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<li class="toctree-l1 current current-page"><a class="current reference internal" href="#">Getting Started</a></li>
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<p class="caption" role="heading"><span class="caption-text">Advanced Ikomia Guide</span></p>
<ul>
<li class="toctree-l1 has-children"><a class="reference internal" href="advanced_guide/index.html">Going deeper with workflows</a><input class="toctree-checkbox" id="toctree-checkbox-1" name="toctree-checkbox-1" role="switch" type="checkbox"/><label for="toctree-checkbox-1"><div class="visually-hidden">Toggle navigation of Going deeper with workflows</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l2"><a class="reference internal" href="advanced_guide/ik_namespace.html">The <code class="docutils literal notranslate"><span class="pre">ik</span></code> auto-completion system</a></li>
<li class="toctree-l2"><a class="reference internal" href="advanced_guide/IO_management.html">Input/Output management</a></li>
<li class="toctree-l2"><a class="reference internal" href="advanced_guide/save_and_load_workflow.html">Save and load your workflow</a></li>
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<li class="toctree-l1 has-children"><a class="reference internal" href="integration/index.html">Create and integrate your algorithm in workflows</a><input class="toctree-checkbox" id="toctree-checkbox-2" name="toctree-checkbox-2" role="switch" type="checkbox"/><label for="toctree-checkbox-2"><div class="visually-hidden">Toggle navigation of Create and integrate your algorithm in workflows</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l2"><a class="reference internal" href="integration/algo_parameters.html">How to add parameters to your algorithm</a></li>
<li class="toctree-l2"><a class="reference internal" href="integration/algo_widget.html">How to make a nice widget for your algorithm</a></li>
<li class="toctree-l2"><a class="reference internal" href="integration/algo_IO.html">Specific I/O for your algorithm</a></li>
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<article role="main" id="furo-main-content">
<section id="getting-started">
<h1>Getting Started<a class="headerlink" href="#getting-started" title="Link to this heading">¶</a></h1>
<section id="installation">
<h2>Installation<a class="headerlink" href="#installation" title="Link to this heading">¶</a></h2>
<p>We strongly recommend using a virtual environment.
If you’re not sure where to start, we offer a tutorial <a class="reference internal" href="bonus/virtual_env.html"><span class="doc std std-doc">here</span></a>.</p>
<section id="installing-ikomia-api">
<h3>Installing Ikomia API<a class="headerlink" href="#installing-ikomia-api" title="Link to this heading">¶</a></h3>
<p>Install Ikomia API</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>ikomia
</pre></div>
</div>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>We only support Python 3.7, 3.8, 3.9 and 3.10 on Windows 10 and Linux.</p>
</div>
</section>
</section>
<section id="pre-requisites">
<h2>Pre-requisites<a class="headerlink" href="#pre-requisites" title="Link to this heading">¶</a></h2>
<p>Open your favorite IDE (PyCharm, VS Code…) and create a new project in your virtual environment.<br>
Then, you can just copy/paste the different examples below.<br></p>
<div class="admonition important">
<p class="admonition-title">Important</p>
<p>If you use a notebook (Jupyter, Jupyter Lab or Google Colab), please copy/paste this code snippet for a better display of images.</p>
</div>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">ImageShow</span>
<span class="n">ImageShow</span><span class="o">.</span><span class="n">register</span><span class="p">(</span><span class="n">ImageShow</span><span class="o">.</span><span class="n">IPythonViewer</span><span class="p">(),</span> <span class="mi">0</span><span class="p">)</span>
</pre></div>
</div>
</section>
<hr class="docutils" />
<section id="basic-usage-workflow-with-1-algorithm">
<h2>Basic usage : workflow with 1 algorithm<a class="headerlink" href="#basic-usage-workflow-with-1-algorithm" title="Link to this heading">¶</a></h2>
<p>In this example, we simply use the <strong>Canny Edge Detector</strong> from OpenCV.<br></p>
<section id="workflow-structure">
<h3>Workflow Structure<a class="headerlink" href="#workflow-structure" title="Link to this heading">¶</a></h3>
<div class="mermaid">
%%{
init: {
'theme': 'base',
'themeVariables': {
'primaryBorderColor': '#CC5A20',
'lineColor': '#CC5A20'
}
}
}%%
graph LR
A[(Input images)] -.-> B(ocv_canny)
B -.-> C[(Output images)]
</div></section>
<section id="code">
<h3>Code<a class="headerlink" href="#code" title="Link to this heading">¶</a></h3>
<p>Create and run your 1st workflow.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">ikomia.dataprocess.workflow</span> <span class="kn">import</span> <span class="n">Workflow</span>
<span class="kn">from</span> <span class="nn">ikomia.utils.displayIO</span> <span class="kn">import</span> <span class="n">display</span>
<span class="c1"># Init your workflow</span>
<span class="n">wf</span> <span class="o">=</span> <span class="n">Workflow</span><span class="p">()</span>
<span class="c1"># Add the Canny Edge Detector</span>
<span class="n">canny</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">add_task</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"ocv_canny"</span><span class="p">,</span> <span class="n">auto_connect</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># Run on your image </span>
<span class="c1"># wf.run_on(path="path/to/your/image.png")</span>
<span class="n">wf</span><span class="o">.</span><span class="n">run_on</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">"https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_work.jpg"</span><span class="p">)</span>
<span class="c1"># Inspect your results</span>
<span class="n">display</span><span class="p">(</span><span class="n">canny</span><span class="o">.</span><span class="n">get_input</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
<span class="n">display</span><span class="p">(</span><span class="n">canny</span><span class="o">.</span><span class="n">get_output</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
</pre></div>
</div>
<p>For a step by step explanation, see <a class="reference internal" href="advanced_guide/index.html"><span class="doc std std-doc">here</span></a>.</p>
</section>
<section id="results">
<h3>Results<a class="headerlink" href="#results" title="Link to this heading">¶</a></h3>
<div class="table-wrapper colwidths-auto docutils container">
<table class="docutils align-default">
<thead>
<tr class="row-odd"><th class="head text-center"><p>Source image</p></th>
<th class="head text-center"><p>Canny Edge Detector</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td class="text-center"><p><img alt="" src="_images/img_work.jpg" /></p></td>
<td class="text-center"><p><img alt="" src="_images/img_canny.jpg" /></p></td>
</tr>
</tbody>
</table>
</div>
</section>
</section>
<section id="basic-usage-workflow-with-1-algorithm-from-ikomia-hub">
<h2>Basic usage : workflow with 1 algorithm from Ikomia HUB<a class="headerlink" href="#basic-usage-workflow-with-1-algorithm-from-ikomia-hub" title="Link to this heading">¶</a></h2>
<p>In this example, we use an algorithm from Ikomia HUB.<br>
Just run your workflow and at runtime, it will automagically download and install all algorithms (if not already installed) on your machine.</p>
<section id="id1">
<h3>Workflow Structure<a class="headerlink" href="#id1" title="Link to this heading">¶</a></h3>
<div class="mermaid">
%%{
init: {
'theme': 'base',
'themeVariables': {
'primaryBorderColor': '#CC5A20',
'lineColor': '#CC5A20'
}
}
}%%
graph LR
A[(Input images)] -.-> B(infer_yolo_v7)
B -.-> C[(Output images)]
</div></section>
<section id="id2">
<h3>Code<a class="headerlink" href="#id2" title="Link to this heading">¶</a></h3>
<p>Create and run your workflow.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">ikomia.dataprocess.workflow</span> <span class="kn">import</span> <span class="n">Workflow</span>
<span class="kn">from</span> <span class="nn">ikomia.utils.displayIO</span> <span class="kn">import</span> <span class="n">display</span>
<span class="c1"># Init your workflow</span>
<span class="n">wf</span> <span class="o">=</span> <span class="n">Workflow</span><span class="p">()</span>
<span class="c1"># Add the YOLO v7 Object Detector</span>
<span class="n">yolov7</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">add_task</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"infer_yolo_v7"</span><span class="p">,</span> <span class="n">auto_connect</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># Run on your image </span>
<span class="c1"># wf.run_on(path="path/to/your/image.png")</span>
<span class="n">wf</span><span class="o">.</span><span class="n">run_on</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">"https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_work.jpg"</span><span class="p">)</span>
<span class="c1"># Inspect your results</span>
<span class="n">display</span><span class="p">(</span><span class="n">yolov7</span><span class="o">.</span><span class="n">get_input</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
<span class="n">display</span><span class="p">(</span><span class="n">yolov7</span><span class="o">.</span><span class="n">get_image_with_graphics</span><span class="p">())</span>
</pre></div>
</div>
<p>For a step by step explanation, see <a class="reference internal" href="advanced_guide/index.html"><span class="doc std std-doc">here</span></a>.</p>
</section>
<section id="id3">
<h3>Results<a class="headerlink" href="#id3" title="Link to this heading">¶</a></h3>
<div class="table-wrapper colwidths-auto docutils container">
<table class="docutils align-default">
<thead>
<tr class="row-odd"><th class="head text-center"><p>Source image</p></th>
<th class="head text-center"><p>YOLO v7 Object Detector</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td class="text-center"><p><img alt="" src="_images/img_work.jpg" /></p></td>
<td class="text-center"><p><img alt="" src="_images/img_yolo.jpg" /></p></td>
</tr>
</tbody>
</table>
</div>
</section>
</section>
<section id="advanced-usage-workflow-with-1-algorithm-custom-settings">
<h2>Advanced usage : workflow with 1 algorithm + custom settings<a class="headerlink" href="#advanced-usage-workflow-with-1-algorithm-custom-settings" title="Link to this heading">¶</a></h2>
<section id="id4">
<h3>Workflow Structure<a class="headerlink" href="#id4" title="Link to this heading">¶</a></h3>
<div class="mermaid">
%%{
init: {
'theme': 'base',
'themeVariables': {
'primaryBorderColor': '#CC5A20',
'lineColor': '#CC5A20'
}
}
}%%
graph LR
A[(Input images)] -.-> B(ocv_canny)
B -.-> C[(Output images)]
</div></section>
<section id="id5">
<h3>Code<a class="headerlink" href="#id5" title="Link to this heading">¶</a></h3>
<p>Adjust the algorithm parameters with our <code class="docutils literal notranslate"><span class="pre">ik</span></code> <a class="reference internal" href="advanced_guide/ik_namespace.html"><span class="doc std std-doc">auto-completion</span></a> mechanism …</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">ikomia.dataprocess.workflow</span> <span class="kn">import</span> <span class="n">Workflow</span>
<span class="kn">from</span> <span class="nn">ikomia.utils.displayIO</span> <span class="kn">import</span> <span class="n">display</span>
<span class="kn">from</span> <span class="nn">ikomia.utils</span> <span class="kn">import</span> <span class="n">ik</span>
<span class="c1"># Init your workflow</span>
<span class="n">wf</span> <span class="o">=</span> <span class="n">Workflow</span><span class="p">()</span>
<span class="c1"># Add the Canny Edge Detector with specific parameters</span>
<span class="n">canny</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">add_task</span><span class="p">(</span><span class="n">ik</span><span class="o">.</span><span class="n">ocv_canny</span><span class="p">(</span><span class="n">threshold1</span><span class="o">=</span><span class="s2">"100"</span><span class="p">,</span> <span class="n">threshold2</span><span class="o">=</span><span class="s2">"200"</span><span class="p">),</span> <span class="n">auto_connect</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># Run on your image </span>
<span class="c1"># wf.run_on(path="path/to/your/image.png")</span>
<span class="n">wf</span><span class="o">.</span><span class="n">run_on</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">"https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_work.jpg"</span><span class="p">)</span>
<span class="c1"># Inspect your results</span>
<span class="n">display</span><span class="p">(</span><span class="n">canny</span><span class="o">.</span><span class="n">get_input</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
<span class="n">display</span><span class="p">(</span><span class="n">canny</span><span class="o">.</span><span class="n">get_output</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
</pre></div>
</div>
<p>… or use a classic Dict approach</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">ikomia.dataprocess.workflow</span> <span class="kn">import</span> <span class="n">Workflow</span>
<span class="kn">from</span> <span class="nn">ikomia.utils.displayIO</span> <span class="kn">import</span> <span class="n">display</span>
<span class="c1"># Init your workflow</span>
<span class="n">wf</span> <span class="o">=</span> <span class="n">Workflow</span><span class="p">()</span>
<span class="c1"># Add the Canny Edge Detector</span>
<span class="n">canny</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">add_task</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"ocv_canny"</span><span class="p">,</span> <span class="n">auto_connect</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># Change Canny parameters</span>
<span class="n">canny</span><span class="o">.</span><span class="n">set_parameters</span><span class="p">({</span>
<span class="s2">"threshold1"</span><span class="p">:</span> <span class="s2">"100"</span><span class="p">,</span>
<span class="s2">"threshold2"</span><span class="p">:</span> <span class="s2">"200"</span>
<span class="p">})</span>
<span class="c1"># Run on your image </span>
<span class="c1"># wf.run_on(path="path/to/your/image.png")</span>
<span class="n">wf</span><span class="o">.</span><span class="n">run_on</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">"https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_work.jpg"</span><span class="p">)</span>
<span class="c1"># Inspect your results</span>
<span class="n">display</span><span class="p">(</span><span class="n">canny</span><span class="o">.</span><span class="n">get_input</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
<span class="n">display</span><span class="p">(</span><span class="n">canny</span><span class="o">.</span><span class="n">get_output</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
</pre></div>
</div>
<p>For a step by step explanation, see <a class="reference internal" href="advanced_guide/index.html"><span class="doc std std-doc">here</span></a>.</p>
</section>
<section id="id6">
<h3>Results<a class="headerlink" href="#id6" title="Link to this heading">¶</a></h3>
<div class="table-wrapper colwidths-auto docutils container">
<table class="docutils align-default">
<thead>
<tr class="row-odd"><th class="head text-center"><p>Source image</p></th>
<th class="head text-center"><p>Canny Edge Detector</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td class="text-center"><p><img alt="" src="_images/img_work.jpg" /></p></td>
<td class="text-center"><p><img alt="" src="_images/img_canny_thres.jpg" /></p></td>
</tr>
</tbody>
</table>
</div>
</section>
</section>
<section id="advanced-usage-workflow-with-2-algorithms-custom-settings">
<h2>Advanced usage : workflow with 2 algorithms + custom settings<a class="headerlink" href="#advanced-usage-workflow-with-2-algorithms-custom-settings" title="Link to this heading">¶</a></h2>
<section id="id7">
<h3>Workflow Structure<a class="headerlink" href="#id7" title="Link to this heading">¶</a></h3>
<div class="mermaid">
%%{
init: {
'theme': 'base',
'themeVariables': {
'primaryBorderColor': '#CC5A20',
'lineColor': '#CC5A20'
}
}
}%%
graph LR
A[(Input images)] -.-> B(infer_face_detection_kornia)
B --> C(ocv_blur)
C -.-> D[(Output images)]
</div></section>
<section id="id8">
<h3>Code<a class="headerlink" href="#id8" title="Link to this heading">¶</a></h3>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">ikomia.dataprocess.workflow</span> <span class="kn">import</span> <span class="n">Workflow</span>
<span class="kn">from</span> <span class="nn">ikomia.utils.displayIO</span> <span class="kn">import</span> <span class="n">display</span>
<span class="kn">from</span> <span class="nn">ikomia.utils</span> <span class="kn">import</span> <span class="n">ik</span>
<span class="c1"># Init your workflow</span>
<span class="n">wf</span> <span class="o">=</span> <span class="n">Workflow</span><span class="p">()</span>
<span class="c1"># Add the Kornia Face Detector</span>
<span class="n">face</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">add_task</span><span class="p">(</span><span class="n">ik</span><span class="o">.</span><span class="n">infer_face_detection_kornia</span><span class="p">(),</span> <span class="n">auto_connect</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># Add a blur effect</span>
<span class="n">blur</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">add_task</span><span class="p">(</span><span class="n">ik</span><span class="o">.</span><span class="n">ocv_blur</span><span class="p">(</span><span class="n">kSizeWidth</span><span class="o">=</span><span class="s2">"61"</span><span class="p">,</span> <span class="n">kSizeHeight</span><span class="o">=</span><span class="s2">"61"</span><span class="p">),</span> <span class="n">auto_connect</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># Run on your image </span>
<span class="c1"># wf.run_on(path="path/to/your/image.png")</span>
<span class="n">wf</span><span class="o">.</span><span class="n">run_on</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">"https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_people.jpg"</span><span class="p">)</span>
<span class="c1"># Inspect your results</span>
<span class="n">display</span><span class="p">(</span><span class="n">face</span><span class="o">.</span><span class="n">get_image_with_graphics</span><span class="p">())</span>
<span class="n">display</span><span class="p">(</span><span class="n">blur</span><span class="o">.</span><span class="n">get_output</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
</pre></div>
</div>
</section>
<section id="id9">
<h3>Results<a class="headerlink" href="#id9" title="Link to this heading">¶</a></h3>
<div class="table-wrapper colwidths-auto docutils container">
<table class="docutils align-default">
<thead>
<tr class="row-odd"><th class="head text-center"><p>Kornia Face Detector</p></th>
<th class="head text-center"><p>Blurred faces</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td class="text-center"><p><img alt="" src="_images/img_face.jpg" /></p></td>
<td class="text-center"><p><img alt="" src="_images/img_blur.jpg" /></p></td>
</tr>
</tbody>
</table>
</div>
</section>
</section>
<section id="advanced-usage-export-results-to-json">
<h2>Advanced usage : export results to JSON<a class="headerlink" href="#advanced-usage-export-results-to-json" title="Link to this heading">¶</a></h2>
<section id="id10">
<h3>Code<a class="headerlink" href="#id10" title="Link to this heading">¶</a></h3>
<p>Create and run your workflow.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">ikomia.dataprocess.workflow</span> <span class="kn">import</span> <span class="n">Workflow</span>
<span class="kn">from</span> <span class="nn">ikomia.utils</span> <span class="kn">import</span> <span class="n">ik</span>
<span class="c1"># Init your workflow</span>
<span class="n">wf</span> <span class="o">=</span> <span class="n">Workflow</span><span class="p">()</span>
<span class="c1"># Add the YOLO v7 Object Detector</span>
<span class="n">yolov7</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">add_task</span><span class="p">(</span><span class="n">ik</span><span class="o">.</span><span class="n">infer_yolo_v7</span><span class="p">(),</span> <span class="n">auto_connect</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># Run on your image</span>
<span class="c1"># wf.run_on(path="path/to/your/image.png")</span>
<span class="n">wf</span><span class="o">.</span><span class="n">run_on</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">"https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_work.jpg"</span><span class="p">)</span>
<span class="c1"># Get results as JSON</span>
<span class="n">results_json</span> <span class="o">=</span> <span class="n">yolov7</span><span class="o">.</span><span class="n">get_results</span><span class="p">()</span><span class="o">.</span><span class="n">to_json</span><span class="p">([</span><span class="s2">"json_format"</span><span class="p">,</span> <span class="s2">"indented"</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="n">results_json</span><span class="p">)</span>
</pre></div>
</div>
<p>For a step by step explanation, see <a class="reference internal" href="advanced_guide/index.html"><span class="doc std std-doc">here</span></a>.</p>
</section>
<section id="id11">
<h3>Results<a class="headerlink" href="#id11" title="Link to this heading">¶</a></h3>
<div class="highlight-zsh notranslate"><div class="highlight"><pre><span></span><span class="o">{</span>
<span class="w"> </span><span class="s2">"detections"</span>:<span class="w"> </span><span class="o">[</span>
<span class="w"> </span><span class="o">{</span>
<span class="w"> </span><span class="s2">"box"</span>:<span class="w"> </span><span class="o">{</span>
<span class="w"> </span><span class="s2">"height"</span>:<span class="w"> </span><span class="m">235</span>.06271362304688,
<span class="w"> </span><span class="s2">"width"</span>:<span class="w"> </span><span class="m">286</span>.51531982421875,
<span class="w"> </span><span class="s2">"x"</span>:<span class="w"> </span><span class="m">853</span>.1284790039062,
<span class="w"> </span><span class="s2">"y"</span>:<span class="w"> </span><span class="m">374</span>.7386779785156
<span class="w"> </span><span class="o">}</span>,
<span class="w"> </span><span class="s2">"color"</span>:<span class="w"> </span><span class="o">{</span>
<span class="w"> </span><span class="s2">"a"</span>:<span class="w"> </span><span class="m">9</span>,
<span class="w"> </span><span class="s2">"b"</span>:<span class="w"> </span><span class="m">50</span>,
<span class="w"> </span><span class="s2">"g"</span>:<span class="w"> </span><span class="m">99</span>,
<span class="w"> </span><span class="s2">"r"</span>:<span class="w"> </span><span class="m">232</span>
<span class="w"> </span><span class="o">}</span>,
<span class="w"> </span><span class="s2">"confidence"</span>:<span class="w"> </span><span class="m">0</span>.9322412014007568,
<span class="w"> </span><span class="s2">"id"</span>:<span class="w"> </span><span class="m">0</span>,
<span class="w"> </span><span class="s2">"label"</span>:<span class="w"> </span><span class="s2">"laptop"</span>
<span class="w"> </span><span class="o">}</span>
<span class="w"> </span><span class="o">]</span>
<span class="o">}</span>
</pre></div>
</div>
</section>
</section>
<hr class="docutils" />
<section id="advanced-usage-export-workflow-to-json">
<h2>Advanced usage : export workflow to JSON<a class="headerlink" href="#advanced-usage-export-workflow-to-json" title="Link to this heading">¶</a></h2>
<section id="id12">
<h3>Code<a class="headerlink" href="#id12" title="Link to this heading">¶</a></h3>
<p>Create and export your workflow as JSON.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">ikomia.dataprocess.workflow</span> <span class="kn">import</span> <span class="n">Workflow</span>
<span class="kn">from</span> <span class="nn">ikomia.utils</span> <span class="kn">import</span> <span class="n">ik</span>
<span class="c1"># Init your workflow</span>
<span class="n">wf</span> <span class="o">=</span> <span class="n">Workflow</span><span class="p">(</span><span class="s2">"My workflow"</span><span class="p">)</span>
<span class="c1"># Add the YOLO v7 Object Detector</span>
<span class="n">yolov7</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">add_task</span><span class="p">(</span><span class="n">ik</span><span class="o">.</span><span class="n">infer_yolo_v7</span><span class="p">(),</span> <span class="n">auto_connect</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># Save your workflow as JSON in the current folder or specify a path</span>
<span class="c1"># wf.save("/path/to/my_workflow.json")</span>
<span class="n">wf</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s2">"./my_workflow.json"</span><span class="p">)</span>
</pre></div>
</div>
<p>Then just load and run your workflow.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">ikomia.dataprocess</span> <span class="kn">import</span> <span class="n">workflow</span>
<span class="kn">from</span> <span class="nn">ikomia.utils</span> <span class="kn">import</span> <span class="n">ik</span>
<span class="kn">from</span> <span class="nn">ikomia.utils.displayIO</span> <span class="kn">import</span> <span class="n">display</span>
<span class="c1"># Load your workflow from the current folder or specify a path</span>
<span class="c1"># wf = workflow.load("/path/to/my_workflow.json")</span>
<span class="n">wf</span> <span class="o">=</span> <span class="n">workflow</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="s2">"./my_workflow.json"</span><span class="p">)</span>
<span class="c1"># Run on your image</span>
<span class="c1"># wf.run_on(path="path/to/your/image.png")</span>
<span class="n">wf</span><span class="o">.</span><span class="n">run_on</span><span class="p">(</span><span class="n">url</span><span class="o">=</span><span class="s2">"https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_work.jpg"</span><span class="p">)</span>
<span class="c1"># Find all tasks with the name 'infer_yolo_v7' in the workflow</span>
<span class="c1"># and store them in a list</span>
<span class="c1"># yolov7_list = wf.find_task("infer_yolo_v7")</span>
<span class="n">yolov7_list</span> <span class="o">=</span> <span class="n">wf</span><span class="o">.</span><span class="n">find_task</span><span class="p">(</span><span class="n">ik</span><span class="o">.</span><span class="n">infer_yolo_v7</span><span class="o">.</span><span class="n">name</span><span class="p">())</span>
<span class="n">yolov7</span> <span class="o">=</span> <span class="n">yolov7_list</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="c1"># Inspect your results</span>
<span class="n">display</span><span class="p">(</span><span class="n">yolov7</span><span class="o">.</span><span class="n">get_input</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">get_image</span><span class="p">())</span>
<span class="n">display</span><span class="p">(</span><span class="n">yolov7</span><span class="o">.</span><span class="n">get_image_with_graphics</span><span class="p">())</span>
</pre></div>
</div>
<p>For a step by step explanation, see <a class="reference internal" href="advanced_guide/index.html"><span class="doc std std-doc">here</span></a>.</p>
</section>
<section id="id13">
<h3>Results<a class="headerlink" href="#id13" title="Link to this heading">¶</a></h3>
<div class="table-wrapper colwidths-auto docutils container">
<table class="docutils align-default">
<thead>
<tr class="row-odd"><th class="head text-center"><p>Source image</p></th>
<th class="head text-center"><p>YOLO v7 Object Detector</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td class="text-center"><p><img alt="" src="_images/img_work.jpg" /></p></td>
<td class="text-center"><p><img alt="" src="_images/img_yolo.jpg" /></p></td>
</tr>
</tbody>
</table>
</div>
</section>
</section>
<section id="conclusion">
<h2>Conclusion<a class="headerlink" href="#conclusion" title="Link to this heading">¶</a></h2>
<p>Congratulations! You’ve reached the end of the quickstart guide.
You should now have a good understanding of how to use Ikomia API to create, customize and run workflows with various algorithms.
Feel free to explore more features and create your own amazing workflows!</p>
</section>
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<ul>
<li><a class="reference internal" href="#">Getting Started</a><ul>
<li><a class="reference internal" href="#installation">Installation</a><ul>
<li><a class="reference internal" href="#installing-ikomia-api">Installing Ikomia API</a></li>
</ul>
</li>
<li><a class="reference internal" href="#pre-requisites">Pre-requisites</a></li>
<li><a class="reference internal" href="#basic-usage-workflow-with-1-algorithm">Basic usage : workflow with 1 algorithm</a><ul>
<li><a class="reference internal" href="#workflow-structure">Workflow Structure</a></li>
<li><a class="reference internal" href="#code">Code</a></li>
<li><a class="reference internal" href="#results">Results</a></li>
</ul>
</li>
<li><a class="reference internal" href="#basic-usage-workflow-with-1-algorithm-from-ikomia-hub">Basic usage : workflow with 1 algorithm from Ikomia HUB</a><ul>
<li><a class="reference internal" href="#id1">Workflow Structure</a></li>
<li><a class="reference internal" href="#id2">Code</a></li>
<li><a class="reference internal" href="#id3">Results</a></li>
</ul>
</li>
<li><a class="reference internal" href="#advanced-usage-workflow-with-1-algorithm-custom-settings">Advanced usage : workflow with 1 algorithm + custom settings</a><ul>
<li><a class="reference internal" href="#id4">Workflow Structure</a></li>
<li><a class="reference internal" href="#id5">Code</a></li>
<li><a class="reference internal" href="#id6">Results</a></li>
</ul>
</li>
<li><a class="reference internal" href="#advanced-usage-workflow-with-2-algorithms-custom-settings">Advanced usage : workflow with 2 algorithms + custom settings</a><ul>
<li><a class="reference internal" href="#id7">Workflow Structure</a></li>
<li><a class="reference internal" href="#id8">Code</a></li>
<li><a class="reference internal" href="#id9">Results</a></li>
</ul>
</li>
<li><a class="reference internal" href="#advanced-usage-export-results-to-json">Advanced usage : export results to JSON</a><ul>
<li><a class="reference internal" href="#id10">Code</a></li>
<li><a class="reference internal" href="#id11">Results</a></li>
</ul>
</li>
<li><a class="reference internal" href="#advanced-usage-export-workflow-to-json">Advanced usage : export workflow to JSON</a><ul>
<li><a class="reference internal" href="#id12">Code</a></li>
<li><a class="reference internal" href="#id13">Results</a></li>
</ul>
</li>
<li><a class="reference internal" href="#conclusion">Conclusion</a></li>
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