onnxruntime/python/auto_examples/plot_dl_keras.html
Xavier Dupré e210853b0c
Update python documentation (rename folders prefixed by _) (#6575)
* Update python documentation

* remove two unnecessary files

Co-authored-by: xavier dupré <xavier.dupre@gmail.com>
2021-02-10 16:34:31 -08:00

216 lines
No EOL
16 KiB
HTML
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>ONNX Runtime for Keras &#8212; ONNX Runtime 1.6.0 documentation</title>
<link rel="stylesheet" href="../static/pygments.css" type="text/css" />
<link rel="stylesheet" href="../static/alabaster.css" type="text/css" />
<link rel="stylesheet" type="text/css" href="../static/graphviz.css" />
<link rel="stylesheet" type="text/css" href="../static/gallery.css" />
<link rel="stylesheet" type="text/css" href="../static/gallery-binder.css" />
<link rel="stylesheet" type="text/css" href="../static/gallery-dataframe.css" />
<link rel="stylesheet" type="text/css" href="../static/gallery-rendered-html.css" />
<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>
<link rel="index" title="Index" href="../genindex.html" />
<link rel="search" title="Search" href="../search.html" />
<link rel="stylesheet" href="../static/custom.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
</head><body>
<div class="document">
<div class="documentwrapper">
<div class="bodywrapper">
<div class="body" role="main">
<div class="sphx-glr-download-link-note admonition note">
<p class="admonition-title">Note</p>
<p>Click <a class="reference internal" href="#sphx-glr-download-auto-examples-plot-dl-keras-py"><span class="std std-ref">here</span></a>
to download the full example code</p>
</div>
<div class="sphx-glr-example-title section" id="onnx-runtime-for-keras">
<span id="l-example-backend-api-tensorflow"></span><span id="sphx-glr-auto-examples-plot-dl-keras-py"></span><h1>ONNX Runtime for Keras<a class="headerlink" href="#onnx-runtime-for-keras" title="Permalink to this headline"></a></h1>
<p>The following demonstrates how to compute the predictions
of a pretrained deep learning model obtained from
<a class="reference external" href="https://keras.io/">keras</a>
with <em>onnxruntime</em>. The conversion requires
<a class="reference external" href="https://keras.io/">keras</a>,
<a class="reference external" href="https://www.tensorflow.org/">tensorflow</a>,
<a class="reference external" href="https://github.com/onnx/keras-onnx/">keras-onnx</a>,
<a class="reference external" href="https://pypi.org/project/onnxmltools/">onnxmltools</a>
but then only <em>onnxruntime</em> is required
to compute the predictions.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="s1">&#39;dense121.onnx&#39;</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">keras.applications.densenet</span> <span class="kn">import</span> <span class="n">DenseNet121</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">DenseNet121</span><span class="p">(</span><span class="n">include_top</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="s1">&#39;imagenet&#39;</span><span class="p">)</span>
<span class="kn">from</span> <span class="nn">keras2onnx</span> <span class="kn">import</span> <span class="n">convert_keras</span>
<span class="n">onx</span> <span class="o">=</span> <span class="n">convert_keras</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s1">&#39;dense121.onnx&#39;</span><span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;dense121.onnx&quot;</span><span class="p">,</span> <span class="s2">&quot;wb&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
<span class="n">f</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="n">onx</span><span class="o">.</span><span class="n">SerializeToString</span><span class="p">())</span>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-pytb notranslate"><div class="highlight"><pre><span></span><span class="gt">Traceback (most recent call last):</span>
File <span class="nb">&quot;C:\xadupre\microsoft_xadupre\onnxruntime\docs\python\examples\plot_dl_keras.py&quot;</span>, line <span class="m">28</span>, in <span class="n">&lt;module&gt;</span>
<span class="n">onx</span> <span class="o">=</span> <span class="n">convert_keras</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s1">&#39;dense121.onnx&#39;</span><span class="p">)</span>
File <span class="nb">&quot;C:\xadupre\microsoft_xadupre\keras-onnx\keras2onnx\main.py&quot;</span>, line <span class="m">82</span>, in <span class="n">convert_keras</span>
<span class="n">tf_graph</span> <span class="o">=</span> <span class="n">build_layer_output_from_model</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">output_dict</span><span class="p">,</span> <span class="n">input_names</span><span class="p">,</span>
File <span class="nb">&quot;C:\xadupre\microsoft_xadupre\keras-onnx\keras2onnx\_parser_tf.py&quot;</span>, line <span class="m">308</span>, in <span class="n">build_layer_output_from_model</span>
<span class="n">graph</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">outputs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">graph</span>
<span class="gr">AttributeError</span>: <span class="n">&#39;KerasTensor&#39; object has no attribute &#39;graph&#39;</span>
</pre></div>
</div>
<p>Lets load an image (source: wikipedia).</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">keras.preprocessing.image</span> <span class="kn">import</span> <span class="n">array_to_img</span><span class="p">,</span> <span class="n">img_to_array</span><span class="p">,</span> <span class="n">load_img</span>
<span class="n">img</span> <span class="o">=</span> <span class="n">load_img</span><span class="p">(</span><span class="s1">&#39;Sannosawa1.jpg&#39;</span><span class="p">)</span>
<span class="n">ximg</span> <span class="o">=</span> <span class="n">img_to_array</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">ximg</span> <span class="o">/</span> <span class="mi">255</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s1">&#39;off&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Lets load the model with onnxruntime.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">onnxruntime</span> <span class="k">as</span> <span class="nn">rt</span>
<span class="kn">from</span> <span class="nn">onnxruntime.capi.onnxruntime_pybind11_state</span> <span class="kn">import</span> <span class="n">InvalidGraph</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">sess</span> <span class="o">=</span> <span class="n">rt</span><span class="o">.</span><span class="n">InferenceSession</span><span class="p">(</span><span class="s1">&#39;dense121.onnx&#39;</span><span class="p">)</span>
<span class="n">ok</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">except</span> <span class="p">(</span><span class="n">InvalidGraph</span><span class="p">,</span> <span class="ne">TypeError</span><span class="p">,</span> <span class="ne">RuntimeError</span><span class="p">)</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
<span class="c1"># Probably a mismatch between onnxruntime and onnx version.</span>
<span class="nb">print</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
<span class="n">ok</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">ok</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;The model expects input shape:&quot;</span><span class="p">,</span> <span class="n">sess</span><span class="o">.</span><span class="n">get_inputs</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;image shape:&quot;</span><span class="p">,</span> <span class="n">ximg</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
</pre></div>
</div>
<p>Lets resize the image.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">if</span> <span class="n">ok</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">skimage.transform</span> <span class="kn">import</span> <span class="n">resize</span>
<span class="kn">import</span> <span class="nn">numpy</span>
<span class="n">ximg224</span> <span class="o">=</span> <span class="n">resize</span><span class="p">(</span><span class="n">ximg</span> <span class="o">/</span> <span class="mi">255</span><span class="p">,</span> <span class="p">(</span><span class="mi">224</span><span class="p">,</span> <span class="mi">224</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span> <span class="n">anti_aliasing</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">ximg</span> <span class="o">=</span> <span class="n">ximg224</span><span class="p">[</span><span class="n">numpy</span><span class="o">.</span><span class="n">newaxis</span><span class="p">,</span> <span class="p">:,</span> <span class="p">:,</span> <span class="p">:]</span>
<span class="n">ximg</span> <span class="o">=</span> <span class="n">ximg</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;new shape:&quot;</span><span class="p">,</span> <span class="n">ximg</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
</pre></div>
</div>
<p>Lets compute the output.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">if</span> <span class="n">ok</span><span class="p">:</span>
<span class="n">input_name</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">get_inputs</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">name</span>
<span class="n">res</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="p">{</span><span class="n">input_name</span><span class="p">:</span> <span class="n">ximg</span><span class="p">})</span>
<span class="n">prob</span> <span class="o">=</span> <span class="n">res</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="nb">print</span><span class="p">(</span><span class="n">prob</span><span class="o">.</span><span class="n">ravel</span><span class="p">()[:</span><span class="mi">10</span><span class="p">])</span> <span class="c1"># Too big to be displayed.</span>
</pre></div>
</div>
<p>Lets get more comprehensive results.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">if</span> <span class="n">ok</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">keras.applications.densenet</span> <span class="kn">import</span> <span class="n">decode_predictions</span>
<span class="n">decoded</span> <span class="o">=</span> <span class="n">decode_predictions</span><span class="p">(</span><span class="n">prob</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">pandas</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pandas</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">decoded</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;class_id&quot;</span><span class="p">,</span> <span class="s2">&quot;name&quot;</span><span class="p">,</span> <span class="s2">&quot;P&quot;</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="n">df</span><span class="p">)</span>
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 6.417 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-dl-keras-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../downloads/b81c8c31615f9400a26ee60f0641af3f/plot_dl_keras.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_dl_keras.py</span></code></a></p>
</div>
<div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
<p><a class="reference download internal" download="" href="../downloads/c9f88a9294285c733dcce209fcc939de/plot_dl_keras.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_dl_keras.ipynb</span></code></a></p>
</div>
</div>
<p class="sphx-glr-signature"><a class="reference external" href="https://sphinx-gallery.github.io">Gallery generated by Sphinx-Gallery</a></p>
</div>
</div>
</div>
</div>
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
<div class="sphinxsidebarwrapper">
<p class="logo"><a href="../index.html">
<img class="logo" src="../static/ONNX_Runtime_icon.png" alt="Logo"/>
</a></p>
<h1 class="logo"><a href="../index.html">ONNX Runtime</a></h1>
<h3>Navigation</h3>
<ul>
<li class="toctree-l1"><a class="reference internal" href="../tutorial.html">Tutorial</a></li>
<li class="toctree-l1"><a class="reference internal" href="../api_summary.html">API Summary</a></li>
<li class="toctree-l1"><a class="reference internal" href="index.html">Gallery of examples</a></li>
</ul>
<div class="relations">
<h3>Related Topics</h3>
<ul>
<li><a href="../index.html">Documentation overview</a><ul>
</ul></li>
</ul>
</div>
<div id="searchbox" style="display: none" role="search">
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="submit" value="Go" />
</form>
</div>
</div>
<script>$('#searchbox').show(0);</script>
</div>
</div>
<div class="clearer"></div>
</div>
<div class="footer">
&copy;2018-2021, Microsoft.
|
Powered by <a href="http://sphinx-doc.org/">Sphinx 3.4.2</a>
&amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.12</a>
|
<a href="../sources/auto_examples/plot_dl_keras.rst.txt"
rel="nofollow">Page source</a>
</div>
</body>
</html>