the video.</p></li>
<li><p><strong>video_fps</strong> (<em>int</em>) – the frame rate for the video</p></li>
</ul>
</p>
</dd>
</dl>
</dd></dl>
<dl class="function">
<dt id="torchvision.io.write_video">
<code class="sig-prename descclassname">torchvision.io.</code><code class="sig-name descname">write_video</code><span class="sig-paren">(</span><em class="sig-param">filename</em>, <em class="sig-param">video_array</em>, <em class="sig-param">fps</em>, <em class="sig-param">video_codec='libx264'</em>, <em class="sig-param">options=None</em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/torchvision/io/video.html#write_video"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#torchvision.io.write_video" title="Permalink to this definition">¶</a></dt>
<dd><p>Writes a 4d tensor in [T, H, W, C] format in a video file</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>filename</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – path where the video will be saved</p></li>
<li><p><strong>video_array</strong> (<a class="reference internal" href="../tensors.html#torch.Tensor" title="torch.Tensor"><em>Tensor</em></a><em>[</em><em>T</em><em>, </em><em>H</em><em>, </em><em>W</em><em>, </em><em>C</em><em>]</em>) – tensor containing the individual frames, as a uint8 tensor in [T, H, W, C] format</p></li>
<li><p><strong>fps</strong> (<em>Number</em>) – frames per second</p></li>
</ul>
</dd>
</dl>
</dd></dl>
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