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332 lines
18 KiB
HTML
332 lines
18 KiB
HTML
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<!doctype html>
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
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<meta name="description" content="">
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<meta name="author" content="">
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<!--<link rel="icon" href="../../../../favicon.ico">-->
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<title>Gradio: An Interactive Demo for Your Trained ML Model</title>
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<body>
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<nav class="navbar navbar-expand-md navbar-light fixed-top" style="background-color: #e3f2fd">
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<a class="navbar-brand" href="#" style="font-weight:bold">Gradio</a>
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<li class="nav-item " style="font-weight:500; font-decoration:none">
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<a class="nav-link" href="http://www.siliconprep.com"><em>A Silicon Prep Tool</em></a>
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<main role="main">
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<section class="jumbotron text-center">
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<div class="container">
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<h1 class="jumbotron-heading">Gradio</h1>
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<p class="lead text-muted" style="font-weight:400 !important">Put a beautiful interactive demo layer over your trained ML model.</p>
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<p>
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<a href="#" class="btn btn-lg btn-pink my-2">Get started</a>
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<a href="#" class="btn btn-lg btn-primary my-2">See examples</a>
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<a href="#" class="btn btn-lg btn-secondary my-2">Github</a>
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</p>
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</div>
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</section>
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<div class="album py-5 bg-light">
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<div class="container">
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<h1>Getting started</h1>
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<p>
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Gradio (gradient input-output) is a python library that allows you to easily transform your trained model into a webpage that easily allows you to interface with it. This allows you to:
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<ul>
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<li>Show off the model to others</li>
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<li>Identify response to unusual behavior</li>
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<li>Encourage fairness and reproducibility of your model</li>
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</ul>
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Gradio is designed to be very simple to use. For example, in just 2 lines of Python code, you can create a sketchpad that allows you write digits and see whether your MNIST model can correctly identify them.
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</p>
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<h4> Installation </h4>
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<p> Gradio is a standard python library, so install it from your terminal like this:
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<div class="codebox">
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<code>
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pip install gradio
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</code>
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</div>
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</p>
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<h4> Usage </h4>
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<p> To use gradio in your code, simply import it, and then launch the appropriate interface
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<div class="codebox">
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<code>
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import gradio <br>
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import tensorflow as tf <br> <br>
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model = tf.keras.Sequential() <br>
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# Define your model, as you ordinarily do <br>
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# Train your model, as you ordinarily do <br> <br>
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gradio.interfaces.Sketchpad(model=model, model_type='keras').launch()
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</code>
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</div>
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</p>
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This will open a new browser window which will allow you to draw into a "sketchpad". Behind the scenes, gradio transforms the user drawing into a numeric array and passes it into your model for your prediction.
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Then, gradio will fetch the result and show it to the user. Like this:
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<br> <br>
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Currently, the following <code>model_type</code> are supported:
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<ul>
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<li>Keras models</li>
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<li>Sklearn models</li>
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<li>Arbitrary python functions</li>
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</ul>
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See the gallery of interfaces below to see what kind of interfaces can be supported. Contribute your own interfaces by visiting our GitHub page.
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<hr>
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<h1>Gallery of Interfaces</h1>
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<div class="row">
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<div class="col-md-4">
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<div class="card mb-4 shadow-sm">
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<img class="card-img-top" src="img/draw-a-digit.png" alt="Card image cap">
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<div class="card-body">
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<p class="card-text"><strong>Draw a Digit</strong>: allow users to draw their own digits to test MNIST-type models.</p>
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<div class="d-flex justify-content-between align-items-center">
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<div class="btn-group">
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<button type="button" class="btn btn-sm btn-outline-secondary" onclick="location.href='templates/draw_a_digit.html';">View</button>
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<button type="button" class="btn btn-sm btn-outline-secondary" onclick="location.href='https://github.com/abidlabs/gradiome/blob/master/templates/draw_a_digit.html';">Source</button>
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</div>
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<small class="text-muted"></small>
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</div>
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</div>
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</div>
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</div>
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<div class="col-md-4">
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<div class="card mb-4 shadow-sm">
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<img class="card-img-top" src="img/placeholder.png" alt="Card image cap">
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<div class="card-body">
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<p class="card-text"><strong>Emotion Detector</strong>: allow users to make emotions through their webcam and detect their emotion with your model.</p>
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<div class="d-flex justify-content-between align-items-center">
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<div class="btn-group">
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<button type="button" class="btn btn-sm btn-outline-secondary" onclick="location.href='templates/emotion_detector.html';">View</button>
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<button type="button" class="btn btn-sm btn-outline-secondary">Source</button>
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</div>
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<small class="text-muted"></small>
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</div>
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</div>
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</div>
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</div>
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<div class="col-md-4">
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<div class="card mb-4 shadow-sm">
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<img class="card-img-top" src="img/placeholder.png" alt="Card image cap">
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<div class="card-body">
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<p class="card-text"><strong>Automated Author</strong>: use an RNN to generate a sequence of words beginning the words that the user has supplied</p>
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<div class="d-flex justify-content-between align-items-center">
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<div class="btn-group">
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<button type="button" class="btn btn-sm btn-outline-secondary">View</button>
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<button type="button" class="btn btn-sm btn-outline-secondary">Source</button>
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</div>
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<small class="text-muted"></small>
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</div>
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</div>
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</div>
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</div>
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<!--<img class="card-img-top" src="img/placeholder.png" alt="Card image cap">-->
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<!--<div class="card-body">-->
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<!--<p class="card-text"><strong>Image Blender</strong>: use an GAN to generate a sequence of images imputed between two images that the user has supplied.</p>-->
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<!--<div class="d-flex justify-content-between align-items-center">-->
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<!--<div class="btn-group">-->
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<!--<button type="button" class="btn btn-sm btn-outline-secondary">View</button>-->
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<!--<small class="text-muted">9 mins</small>-->
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<!--<button type="button" class="btn btn-sm btn-outline-secondary">View</button>-->
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<!--<small class="text-muted">9 mins</small>-->
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<!--<img class="card-img-top" data-src="holder.js/100px225?theme=thumb&bg=55595c&fg=eceeef&text=Thumbnail" alt="Card image cap">-->
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<!--<div class="card-body">-->
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<!--<p class="card-text">This is a wider card with supporting text below as a natural lead-in to additional content. This content is a little bit longer.</p>-->
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<!--<div class="d-flex justify-content-between align-items-center">-->
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<!--<button type="button" class="btn btn-sm btn-outline-secondary">View</button>-->
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<!--<button type="button" class="btn btn-sm btn-outline-secondary">Source</button>-->
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<!--<small class="text-muted">9 mins</small>-->
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<!--</div>-->
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<!--<div class="card mb-4 shadow-sm">-->
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<!--<img class="card-img-top" data-src="holder.js/100px225?theme=thumb&bg=55595c&fg=eceeef&text=Thumbnail" alt="Card image cap">-->
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<!--<div class="card-body">-->
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<!--<p class="card-text">This is a wider card with supporting text below as a natural lead-in to additional content. This content is a little bit longer.</p>-->
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<!--<div class="d-flex justify-content-between align-items-center">-->
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<!--<button type="button" class="btn btn-sm btn-outline-secondary">View</button>-->
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<!--<button type="button" class="btn btn-sm btn-outline-secondary">Source</button>-->
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</main>
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<!-- Add font awesome icons -->
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Gradio is open-source, help make it better
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<a href="https://github.com/abidlabs/gradiome" target="_blank" class="fa fa-github"></a>
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</span>
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