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<li class="toctree-l2"><a class="reference internal" href="#module-ipfml.processing">ipfml.processing</a></li>
<li class="toctree-l2"><a class="reference internal" href="#ipfml-filters">ipfml.filters</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#module-ipfml.filters.noise">ipfml.filters.noise</a></li>
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<h1>Documentation<a class="headerlink" href="#documentation" title="Permalink to this headline">¶</a></h1>
<div class="section" id="module-ipfml.metrics">
<span id="ipfml-metrics"></span><h2>ipfml.metrics<a class="headerlink" href="#module-ipfml.metrics" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt id="ipfml.metrics.get_LAB">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_LAB</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_LAB" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms RGB  Image into Lab</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">Lab information</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">Lab</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_LAB</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">Lab</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200, 3)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_LAB_L">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_LAB_L</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_LAB_L" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms RGB Image into Lab and returns L</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">The L chanel from Lab information</td>
</tr>
</tbody>
</table>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">L</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_LAB_L</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">L</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_LAB_a">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_LAB_a</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_LAB_a" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms RGB Image into LAB and returns a</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">The a chanel from Lab information</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_LAB_a</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_LAB_b">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_LAB_b</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_LAB_b" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms RGB Image into LAB and returns b</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">The b chanel from Lab information</td>
</tr>
</tbody>
</table>
<p>Usage :</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">b</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_LAB_b</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">b</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_SVD">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_SVD</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_SVD" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms Image using SVD compression</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert into SVD compression</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">U, s, V obtained from SVD compression</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">U</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">V</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_SVD</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">U</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200, 3)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">len</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
<span class="go">200</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">V</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 3, 3)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_SVD_U">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_SVD_U</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_SVD_U" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms Image into SVD and returns only ‘U’ part</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">U matrix from SVD compression</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">U</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_SVD_U</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">U</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200, 3)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_SVD_V">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_SVD_V</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_SVD_V" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms Image into SVD and returns only ‘V’ part</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">V matrix obtained from SVD compression</td>
</tr>
</tbody>
</table>
<p>Usage :</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">V</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_SVD_V</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">V</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 3, 3)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_SVD_s">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_SVD_s</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_SVD_s" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms Image into SVD and returns only ‘s’ part</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">vector of singular values obtained from SVD compression</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">s</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_SVD_s</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">len</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
<span class="go">200</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_XYZ">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_XYZ</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_XYZ" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms RGB Image into XYZ</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">XYZ information obtained from transformation</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">metrics</span><span class="o">.</span><span class="n">get_XYZ</span><span class="p">(</span><span class="n">img</span><span class="p">)</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200, 3)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_XYZ_X">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_XYZ_X</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_XYZ_X" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms RGB Image into XYZ and returns X</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">The X chanel from XYZ information</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_XYZ_X</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_XYZ_Y">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_XYZ_Y</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_XYZ_Y" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms RGB Image into XYZ and returns Y</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">The Y chanel from XYZ information</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_XYZ_Y</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_XYZ_Z">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_XYZ_Z</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_XYZ_Z" title="Permalink to this definition">¶</a></dt>
<dd><p>Transforms RGB Image into XYZ and returns Z</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – image to convert</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">The Z chanel from XYZ information</td>
</tr>
<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body"><code class="xref py py-exc docutils literal notranslate"><span class="pre">ValueError</span></code> – If <cite>nb_bits</cite> has unexpected value. <cite>nb_bits</cite> needs to be in interval [1, 8].</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">z</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_XYZ_Z</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">z</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_bits_img">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_bits_img</code><span class="sig-paren">(</span><em>image</em>, <em>interval</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_bits_img" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns only bits specified into the interval</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image to convert using this interval of bits value to keep</li>
<li><strong>interval</strong> – (begin, end) of bits values</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">Numpy array with reduced values</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body"><ul class="first last simple">
<li><code class="xref py py-exc docutils literal notranslate"><span class="pre">ValueError</span></code> – If min value from interval is not &gt;= 1.</li>
<li><code class="xref py py-exc docutils literal notranslate"><span class="pre">ValueError</span></code> – If max value from interval is not &lt;= 8.</li>
<li><code class="xref py py-exc docutils literal notranslate"><span class="pre">ValueError</span></code> – If min value from interval &gt;= max value.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">bits_img</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_bits_img</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">bits_img</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200, 3)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.get_low_bits_img">
<code class="descclassname">ipfml.metrics.</code><code class="descname">get_low_bits_img</code><span class="sig-paren">(</span><em>image</em>, <em>nb_bits=4</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.get_low_bits_img" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns Image or Numpy array with data information reduced using only low bits</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image to convert</li>
<li><strong>nb_bits</strong> – optional parameter which indicates the number of bits to keep</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Numpy array with reduced values</p>
</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">low_bits_img</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_low_bits_img</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">low_bits_img</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200, 3)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.metrics.gray_to_mscn">
<code class="descclassname">ipfml.metrics.</code><code class="descname">gray_to_mscn</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.metrics.gray_to_mscn" title="Permalink to this definition">¶</a></dt>
<dd><p>Convert Grayscale Image into Mean Subtracted Contrast Normalized (MSCN)</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – grayscale image</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">MSCN matrix obtained from transformation</td>
</tr>
</tbody>
</table>
<p>Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img_mscn</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">rgb_to_mscn</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img_mscn</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

</div>
<div class="section" id="module-ipfml.processing">
<span id="ipfml-processing"></span><h2>ipfml.processing<a class="headerlink" href="#module-ipfml.processing" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt id="ipfml.processing.divide_in_blocks">
<code class="descclassname">ipfml.processing.</code><code class="descname">divide_in_blocks</code><span class="sig-paren">(</span><em>image</em>, <em>block_size</em>, <em>pil=True</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.divide_in_blocks" title="Permalink to this definition">¶</a></dt>
<dd><p>Divide image into equal size blocks</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – PIL Image or Numpy array</li>
<li><strong>block</strong> – tuple (width, height) representing the size of each dimension of the block</li>
<li><strong>pil</strong> – block type returned (default True)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">list containing all 2D Numpy blocks (in RGB or not)</p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body"><p class="first last"><code class="xref py py-exc docutils literal notranslate"><span class="pre">ValueError</span></code> – If <cite>image_width</cite> or <cite>image_heigt</cite> are not compatible to produce correct block sizes</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">image_values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">255</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="mi">800</span><span class="p">,</span> <span class="mi">800</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">blocks</span> <span class="o">=</span> <span class="n">divide_in_blocks</span><span class="p">(</span><span class="n">image_values</span><span class="p">,</span> <span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">20</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">len</span><span class="p">(</span><span class="n">blocks</span><span class="p">)</span>
<span class="go">1600</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">blocks</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">width</span>
<span class="go">20</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">blocks</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">height</span>
<span class="go">20</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img_l</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">L</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">get_LAB_L</span><span class="p">(</span><span class="n">img_l</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">blocks_L</span> <span class="o">=</span> <span class="n">divide_in_blocks</span><span class="p">(</span><span class="n">L</span><span class="p">,</span> <span class="p">(</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">len</span><span class="p">(</span><span class="n">blocks_L</span><span class="p">)</span>
<span class="go">4</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">blocks_L</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">width</span>
<span class="go">100</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.get_LAB_L_SVD">
<code class="descclassname">ipfml.processing.</code><code class="descname">get_LAB_L_SVD</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.get_LAB_L_SVD" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns Singular values from LAB L Image information</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – PIL Image or Numpy array</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">U, s, V information obtained from SVD compression using Lab</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">U</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">V</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">get_LAB_L_SVD</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">U</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">len</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
<span class="go">200</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">V</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.get_LAB_L_SVD_U">
<code class="descclassname">ipfml.processing.</code><code class="descname">get_LAB_L_SVD_U</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.get_LAB_L_SVD_U" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns U SVD from L of LAB Image information</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – PIL Image or Numpy array</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">U matrix of SVD compression</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">U</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">get_LAB_L_SVD_U</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">U</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.get_LAB_L_SVD_V">
<code class="descclassname">ipfml.processing.</code><code class="descname">get_LAB_L_SVD_V</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.get_LAB_L_SVD_V" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns V SVD from L of LAB Image information</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – PIL Image or Numpy array</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">V matrix of SVD compression</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">V</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">get_LAB_L_SVD_V</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">V</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.get_LAB_L_SVD_s">
<code class="descclassname">ipfml.processing.</code><code class="descname">get_LAB_L_SVD_s</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.get_LAB_L_SVD_s" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns s (Singular values) SVD from L of LAB Image information</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – PIL Image or Numpy array</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">vector of singular values</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">s</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">get_LAB_L_SVD_s</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">len</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
<span class="go">200</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.normalize_2D_arr">
<code class="descclassname">ipfml.processing.</code><code class="descname">normalize_2D_arr</code><span class="sig-paren">(</span><em>arr</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.normalize_2D_arr" title="Permalink to this definition">¶</a></dt>
<dd><p>Return array normalize from its min and max values</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>arr</strong> – 2D Numpy array</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">Normalized 2D Numpy array</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img_mscn</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">rgb_to_mscn</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img_normalized</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">normalize_2D_arr</span><span class="p">(</span><span class="n">img_mscn</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img_normalized</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.normalize_arr">
<code class="descclassname">ipfml.processing.</code><code class="descname">normalize_arr</code><span class="sig-paren">(</span><em>arr</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.normalize_arr" title="Permalink to this definition">¶</a></dt>
<dd><p>Normalize data of 1D array shape</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>arr</strong> – array data of 1D shape</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">Normalized 1D array</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">arr</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">11</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">arr_normalized</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">normalize_arr</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">arr_normalized</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="go">0.1</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.normalize_arr_with_range">
<code class="descclassname">ipfml.processing.</code><code class="descname">normalize_arr_with_range</code><span class="sig-paren">(</span><em>arr</em>, <em>min</em>, <em>max</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.normalize_arr_with_range" title="Permalink to this definition">¶</a></dt>
<dd><p>Normalize data of 1D array shape</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>arr</strong> – array data of 1D shape</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">Normalized 1D Numpy array</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">arr</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">11</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">arr_normalized</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">normalize_arr_with_range</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">20</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">arr_normalized</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="go">0.05</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.rgb_to_LAB_L_bits">
<code class="descclassname">ipfml.processing.</code><code class="descname">rgb_to_LAB_L_bits</code><span class="sig-paren">(</span><em>image</em>, <em>interval</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.rgb_to_LAB_L_bits" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns only bits from LAB L canal specified into the interval</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image to convert using this interval of bits value to keep</li>
<li><strong>interval</strong> – (begin, end) of bits values</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with reduced values</p>
</td>
</tr>
</tbody>
</table>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">bits_Lab_l_img</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">rgb_to_LAB_L_bits</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">6</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">bits_Lab_l_img</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.rgb_to_LAB_L_low_bits">
<code class="descclassname">ipfml.processing.</code><code class="descname">rgb_to_LAB_L_low_bits</code><span class="sig-paren">(</span><em>image</em>, <em>nb_bits=4</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.rgb_to_LAB_L_low_bits" title="Permalink to this definition">¶</a></dt>
<dd><p>Convert RGB Image into Lab L channel image using only 4 low bits values</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – 3D RGB image Numpy array or PIL RGB image</li>
<li><strong>nb_bits</strong> – optional parameter which indicates the number of bits to keep (default 4)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with low bits information kept</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">low_bits_Lab_l_img</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">rgb_to_LAB_L_low_bits</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">low_bits_Lab_l_img</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.rgb_to_grey_low_bits">
<code class="descclassname">ipfml.processing.</code><code class="descname">rgb_to_grey_low_bits</code><span class="sig-paren">(</span><em>image</em>, <em>nb_bits=4</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.rgb_to_grey_low_bits" title="Permalink to this definition">¶</a></dt>
<dd><p>Convert RGB Image into grey image using only 4 low bits values</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – 3D RGB image Numpy array or PIL RGB image</li>
<li><strong>nb_bits</strong> – optional parameter which indicates the number of bits to keep (default 4)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with low bits information kept</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">low_bits_grey_img</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">rgb_to_grey_low_bits</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">low_bits_grey_img</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.processing.rgb_to_mscn">
<code class="descclassname">ipfml.processing.</code><code class="descname">rgb_to_mscn</code><span class="sig-paren">(</span><em>image</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.processing.rgb_to_mscn" title="Permalink to this definition">¶</a></dt>
<dd><p>Convert RGB Image into Mean Subtracted Contrast Normalized (MSCN)</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>image</strong> – 3D RGB image Numpy array or PIL RGB image</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">2D Numpy array with MSCN information</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml</span> <span class="k">import</span> <span class="n">processing</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s1">&#39;./images/test_img.png&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img_mscn</span> <span class="o">=</span> <span class="n">processing</span><span class="o">.</span><span class="n">rgb_to_mscn</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">img_mscn</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(200, 200)</span>
</pre></div>
</div>
</dd></dl>

</div>
<div class="section" id="ipfml-filters">
<h2>ipfml.filters<a class="headerlink" href="#ipfml-filters" title="Permalink to this headline">¶</a></h2>
<div class="section" id="module-ipfml.filters.noise">
<span id="ipfml-filters-noise"></span><h3>ipfml.filters.noise<a class="headerlink" href="#module-ipfml.filters.noise" title="Permalink to this headline">¶</a></h3>
<dl class="function">
<dt id="ipfml.filters.noise.cauchy_noise">
<code class="descclassname">ipfml.filters.noise.</code><code class="descname">cauchy_noise</code><span class="sig-paren">(</span><em>image</em>, <em>n</em>, <em>identical=False</em>, <em>distribution_interval=(0</em>, <em>1)</em>, <em>k=0.0002</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.filters.noise.cauchy_noise" title="Permalink to this definition">¶</a></dt>
<dd><p>Cauchy noise filter to apply on image</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image used as input (2D or 3D image representation)</li>
<li><strong>n</strong> – used to set importance of noise [1, 999]</li>
<li><strong>identical</strong> – keep or not identical noise distribution for each canal if RGB Image (default False)</li>
<li><strong>distribution_interval</strong> – set the distribution interval of normal law distribution (default (0, 1))</li>
<li><strong>k</strong> – variable that specifies the amount of noise to be taken into account in the output image (default 0.0002)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with Cauchy noise applied</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml.filters.noise</span> <span class="k">import</span> <span class="n">cauchy_noise</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="mi">10000</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span> <span class="o">=</span> <span class="n">cauchy_noise</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(100, 100)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.filters.noise.gaussian_noise">
<code class="descclassname">ipfml.filters.noise.</code><code class="descname">gaussian_noise</code><span class="sig-paren">(</span><em>image</em>, <em>n</em>, <em>identical=False</em>, <em>distribution_interval=(0</em>, <em>1)</em>, <em>k=0.1</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.filters.noise.gaussian_noise" title="Permalink to this definition">¶</a></dt>
<dd><p>Gaussian noise filter to apply on image</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image used as input (2D or 3D image representation)</li>
<li><strong>n</strong> – used to set importance of noise [1, 999]</li>
<li><strong>identical</strong> – keep or not identical noise distribution for each canal if RGB Image (default False)</li>
<li><strong>distribution_interval</strong> – set the distribution interval of normal law distribution (default (0, 1))</li>
<li><strong>k</strong> – variable that specifies the amount of noise to be taken into account in the output image (default 0.1)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with gaussian noise applied</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml.filters.noise</span> <span class="k">import</span> <span class="n">gaussian_noise</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="mi">10000</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span> <span class="o">=</span> <span class="n">gaussian_noise</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(100, 100)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.filters.noise.laplace_noise">
<code class="descclassname">ipfml.filters.noise.</code><code class="descname">laplace_noise</code><span class="sig-paren">(</span><em>image</em>, <em>n</em>, <em>identical=False</em>, <em>distribution_interval=(0</em>, <em>1)</em>, <em>k=0.1</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.filters.noise.laplace_noise" title="Permalink to this definition">¶</a></dt>
<dd><p>Laplace noise filter to apply on image</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image used as input (2D or 3D image representation)</li>
<li><strong>n</strong> – used to set importance of noise [1, 999]</li>
<li><strong>identical</strong> – keep or not identical noise distribution for each canal if RGB Image (default False)</li>
<li><strong>distribution_interval</strong> – set the distribution interval of normal law distribution (default (0, 1))</li>
<li><strong>k</strong> – variable that specifies the amount of noise to be taken into account in the output image (default 0.1)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpay array with Laplace noise applied</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml.filters.noise</span> <span class="k">import</span> <span class="n">laplace_noise</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="mi">10000</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span> <span class="o">=</span> <span class="n">laplace_noise</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(100, 100)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.filters.noise.log_normal_noise">
<code class="descclassname">ipfml.filters.noise.</code><code class="descname">log_normal_noise</code><span class="sig-paren">(</span><em>image</em>, <em>n</em>, <em>identical=False</em>, <em>distribution_interval=(0</em>, <em>1)</em>, <em>k=0.05</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.filters.noise.log_normal_noise" title="Permalink to this definition">¶</a></dt>
<dd><p>Log-normal noise filter to apply on image</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image used as input (2D or 3D image representation)</li>
<li><strong>n</strong> – used to set importance of noise [1, 999]</li>
<li><strong>identical</strong> – keep or not identical noise distribution for each canal if RGB Image (default False)</li>
<li><strong>distribution_interval</strong> – set the distribution interval of normal law distribution (default (0, 1))</li>
<li><strong>k</strong> – variable that specifies the amount of noise to be taken into account in the output image (default 0.05)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with Log-normal noise applied</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml.filters.noise</span> <span class="k">import</span> <span class="n">log_normal_noise</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="mi">10000</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span> <span class="o">=</span> <span class="n">log_normal_noise</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(100, 100)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.filters.noise.mut_white_noise">
<code class="descclassname">ipfml.filters.noise.</code><code class="descname">mut_white_noise</code><span class="sig-paren">(</span><em>image</em>, <em>n</em>, <em>identical=False</em>, <em>distribution_interval=(0</em>, <em>1)</em>, <em>k=0.002</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.filters.noise.mut_white_noise" title="Permalink to this definition">¶</a></dt>
<dd><p>Multiplied White noise filter to apply on image</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image used as input (2D or 3D image representation)</li>
<li><strong>n</strong> – used to set importance of noise [1, 999]</li>
<li><strong>identical</strong> – keep or not identical noise distribution for each canal if RGB Image (default False)</li>
<li><strong>distribution_interval</strong> – set the distribution interval of normal law distribution (default (-0.5, 0.5))</li>
<li><strong>k</strong> – variable that specifies the amount of noise to be taken into account in the output image (default 0.002)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with multiplied white noise applied</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml.filters.noise</span> <span class="k">import</span> <span class="n">mut_white_noise</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="mi">10000</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span> <span class="o">=</span> <span class="n">mut_white_noise</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(100, 100)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.filters.noise.salt_pepper_noise">
<code class="descclassname">ipfml.filters.noise.</code><code class="descname">salt_pepper_noise</code><span class="sig-paren">(</span><em>image</em>, <em>n</em>, <em>identical=False</em>, <em>p=0.1</em>, <em>k=0.5</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.filters.noise.salt_pepper_noise" title="Permalink to this definition">¶</a></dt>
<dd><p>Pepper salt noise filter to apply on image</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image used as input (2D or 3D image representation)</li>
<li><strong>n</strong> – used to set importance of noise [1, 999]</li>
<li><strong>identical</strong> – keep or not identical noise distribution for each canal if RGB Image (default False)</li>
<li><strong>p</strong> – probability to increase pixel value otherwise decrease it</li>
<li><strong>k</strong> – variable that specifies the amount of noise to be taken into account in the output image (default 0.5)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with salt and pepper noise applied</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml.filters.noise</span> <span class="k">import</span> <span class="n">salt_pepper_noise</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="mi">10000</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span> <span class="o">=</span> <span class="n">salt_pepper_noise</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(100, 100)</span>
</pre></div>
</div>
</dd></dl>

<dl class="function">
<dt id="ipfml.filters.noise.white_noise">
<code class="descclassname">ipfml.filters.noise.</code><code class="descname">white_noise</code><span class="sig-paren">(</span><em>image</em>, <em>n</em>, <em>identical=False</em>, <em>distribution_interval=(-0.5</em>, <em>0.5)</em>, <em>k=0.2</em><span class="sig-paren">)</span><a class="headerlink" href="#ipfml.filters.noise.white_noise" title="Permalink to this definition">¶</a></dt>
<dd><p>White noise filter to apply on image</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>image</strong> – image used as input (2D or 3D image representation)</li>
<li><strong>n</strong> – used to set importance of noise [1, 999]</li>
<li><strong>identical</strong> – keep or not identical noise distribution for each canal if RGB Image (default False)</li>
<li><strong>distribution_interval</strong> – set the distribution interval of normal law distribution (default (-0.5, 0.5))</li>
<li><strong>k</strong> – variable that specifies the amount of noise to be taken into account in the output image (default 0.2)</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">2D Numpy array with white noise applied</p>
</td>
</tr>
</tbody>
</table>
<p>Example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">ipfml.filters.noise</span> <span class="k">import</span> <span class="n">white_noise</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="mi">10000</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span> <span class="o">=</span> <span class="n">white_noise</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">noisy_image</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(100, 100)</span>
</pre></div>
</div>
</dd></dl>

</div>
</div>
</div>


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