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compLIB/lib/Vision.html
Konstantin Lampalzer 16a3609f9f Update documentation
2022-01-09 18:41:17 +01:00

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<li class="toctree-l1 current"><a class="current reference internal" href="#">Vision</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#opencv-stream">Opencv Stream</a></li>
<li class="toctree-l2"><a class="reference internal" href="#examples">Examples</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#using-the-vision-module">Using the Vision Module</a></li>
<li class="toctree-l3"><a class="reference internal" href="#chessboard-detection">Chessboard Detection</a></li>
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<div class="section" id="vision">
<span id="lib-vision"></span><h1>Vision<a class="headerlink" href="#vision" title="Permalink to this headline"></a></h1>
<p>This module provides an interface for grabbing an rtmp stream and using the images to do some processing in opencv.</p>
<p>How do I use this module?</p>
<ol class="arabic simple">
<li><p>Get frames from the raspberry pi camera</p></li>
<li><p>– here comes your own processing –</p></li>
<li><p>Publish the processed frames on an http server</p></li>
<li><p>You can view the http stream of your processed images in a web browser</p></li>
</ol>
<div class="section" id="opencv-stream">
<h2>Opencv Stream<a class="headerlink" href="#opencv-stream" title="Permalink to this headline"></a></h2>
<p>Because of the rtmp stream needing to buffer some frames and waiting for P-Frames, importing this module might take up
to 5 Seconds.</p>
<dl class="py class">
<dt id="compLib.Vision.__Streaming">
<em class="property">class </em><code class="sig-prename descclassname">compLib.Vision.</code><code class="sig-name descname">__Streaming</code><a class="headerlink" href="#compLib.Vision.__Streaming" title="Permalink to this definition"></a></dt>
<dd><p>Class that handles rtmp streaming for opencv.</p>
<p>DO NOT CREATE AN INSTANCE OF THIS CLASS YOURSELF!</p>
<p>This is automatically done when importing this module. Use Vision.Streaming which is
an instance of this class!</p>
<p>grab frames -&gt; do your own processing -&gt; publish frame -&gt; view on http server</p>
<dl class="py method">
<dt id="compLib.Vision.__Streaming.get_frame">
<code class="sig-name descname">get_frame</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#compLib.Vision.__Streaming.get_frame" title="Permalink to this definition"></a></dt>
<dd><p>Grab the newest frame from the rtmp stream.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>An opencv frame</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="compLib.Vision.__Streaming.publish_frame">
<code class="sig-name descname">publish_frame</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">image</span></em><span class="sig-paren">)</span><a class="headerlink" href="#compLib.Vision.__Streaming.publish_frame" title="Permalink to this definition"></a></dt>
<dd><p>Publish an opencv frame to the http webserver.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>image</strong> – Opencv frame that will be published</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>None</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="examples">
<h2>Examples<a class="headerlink" href="#examples" title="Permalink to this headline"></a></h2>
<div class="section" id="using-the-vision-module">
<h3>Using the Vision Module<a class="headerlink" href="#using-the-vision-module" title="Permalink to this headline"></a></h3>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">cv2</span>
<span class="kn">from</span> <span class="nn">compLib</span> <span class="kn">import</span> <span class="n">Vision</span>
<span class="k">while</span> <span class="kc">True</span><span class="p">:</span>
<span class="c1"># get newest opencv frame from camera</span>
<span class="n">frame</span> <span class="o">=</span> <span class="n">Vision</span><span class="o">.</span><span class="n">Streaming</span><span class="o">.</span><span class="n">get_frame</span><span class="p">()</span>
<span class="c1"># do some processing with the frame.....</span>
<span class="c1"># publish frame to streaming server</span>
<span class="n">Vision</span><span class="o">.</span><span class="n">Streaming</span><span class="o">.</span><span class="n">publish_frame</span><span class="p">(</span><span class="n">frame</span><span class="p">)</span>
</pre></div>
</div>
<p>Connect the raspberry pi to your internet and view the stream at: “<a class="reference external" href="http://your_raspi_ip:9898/">http://your_raspi_ip:9898/</a>”. This should display
your raspberry pi camera. Note: the stream will lag a little bit BUT the processing of the image will be done in
realtime.</p>
<p>The output on the website should show whatever your raspberry pi cam records:</p>
<a class="reference internal image-reference" href="../_images/opencv_http_stream.png"><img alt="Processed frames from opencv" src="../_images/opencv_http_stream.png" style="width: 680px;" /></a>
</div>
<div class="section" id="chessboard-detection">
<h3>Chessboard Detection<a class="headerlink" href="#chessboard-detection" title="Permalink to this headline"></a></h3>
<p>In this example we process the captured stream of images and want to detect chessboards. Run this example and
point your raspberry pi camera to a chessboard and it should be detected.</p>
<p>For testing you can point it at this image:</p>
<a class="reference internal image-reference" href="../_images/chessboard.jpg"><img alt="Chessboard for opencv processing" src="../_images/chessboard.jpg" style="width: 680px;" /></a>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">cv2</span>
<span class="kn">from</span> <span class="nn">compLib</span> <span class="kn">import</span> <span class="n">Vision</span>
<span class="k">while</span> <span class="kc">True</span><span class="p">:</span>
<span class="c1"># get newest opencv frame from camera</span>
<span class="n">frame</span> <span class="o">=</span> <span class="n">Vision</span><span class="o">.</span><span class="n">Streaming</span><span class="o">.</span><span class="n">get_frame</span><span class="p">()</span>
<span class="n">criteria</span> <span class="o">=</span> <span class="p">(</span><span class="n">cv2</span><span class="o">.</span><span class="n">TERM_CRITERIA_EPS</span> <span class="o">+</span> <span class="n">cv2</span><span class="o">.</span><span class="n">TERM_CRITERIA_MAX_ITER</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">)</span>
<span class="c1"># convert image to grayscale image</span>
<span class="n">gray</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">cvtColor</span><span class="p">(</span><span class="n">frame</span><span class="p">,</span> <span class="n">cv2</span><span class="o">.</span><span class="n">COLOR_BGR2GRAY</span><span class="p">)</span>
<span class="c1"># find the chessboard corners</span>
<span class="n">ret</span><span class="p">,</span> <span class="n">corners</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">findChessboardCorners</span><span class="p">(</span><span class="n">gray</span><span class="p">,</span> <span class="p">(</span><span class="mi">6</span><span class="p">,</span> <span class="mi">9</span><span class="p">),</span> <span class="kc">None</span><span class="p">)</span>
<span class="c1"># draw detected chessboard position onto the image</span>
<span class="n">cv2</span><span class="o">.</span><span class="n">drawChessboardCorners</span><span class="p">(</span><span class="n">frame</span><span class="p">,</span> <span class="p">(</span><span class="mi">6</span><span class="p">,</span> <span class="mi">9</span><span class="p">),</span> <span class="n">corners</span><span class="p">,</span> <span class="n">ret</span><span class="p">)</span>
<span class="c1"># publish frame to streaming server</span>
<span class="n">Vision</span><span class="o">.</span><span class="n">Streaming</span><span class="o">.</span><span class="n">publish_frame</span><span class="p">(</span><span class="n">frame</span><span class="p">)</span>
</pre></div>
</div>
<p>Connect the raspberry pi to your internet and view the stream at: “<a class="reference external" href="http://your_raspi_ip:9898/">http://your_raspi_ip:9898/</a>”.</p>
<p>The output image should look like this:</p>
<a class="reference internal image-reference" href="../_images/chessboard_detected.jpg"><img alt="Processed frames from opencv" src="../_images/chessboard_detected.jpg" style="width: 680px;" /></a>
<p>Here is a screenshot of the stream website while viewing the chessboard in this documentation.</p>
<a class="reference internal image-reference" href="../_images/opencv_processed.png"><img alt="Processed frames from opencv" src="../_images/opencv_processed.png" style="width: 680px;" /></a>
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