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<title>ONNX Runtime for Keras — ONNX Runtime 1.6.0 documentation</title>
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<div class="sphx-glr-download-link-note admonition note">
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<p class="admonition-title">Note</p>
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<p>Click <a class="reference internal" href="#sphx-glr-download-auto-examples-plot-dl-keras-py"><span class="std std-ref">here</span></a>
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to download the full example code</p>
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</div>
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<div class="sphx-glr-example-title section" id="onnx-runtime-for-keras">
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<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>
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<p>The following demonstrates how to compute the predictions
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of a pretrained deep learning model obtained from
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<a class="reference external" href="https://keras.io/">keras</a>
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with <em>onnxruntime</em>. The conversion requires
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<a class="reference external" href="https://keras.io/">keras</a>,
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<a class="reference external" href="https://www.tensorflow.org/">tensorflow</a>,
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<a class="reference external" href="https://github.com/onnx/keras-onnx/">keras-onnx</a>,
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<a class="reference external" href="https://pypi.org/project/onnxmltools/">onnxmltools</a>
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but then only <em>onnxruntime</em> is required
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to compute the predictions.</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>
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<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">'dense121.onnx'</span><span class="p">):</span>
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<span class="kn">from</span> <span class="nn">keras.applications.densenet</span> <span class="kn">import</span> <span class="n">DenseNet121</span>
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<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">'imagenet'</span><span class="p">)</span>
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<span class="kn">from</span> <span class="nn">keras2onnx</span> <span class="kn">import</span> <span class="n">convert_keras</span>
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<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">'dense121.onnx'</span><span class="p">)</span>
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<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">"dense121.onnx"</span><span class="p">,</span> <span class="s2">"wb"</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
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<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>
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</pre></div>
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</div>
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<div class="sphx-glr-script-out highlight-pytb notranslate"><div class="highlight"><pre><span></span><span class="gt">Traceback (most recent call last):</span>
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File <span class="nb">"C:\xadupre\microsoft_xadupre\onnxruntime\docs\python\examples\plot_dl_keras.py"</span>, line <span class="m">28</span>, in <span class="n"><module></span>
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<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">'dense121.onnx'</span><span class="p">)</span>
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File <span class="nb">"C:\xadupre\microsoft_xadupre\keras-onnx\keras2onnx\main.py"</span>, line <span class="m">82</span>, in <span class="n">convert_keras</span>
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<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>
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File <span class="nb">"C:\xadupre\microsoft_xadupre\keras-onnx\keras2onnx\_parser_tf.py"</span>, line <span class="m">308</span>, in <span class="n">build_layer_output_from_model</span>
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<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>
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<span class="gr">AttributeError</span>: <span class="n">'KerasTensor' object has no attribute 'graph'</span>
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</pre></div>
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</div>
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<p>Let’s load an image (source: wikipedia).</p>
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<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>
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<span class="n">img</span> <span class="o">=</span> <span class="n">load_img</span><span class="p">(</span><span class="s1">'Sannosawa1.jpg'</span><span class="p">)</span>
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<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>
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<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
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<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>
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<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">(</span><span class="s1">'off'</span><span class="p">)</span>
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</pre></div>
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</div>
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<p>Let’s load the model with onnxruntime.</p>
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<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>
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<span class="kn">from</span> <span class="nn">onnxruntime.capi.onnxruntime_pybind11_state</span> <span class="kn">import</span> <span class="n">InvalidGraph</span>
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<span class="k">try</span><span class="p">:</span>
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<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">'dense121.onnx'</span><span class="p">)</span>
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<span class="n">ok</span> <span class="o">=</span> <span class="kc">True</span>
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<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>
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<span class="c1"># Probably a mismatch between onnxruntime and onnx version.</span>
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<span class="nb">print</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
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<span class="n">ok</span> <span class="o">=</span> <span class="kc">False</span>
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<span class="k">if</span> <span class="n">ok</span><span class="p">:</span>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"The model expects input shape:"</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>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"image shape:"</span><span class="p">,</span> <span class="n">ximg</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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</pre></div>
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</div>
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<p>Let’s resize the image.</p>
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<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>
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<span class="kn">from</span> <span class="nn">skimage.transform</span> <span class="kn">import</span> <span class="n">resize</span>
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<span class="kn">import</span> <span class="nn">numpy</span>
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<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>
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<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>
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<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>
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<span class="nb">print</span><span class="p">(</span><span class="s2">"new shape:"</span><span class="p">,</span> <span class="n">ximg</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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</pre></div>
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</div>
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<p>Let’s compute the output.</p>
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<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>
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<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>
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<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>
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<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>
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<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>
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</pre></div>
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</div>
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<p>Let’s get more comprehensive results.</p>
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<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>
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<span class="kn">from</span> <span class="nn">keras.applications.densenet</span> <span class="kn">import</span> <span class="n">decode_predictions</span>
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<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>
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<span class="kn">import</span> <span class="nn">pandas</span>
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<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">"class_id"</span><span class="p">,</span> <span class="s2">"name"</span><span class="p">,</span> <span class="s2">"P"</span><span class="p">])</span>
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<span class="nb">print</span><span class="p">(</span><span class="n">df</span><span class="p">)</span>
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</pre></div>
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<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>
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<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>
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