Google Git
Sign in
apache / spark-website / e70e5c0adf47fbb67f89c252db397607e9f77225 / . / site / docs / 3.1.1 / api / python / _modules / pyspark / ml / image.html
blob: 302e7ba864709e5592dd7fe0f186853d86217eee [file] [log] [blame]
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<title>pyspark.ml.image &#8212; PySpark 3.1.1 documentation</title>
<link rel="stylesheet" href="../../../_static/css/index.73d71520a4ca3b99cfee5594769eaaae.css">
<link rel="stylesheet"
href="../../../_static/vendor/fontawesome/5.13.0/css/all.min.css">
<link rel="preload" as="font" type="font/woff2" crossorigin
href="../../../_static/vendor/fontawesome/5.13.0/webfonts/fa-solid-900.woff2">
<link rel="preload" as="font" type="font/woff2" crossorigin
href="../../../_static/vendor/fontawesome/5.13.0/webfonts/fa-brands-400.woff2">
<link rel="stylesheet"
href="../../../_static/vendor/open-sans_all/1.44.1/index.css">
<link rel="stylesheet"
href="../../../_static/vendor/lato_latin-ext/1.44.1/index.css">
<link rel="stylesheet" href="../../../_static/basic.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<link rel="stylesheet" type="text/css" href="../../../_static/css/pyspark.css" />
<link rel="preload" as="script" href="../../../_static/js/index.3da636dd464baa7582d2.js">
<script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
<script src="../../../_static/underscore.js"></script>
<script src="../../../_static/doctools.js"></script>
<script src="../../../_static/language_data.js"></script>
<script src="../../../_static/copybutton.js"></script>
<script crossorigin="anonymous" integrity="sha256-Ae2Vz/4ePdIu6ZyI/5ZGsYnb+m0JlOmKPjt6XZ9JJkA=" src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js"></script>
<script async="async" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/latest.js?config=TeX-AMS-MML_HTMLorMML"></script>
<script type="text/x-mathjax-config">MathJax.Hub.Config({"tex2jax": {"inlineMath": [["$", "$"], ["\\(", "\\)"]], "processEscapes": true, "ignoreClass": "document", "processClass": "math|output_area"}})</script>
<link rel="canonical" href="https://spark.apache.org/docs/latest/api/python/_modules/pyspark/ml/image.html" />
<link rel="search" title="Search" href="../../../search.html" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<meta name="docsearch:language" content="en" />
<!-- Matomo -->
<script type="text/javascript">
var _paq = window._paq = window._paq || [];
/* tracker methods like "setCustomDimension" should be called before "trackPageView" */
_paq.push(["disableCookies"]);
_paq.push(['trackPageView']);
_paq.push(['enableLinkTracking']);
(function() {
var u="https://analytics.apache.org/";
_paq.push(['setTrackerUrl', u+'matomo.php']);
_paq.push(['setSiteId', '40']);
var d=document, g=d.createElement('script'), s=d.getElementsByTagName('script')[0];
g.async=true; g.src=u+'matomo.js'; s.parentNode.insertBefore(g,s);
})();
</script>
<!-- End Matomo Code -->
</head>
<body data-spy="scroll" data-target="#bd-toc-nav" data-offset="80">
<nav class="navbar navbar-light navbar-expand-lg bg-light fixed-top bd-navbar" id="navbar-main">
<div class="container-xl">
<a class="navbar-brand" href="../../../index.html">
<img src="../../../_static/spark-logo-reverse.png" class="logo" alt="logo" />
</a>
<button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbar-menu" aria-controls="navbar-menu" aria-expanded="false" aria-label="Toggle navigation">
<span class="navbar-toggler-icon"></span>
</button>
<div id="navbar-menu" class="col-lg-9 collapse navbar-collapse">
<ul id="navbar-main-elements" class="navbar-nav mr-auto">
<li class="nav-item ">
<a class="nav-link" href="../../../getting_started/index.html">Getting Started</a>
</li>
<li class="nav-item ">
<a class="nav-link" href="../../../user_guide/index.html">User Guide</a>
</li>
<li class="nav-item ">
<a class="nav-link" href="../../../reference/index.html">API Reference</a>
</li>
<li class="nav-item ">
<a class="nav-link" href="../../../development/index.html">Development</a>
</li>
<li class="nav-item ">
<a class="nav-link" href="../../../migration_guide/index.html">Migration Guide</a>
</li>
</ul>
<ul class="navbar-nav">
</ul>
</div>
</div>
</nav>
<div class="container-xl">
<div class="row">
<div class="col-12 col-md-3 bd-sidebar"><form class="bd-search d-flex align-items-center" action="../../../search.html" method="get">
<i class="icon fas fa-search"></i>
<input type="search" class="form-control" name="q" id="search-input" placeholder="Search the docs ..." aria-label="Search the docs ..." autocomplete="off" >
</form>
<nav class="bd-links" id="bd-docs-nav" aria-label="Main navigation">
<div class="bd-toc-item active">
<ul class="nav bd-sidenav">
</ul>
</nav>
</div>
<div class="d-none d-xl-block col-xl-2 bd-toc">
<nav id="bd-toc-nav">
<ul class="nav section-nav flex-column">
</ul>
</nav>
</div>
<main class="col-12 col-md-9 col-xl-7 py-md-5 pl-md-5 pr-md-4 bd-content" role="main">
<div>
<h1>Source code for pyspark.ml.image</h1><div class="highlight"><pre>
<span></span><span class="c1">#</span>
<span class="c1"># Licensed to the Apache Software Foundation (ASF) under one or more</span>
<span class="c1"># contributor license agreements. See the NOTICE file distributed with</span>
<span class="c1"># this work for additional information regarding copyright ownership.</span>
<span class="c1"># The ASF licenses this file to You under the Apache License, Version 2.0</span>
<span class="c1"># (the &quot;License&quot;); you may not use this file except in compliance with</span>
<span class="c1"># the License. You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1"># Unless required by applicable law or agreed to in writing, software</span>
<span class="c1"># distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1"># See the License for the specific language governing permissions and</span>
<span class="c1"># limitations under the License.</span>
<span class="c1">#</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">.. attribute:: ImageSchema</span>
<span class="sd"> An attribute of this module that contains the instance of :class:`_ImageSchema`.</span>
<span class="sd">.. autoclass:: _ImageSchema</span>
<span class="sd"> :members:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">distutils.version</span> <span class="kn">import</span> <span class="n">LooseVersion</span>
<span class="kn">from</span> <span class="nn">pyspark</span> <span class="kn">import</span> <span class="n">SparkContext</span>
<span class="kn">from</span> <span class="nn">pyspark.sql.types</span> <span class="kn">import</span> <span class="n">Row</span><span class="p">,</span> <span class="n">_create_row</span><span class="p">,</span> <span class="n">_parse_datatype_json_string</span>
<span class="kn">from</span> <span class="nn">pyspark.sql</span> <span class="kn">import</span> <span class="n">SparkSession</span>
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;ImageSchema&quot;</span><span class="p">]</span>
<div class="viewcode-block" id="_ImageSchema"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.image._ImageSchema.html#pyspark.ml.image._ImageSchema">[docs]</a><span class="k">class</span> <span class="nc">_ImageSchema</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Internal class for `pyspark.ml.image.ImageSchema` attribute. Meant to be private and</span>
<span class="sd"> not to be instantized. Use `pyspark.ml.image.ImageSchema` attribute to access the</span>
<span class="sd"> APIs of this class.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imageSchema</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_ocvTypes</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_columnSchema</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imageFields</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_undefinedImageType</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">imageSchema</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the image schema.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> :class:`StructType`</span>
<span class="sd"> with a single column of images named &quot;image&quot; (nullable)</span>
<span class="sd"> and having the same type returned by :meth:`columnSchema`.</span>
<span class="sd"> .. versionadded:: 2.3.0</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_imageSchema</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ctx</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_active_spark_context</span>
<span class="n">jschema</span> <span class="o">=</span> <span class="n">ctx</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">image</span><span class="o">.</span><span class="n">ImageSchema</span><span class="o">.</span><span class="n">imageSchema</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imageSchema</span> <span class="o">=</span> <span class="n">_parse_datatype_json_string</span><span class="p">(</span><span class="n">jschema</span><span class="o">.</span><span class="n">json</span><span class="p">())</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_imageSchema</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">ocvTypes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the OpenCV type mapping supported.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> dict</span>
<span class="sd"> a dictionary containing the OpenCV type mapping supported.</span>
<span class="sd"> .. versionadded:: 2.3.0</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_ocvTypes</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ctx</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_active_spark_context</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_ocvTypes</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">ctx</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">image</span><span class="o">.</span><span class="n">ImageSchema</span><span class="o">.</span><span class="n">javaOcvTypes</span><span class="p">())</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_ocvTypes</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">columnSchema</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the schema for the image column.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> :class:`StructType`</span>
<span class="sd"> a schema for image column,</span>
<span class="sd"> ``struct&lt;origin:string, height:int, width:int, nChannels:int, mode:int, data:binary&gt;``.</span>
<span class="sd"> .. versionadded:: 2.4.0</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_columnSchema</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ctx</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_active_spark_context</span>
<span class="n">jschema</span> <span class="o">=</span> <span class="n">ctx</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">image</span><span class="o">.</span><span class="n">ImageSchema</span><span class="o">.</span><span class="n">columnSchema</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_columnSchema</span> <span class="o">=</span> <span class="n">_parse_datatype_json_string</span><span class="p">(</span><span class="n">jschema</span><span class="o">.</span><span class="n">json</span><span class="p">())</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_columnSchema</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">imageFields</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns field names of image columns.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> list</span>
<span class="sd"> a list of field names.</span>
<span class="sd"> .. versionadded:: 2.3.0</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_imageFields</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ctx</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_active_spark_context</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_imageFields</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">ctx</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">image</span><span class="o">.</span><span class="n">ImageSchema</span><span class="o">.</span><span class="n">imageFields</span><span class="p">())</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_imageFields</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">undefinedImageType</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the name of undefined image type for the invalid image.</span>
<span class="sd"> .. versionadded:: 2.3.0</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_undefinedImageType</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ctx</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_active_spark_context</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_undefinedImageType</span> <span class="o">=</span> \
<span class="n">ctx</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">image</span><span class="o">.</span><span class="n">ImageSchema</span><span class="o">.</span><span class="n">undefinedImageType</span><span class="p">()</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_undefinedImageType</span>
<div class="viewcode-block" id="_ImageSchema.toNDArray"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.image._ImageSchema.html#pyspark.ml.image._ImageSchema.toNDArray">[docs]</a> <span class="k">def</span> <span class="nf">toNDArray</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">image</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Converts an image to an array with metadata.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> image : :class:`Row`</span>
<span class="sd"> image: A row that contains the image to be converted. It should</span>
<span class="sd"> have the attributes specified in `ImageSchema.imageSchema`.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> :class:`numpy.ndarray`</span>
<span class="sd"> that is an image.</span>
<span class="sd"> .. versionadded:: 2.3.0</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">Row</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
<span class="s2">&quot;image argument should be pyspark.sql.types.Row; however, &quot;</span>
<span class="s2">&quot;it got [</span><span class="si">%s</span><span class="s2">].&quot;</span> <span class="o">%</span> <span class="nb">type</span><span class="p">(</span><span class="n">image</span><span class="p">))</span>
<span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span> <span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">imageFields</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s2">&quot;image argument should have attributes specified in &quot;</span>
<span class="s2">&quot;ImageSchema.imageSchema [</span><span class="si">%s</span><span class="s2">].&quot;</span> <span class="o">%</span> <span class="s2">&quot;, &quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imageFields</span><span class="p">))</span>
<span class="n">height</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">height</span>
<span class="n">width</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">width</span>
<span class="n">nChannels</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">nChannels</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">(</span>
<span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">,</span> <span class="n">nChannels</span><span class="p">),</span>
<span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">,</span>
<span class="n">buffer</span><span class="o">=</span><span class="n">image</span><span class="o">.</span><span class="n">data</span><span class="p">,</span>
<span class="n">strides</span><span class="o">=</span><span class="p">(</span><span class="n">width</span> <span class="o">*</span> <span class="n">nChannels</span><span class="p">,</span> <span class="n">nChannels</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span></div>
<div class="viewcode-block" id="_ImageSchema.toImage"><a class="viewcode-back" href="../../../reference/api/pyspark.ml.image._ImageSchema.html#pyspark.ml.image._ImageSchema.toImage">[docs]</a> <span class="k">def</span> <span class="nf">toImage</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">array</span><span class="p">,</span> <span class="n">origin</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Converts an array with metadata to a two-dimensional image.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> array : :class:`numpy.ndarray`</span>
<span class="sd"> The array to convert to image.</span>
<span class="sd"> origin : str</span>
<span class="sd"> Path to the image, optional.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> :class:`Row`</span>
<span class="sd"> that is a two dimensional image.</span>
<span class="sd"> .. versionadded:: 2.3.0</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">array</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
<span class="s2">&quot;array argument should be numpy.ndarray; however, it got [</span><span class="si">%s</span><span class="s2">].&quot;</span> <span class="o">%</span> <span class="nb">type</span><span class="p">(</span><span class="n">array</span><span class="p">))</span>
<span class="k">if</span> <span class="n">array</span><span class="o">.</span><span class="n">ndim</span> <span class="o">!=</span> <span class="mi">3</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Invalid array shape&quot;</span><span class="p">)</span>
<span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">,</span> <span class="n">nChannels</span> <span class="o">=</span> <span class="n">array</span><span class="o">.</span><span class="n">shape</span>
<span class="n">ocvTypes</span> <span class="o">=</span> <span class="n">ImageSchema</span><span class="o">.</span><span class="n">ocvTypes</span>
<span class="k">if</span> <span class="n">nChannels</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">mode</span> <span class="o">=</span> <span class="n">ocvTypes</span><span class="p">[</span><span class="s2">&quot;CV_8UC1&quot;</span><span class="p">]</span>
<span class="k">elif</span> <span class="n">nChannels</span> <span class="o">==</span> <span class="mi">3</span><span class="p">:</span>
<span class="n">mode</span> <span class="o">=</span> <span class="n">ocvTypes</span><span class="p">[</span><span class="s2">&quot;CV_8UC3&quot;</span><span class="p">]</span>
<span class="k">elif</span> <span class="n">nChannels</span> <span class="o">==</span> <span class="mi">4</span><span class="p">:</span>
<span class="n">mode</span> <span class="o">=</span> <span class="n">ocvTypes</span><span class="p">[</span><span class="s2">&quot;CV_8UC4&quot;</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Invalid number of channels&quot;</span><span class="p">)</span>
<span class="c1"># Running `bytearray(numpy.array([1]))` fails in specific Python versions</span>
<span class="c1"># with a specific Numpy version, for example in Python 3.6.0 and NumPy 1.13.3.</span>
<span class="c1"># Here, it avoids it by converting it to bytes.</span>
<span class="k">if</span> <span class="n">LooseVersion</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">__version__</span><span class="p">)</span> <span class="o">&gt;=</span> <span class="n">LooseVersion</span><span class="p">(</span><span class="s1">&#39;1.9&#39;</span><span class="p">):</span>
<span class="n">data</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">(</span><span class="n">array</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span><span class="o">.</span><span class="n">tobytes</span><span class="p">())</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># Numpy prior to 1.9 don&#39;t have `tobytes` method.</span>
<span class="n">data</span> <span class="o">=</span> <span class="nb">bytearray</span><span class="p">(</span><span class="n">array</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span><span class="o">.</span><span class="n">ravel</span><span class="p">())</span>
<span class="c1"># Creating new Row with _create_row(), because Row(name = value, ... )</span>
<span class="c1"># orders fields by name, which conflicts with expected schema order</span>
<span class="c1"># when the new DataFrame is created by UDF</span>
<span class="k">return</span> <span class="n">_create_row</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">imageFields</span><span class="p">,</span>
<span class="p">[</span><span class="n">origin</span><span class="p">,</span> <span class="n">height</span><span class="p">,</span> <span class="n">width</span><span class="p">,</span> <span class="n">nChannels</span><span class="p">,</span> <span class="n">mode</span><span class="p">,</span> <span class="n">data</span><span class="p">])</span></div></div>
<span class="n">ImageSchema</span> <span class="o">=</span> <span class="n">_ImageSchema</span><span class="p">()</span>
<span class="c1"># Monkey patch to disallow instantiation of this class.</span>
<span class="k">def</span> <span class="nf">_disallow_instance</span><span class="p">(</span><span class="n">_</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Creating instance of _ImageSchema class is disallowed.&quot;</span><span class="p">)</span>
<span class="n">_ImageSchema</span><span class="o">.</span><span class="fm">__init__</span> <span class="o">=</span> <span class="n">_disallow_instance</span>
<span class="k">def</span> <span class="nf">_test</span><span class="p">():</span>
<span class="kn">import</span> <span class="nn">doctest</span>
<span class="kn">import</span> <span class="nn">pyspark.ml.image</span>
<span class="n">globs</span> <span class="o">=</span> <span class="n">pyspark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">image</span><span class="o">.</span><span class="vm">__dict__</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="n">spark</span> <span class="o">=</span> <span class="n">SparkSession</span><span class="o">.</span><span class="n">builder</span>\
<span class="o">.</span><span class="n">master</span><span class="p">(</span><span class="s2">&quot;local[2]&quot;</span><span class="p">)</span>\
<span class="o">.</span><span class="n">appName</span><span class="p">(</span><span class="s2">&quot;ml.image tests&quot;</span><span class="p">)</span>\
<span class="o">.</span><span class="n">getOrCreate</span><span class="p">()</span>
<span class="n">globs</span><span class="p">[</span><span class="s1">&#39;spark&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">spark</span>
<span class="p">(</span><span class="n">failure_count</span><span class="p">,</span> <span class="n">test_count</span><span class="p">)</span> <span class="o">=</span> <span class="n">doctest</span><span class="o">.</span><span class="n">testmod</span><span class="p">(</span>
<span class="n">pyspark</span><span class="o">.</span><span class="n">ml</span><span class="o">.</span><span class="n">image</span><span class="p">,</span> <span class="n">globs</span><span class="o">=</span><span class="n">globs</span><span class="p">,</span>
<span class="n">optionflags</span><span class="o">=</span><span class="n">doctest</span><span class="o">.</span><span class="n">ELLIPSIS</span> <span class="o">|</span> <span class="n">doctest</span><span class="o">.</span><span class="n">NORMALIZE_WHITESPACE</span><span class="p">)</span>
<span class="n">spark</span><span class="o">.</span><span class="n">stop</span><span class="p">()</span>
<span class="k">if</span> <span class="n">failure_count</span><span class="p">:</span>
<span class="n">sys</span><span class="o">.</span><span class="n">exit</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s2">&quot;__main__&quot;</span><span class="p">:</span>
<span class="n">_test</span><span class="p">()</span>
</pre></div>
</div>
<div class='prev-next-bottom'>
</div>
</main>
</div>
</div>
<script src="../../../_static/js/index.3da636dd464baa7582d2.js"></script>
<footer class="footer mt-5 mt-md-0">
<div class="container">
<p>
&copy; Copyright .<br/>
Created using <a href="http://sphinx-doc.org/">Sphinx</a> 3.0.4.<br/>
</p>
</div>
</footer>
</body>
</html>