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<p>In this example, we convert Inception V4 trained on Tensorflow to SINGA for image classification. Tested on SINGA version 1.1.1 with <a href="https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz">parameters pretrained by tensorflow</a>.</p>
<h2><a class="anchor" aria-hidden="true" id="instructions"></a><a href="#instructions" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Instructions</h2>
<blockquote>
<p>Please <code>cd</code> to <code>singa/examples/imagenet/inception/</code> for the following commands</p>
</blockquote>
<h3><a class="anchor" aria-hidden="true" id="download"></a><a href="#download" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Download</h3>
<p>Download the parameter checkpoint file</p>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> wget https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz</span>
<span class="hljs-meta">$</span><span class="bash"> tar xvf inception_v4.tar.gz</span>
</code></pre>
<p>Download <a href="https://github.com/BVLC/caffe/blob/master/data/ilsvrc12/get_ilsvrc_aux.sh">synset_word.txt</a> file.</p>
<h3><a class="anchor" aria-hidden="true" id="run-the-program"></a><a href="#run-the-program" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Run the program</h3>
<pre><code class="hljs css language-shell"><span class="hljs-meta">#</span><span class="bash"> use cpu</span>
<span class="hljs-meta">$</span><span class="bash"> python serve.py -C &amp;</span>
<span class="hljs-meta">#</span><span class="bash"> use gpu</span>
<span class="hljs-meta">$</span><span class="bash"> python serve.py &amp;</span>
</code></pre>
<h3><a class="anchor" aria-hidden="true" id="submit-images-for-classification"></a><a href="#submit-images-for-classification" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Submit images for classification</h3>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> curl -i -F image=@image1.jpg http://localhost:9999/api</span>
<span class="hljs-meta">$</span><span class="bash"> curl -i -F image=@image2.jpg http://localhost:9999/api</span>
<span class="hljs-meta">$</span><span class="bash"> curl -i -F image=@image3.jpg http://localhost:9999/api</span>
</code></pre>
<p>image1.jpg, image2.jpg and image3.jpg should be downloaded before executing the above commands.</p>
<h2><a class="anchor" aria-hidden="true" id="details"></a><a href="#details" aria-hidden="true" class="hash-link"><svg class="hash-link-icon" aria-hidden="true" height="16" version="1.1" viewBox="0 0 16 16" width="16"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a>Details</h2>
<p>We first extract the parameter values from <a href="http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz">Tensorflow's checkpoint file</a> into a pickle version. After downloading and decompressing the checkpoint file, run the following script</p>
<pre><code class="hljs css language-shell"><span class="hljs-meta">$</span><span class="bash"> python convert.py --file_name=inception_v4.ckpt</span>
</code></pre>
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