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Landing page update #5

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34195f1
landing page update
cat-liu Nov 21, 2023
dfb9145
Adding new files
nharada1 Nov 22, 2023
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230 changes: 117 additions & 113 deletions docs/index.html
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@@ -1,126 +1,130 @@
<!DOCTYPE html>
<html>
<html lang="en">
<head>
<title>Zeroshot</title>
<link href="https://cdnjs.cloudflare.com/ajax/libs/prism/1.25.0/themes/prism-okaidia.min.css" rel="stylesheet" />
<link href="https://fonts.googleapis.com/css2?family=Roboto:wght@300;400;500&display=swap" rel="stylesheet">
<style>
body {
font-family: 'Roboto', sans-serif;
background-color: #1a1a1a;
color: #f5f5f5;
padding: 20px;
line-height: 1.6;
}
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<link rel="stylesheet" href="styles.css">

h1 {
font-size: 3em;
}

.container {
width: 60%;
margin: auto;
text-align: left;
}

.center {
text-align: center;
}

.steps {
margin-top: 2em;
}

.step-box {
background-color: #2c2c2c;
padding: 20px;
border-radius: 5px;
margin-bottom: 2em;
}

.button {
background-color: #27ae60;
border: none;
color: white;
padding: 15px 32px;
text-align: center;
text-decoration: none;
display: inline-block;
font-size: 16px;
margin: 4px 2px;
cursor: pointer;
transition: background-color 0.3s ease;
}

.button:hover {
background-color: #2ecc71;
}

a {
color: rgb(0, 98, 255);
}

a:visited {
color: rgb(0, 98, 255);
}

a.button:visited {
color: white;
}

img {
max-width: 100%;
}

.code-container {
background-color: #2c2c2c;
padding: 20px;
border-radius: 5px;
}

.code-container pre {
margin-top: 0;
margin-bottom: 0;
}
</style>
<link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0-beta3/css/all.min.css" rel="stylesheet">
<link href="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/themes/prism-tomorrow.min.css" rel="stylesheet" />
<title>zeroshot</title>
</head>
<body>
<div class="container">
<div class="center">
<h1>Zeroshot</h1>
<p>Like if GPT+Images had a baby brother. Check out our <a href="https://github.com/moonshinelabs-ai/zeroshot-python">Github</a>.</p>
</div>

<div class="steps">
<div class="step-box">
<h2>Step 1: Make image categories by describing them with text.</h2>
<div class="center">
<a href="https://usezeroshot.com" class="button">Create a Classifier in 60 Seconds</a>
</div>
<p>See our <a href="https://github.com/moonshinelabs-ai/zeroshot-python/blob/main/docs/getting_started.md">getting started</a> page for more detailed instructions.</p>
</div>

<div class="step-box">
<h2>Step 2: Use our code to automatically categorize new images.</h2>
<div class="center">
<div class="code-container">
<pre><code class="language-python">
model = zeroshot.Classifier(
"your model key here"
)
<!-- <header>
code for menu nav will be here
</header> -->

<main>
<div class="content">
<!-- landing page hero -->
<div class="hero-container">
<div class="hero-text-container">
<div class="hero-left">
<p class="hero-title">Harness the power of text to add computer vision to your app in minutes</p>
<p class="hero-subtext">Zeroshot is an open source tool for developers that creates image classifiers
from text descriptions</p>
<div class="hero-buttons">
<button class="try-button"> Try it out</button>
<button class="github-button">Github</button>
</div>
</div>
</div>

result = model.predict(url_or_ndarray)
class_name = model.classes[result]
<!-- show examples of image classification with gif -->
<div class="gif-container">
<img src="images/placeholder-image.png" class="hero-gif"/>
</div>
</div>
<!-- feature section -->
<div class="features-container">
<div class="feature-item">
<h3>Open Source</h3>
<p>Zeroshot is a free, community-driven product for versatile applications.</p>
<i class="fa fa-user-group feature-logo"></i>
</div>
<div class="feature-item">
<h3>Low Latency</h3>
<p>Fast and efficient real-time image classification. More accurate and faster than CLIP.</p>
<i class="fa fa-gauge-high feature-logo"></i>
</div>
<div class="feature-item">
<h3>Offline Access</h3>
<p>No internet required, you can use Zeroshot and deploy from anywhere, anytime.</p>
<i class="fa fa-globe feature-logo"></i>
</div>
</div>
<!-- video example -->
<div class="video-example-section">
<div class="video-container">
<img src="images/placeholder-image.png" class="video-example" />
</div>
<div class="video-text-container">
<p>Build a classifier <span class="highlight">in seconds</span>, with no labeling required.</p>
</div>
</div>
<!-- code example -->
<div class="code-example-section">
<div class="description-container">
<p>Deploy to CPU or GPU easily with a <span class="highlight">few lines of code</span></p>
</div>
<div class="code-container">
<pre>
<code class="language-py">
import zeroshot

# Create the classifier and preprocessing function.
classifier = zeroshot.Classifier(
"your model string or path"
)
preprocess_fn = zeroshot.create_preprocess_fn()

# Run the model! The result is the index of the prediction.
prediction = classifier.predict(preprocess_fn(image))
print(f"The image is class {prediction}")
</code>
</pre>
</div>
</div>
<!-- performance example -->
<div class="performance-section">
<div class="performance-chart-container">
<img src="images/placeholder-image.png" class="video-example" />
</div>
<div class="performance-text-container">
<p><span class="highlight">Save costs</span> with a fast, local model that doesn't cost money each time it's run.</p>
</div>
</div>

print(f'Prediction: "{class_name}"')
</code></pre>
</div>
<!-- update with svg files later when have time -->
<div class="how-container">
<p class="how-to-title">How it works</p>
<div class="how-to-box">
<img src="images/model_training.png" class="how-to-icon" />
<p class="how-to-text">Train your model</p>
</div>
<div class="how-to-box">
<img src="images/download.png" class="how-to-icon" />
<p class="how-to-text">Install Zeroshot</p>
</div>
<div class="how-to-box">
<img src="images/create_new_folder.png" class="how-to-icon" />
<p class="how-to-text">Import Zeroshot</p>
</div>
<div class="how-to-box">
<img src="images/widgets.png" class="how-to-icon" />
<p class="how-to-text">Use with your custom model</p>
</div>
<div class="how-to-box">
<button class="trainmodel-button">Train your custom model ></button>
</div>
</div>
</div>
</div>
</main>

<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.25.0/prism.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.25.0/components/prism-python.min.js"></script>
<!-- <footer>
code for footer
</footer> -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/prism.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/plugins/autoloader/prism-autoloader.min.js"></script>
</body>
</html>
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