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Initial commit for OmniLottie project page
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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env/
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venv/
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ENV/
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*.py
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# OS
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||||
.DS_Store
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.DS_Store?
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||||
._*
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.Spotlight-V100
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||||
.Trashes
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ehthumbs.db
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Thumbs.db
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||||
# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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||||
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# Logs
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||||
*.log
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# Temporary files
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*.tmp
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*.bak
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||||
*.swp
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# Documentation and scripts (不上传到GitHub Pages)
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||||
*.md
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||||
*.sh
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||||
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||||
# Backup
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||||
.git.bak/
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||||
# Don't ignore these important files
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!static/css/index.css
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!static/js/index.js
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<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8">
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<meta name="description" content="OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens</title>
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||||
<link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro" rel="stylesheet">
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||||
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/css/bootstrap.min.css"/>
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<link rel="stylesheet" href="./static/css/bulma.min.css">
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||||
<link rel="stylesheet" href="./static/css/bulma-carousel.min.css">
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<link rel="stylesheet" href="./static/css/bulma-slider.min.css">
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||||
<link rel="stylesheet" href="./static/css/fontawesome.all.min.css">
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||||
<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css">
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<link rel="stylesheet" href="./static/css/index.css">
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<link rel="icon" href="./static/images/lottie_icon.png"/>
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<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.6.4/jquery.min.js"></script>
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<script defer src="./static/js/fontawesome.all.min.js"></script>
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<script src="./static/js/bulma-slider.min.js"></script>
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<script src="./static/js/index.js"></script>
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||||
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.1/js/bootstrap.min.js"></script>
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||||
|
||||
<style>
|
||||
body {
|
||||
margin: auto;
|
||||
font-family: Arial, sans-serif;
|
||||
}
|
||||
|
||||
nav {
|
||||
position: auto;
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||||
top: 0;
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||||
left: 0;
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||||
width: 100%;
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||||
background-color: ghostwhite;
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z-index: 100;
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||||
box-shadow: 0px 3px 5px rgba(0, 0, 0, 0.3);
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}
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nav ul {
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padding: 0;
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margin: auto;
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||||
list-style: none;
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||||
display: flex;
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||||
justify-content: center;
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}
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||||
|
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nav ul li {
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||||
margin: auto;
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}
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||||
nav ul li a {
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display: block;
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||||
padding: 5px;
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||||
text-decoration: none;
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||||
transition: background-color 0.3s;
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||||
}
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||||
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||||
nav ul li a:hover {
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||||
background-color: #555;
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}
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||||
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||||
.title {
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||||
font-size: 41px;
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}
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||||
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||||
.teaserTitle {
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||||
font-size: 76px;
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}
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||||
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.subTeaserTitle {
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font-size: 15px;
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}
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||||
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.carousel-indicators {
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bottom: -26px;
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}
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.carousel-control.left,
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.carousel-control.right {
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background-image: none !important;
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filter: none !important;
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||||
width: 20px;
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||||
}
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||||
|
||||
.columns {
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||||
display: flex;
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||||
flex-wrap: wrap;
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||||
}
|
||||
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||||
.column {
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||||
flex: 1;
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min-width: 150px;
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||||
}
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||||
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||||
.carousel-indicators ol {
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||||
width: 100%;
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||||
}
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||||
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.carousel-indicators li {
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||||
height: 3px !important;
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||||
border-radius: 0px !important;
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width: 25%;
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}
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||||
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||||
.render_wrapper {
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||||
position: relative;
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height: 300px;
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||||
}
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||||
|
||||
.render_wrapper_small {
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||||
position: relative;
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||||
height: 200px;
|
||||
}
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||||
|
||||
.render_div {
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||||
position: absolute;
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||||
top: 0;
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||||
left: 0;
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||||
}
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||||
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||||
#interpolation-image-wrapper-car {
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text-align: center;
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||||
}
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||||
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||||
#interpolation-image-wrapper-chair {
|
||||
text-align: center;
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||||
}
|
||||
|
||||
.nested-columns {
|
||||
margin-bottom: 0 !important;
|
||||
}
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||||
|
||||
.task-icon {
|
||||
font-size: 1.2em;
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||||
margin-right: 8px;
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||||
}
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||||
|
||||
.highlight-box {
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||||
background: linear-gradient(135deg, #b39ddb 0%, #9575cd 100%);
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||||
border-radius: 10px;
|
||||
padding: 20px;
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||||
margin: 10px 0;
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||||
color: white;
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||||
}
|
||||
|
||||
.feature-card {
|
||||
border: 1px solid #e0e0e0;
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||||
border-radius: 8px;
|
||||
padding: 15px;
|
||||
margin: 10px;
|
||||
transition: box-shadow 0.3s;
|
||||
}
|
||||
|
||||
.feature-card:hover {
|
||||
box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
|
||||
<body>
|
||||
|
||||
<section class="hero">
|
||||
<div class="hero-body">
|
||||
<div class="container is-max-desktop">
|
||||
<div class="columns is-centered">
|
||||
<div class="column has-text-centered">
|
||||
<h1 class="title is-0 publication-title">
|
||||
OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens <br/>
|
||||
</h1>
|
||||
|
||||
<style>
|
||||
.neurips-text {
|
||||
color: #b39ddb; /* 浅紫色 - 与OmniSVG一致 */
|
||||
font-size: 30px;
|
||||
font-weight: bold;
|
||||
text-align: center;
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||||
margin-top: 10px;
|
||||
}
|
||||
</style>
|
||||
|
||||
<div class="neurips-text">
|
||||
NeurIPS 2025
|
||||
</div>
|
||||
|
||||
<div class="is-size-4 publication-authors">
|
||||
<span class="author-block">
|
||||
<a href="#">Author 1</a><sup>1,2*</sup>,</span>
|
||||
<span class="author-block">
|
||||
<a href="#">Author 2</a><sup>2*</sup>,</span>
|
||||
<span class="author-block">
|
||||
<a href="#">Author 3</a><sup>1</sup>,</span>
|
||||
<span class="author-block">
|
||||
<a href="#">Author 4</a><sup>2</sup>,</span>
|
||||
<span class="author-block">
|
||||
<a href="#">Author 5</a><sup>1</sup>,</span>
|
||||
</div>
|
||||
<div class="is-size-4 publication-authors">
|
||||
<span class="author-block">
|
||||
<a href="#">Author 6</a><sup>2</sup>,</span>
|
||||
<span class="author-block">
|
||||
<a href="#">Author 7</a><sup>2</sup>,</span>
|
||||
<span class="author-block">
|
||||
<a href="#">Author 8</a><sup>2‡</sup>,</span>
|
||||
<span class="author-block">
|
||||
<a href="#">Author 9</a><sup>1‡</sup>,</span>
|
||||
<span class="author-block">
|
||||
<a href="#">Author 10</a><sup>1</sup></span>
|
||||
</div>
|
||||
<div class="is-size-5 publication-authors">
|
||||
<span class="author-block"><sup>*</sup>Equal Contribution,</span>
|
||||
<span class="author-block"><sup>‡</sup>Correspondence Authors</span>
|
||||
</div>
|
||||
<div class="is-size-5 publication-authors">
|
||||
<span class="author-block"><sup>1</sup>Fudan University,</span>
|
||||
<span class="author-block"><sup>2</sup>StepFun</span>
|
||||
</div>
|
||||
|
||||
<div class="column has-text-centered">
|
||||
<div class="publication-links">
|
||||
<!-- arXiv Link -->
|
||||
<span class="link-block">
|
||||
<a class="external-link button is-normal is-rounded is-dark" href="#">
|
||||
<span class="icon">
|
||||
<i class="ai ai-arxiv"></i>
|
||||
</span>
|
||||
<span>arXiv</span>
|
||||
</a>
|
||||
</span>
|
||||
|
||||
<!-- Github Link -->
|
||||
<span class="link-block">
|
||||
<a href="#" class="external-link button is-normal is-rounded is-dark">
|
||||
<span class="icon">
|
||||
<i class="fab fa-github" style="color: white;"></i>
|
||||
</span>
|
||||
<span>Code</span>
|
||||
</a>
|
||||
</span>
|
||||
|
||||
<!-- Weights Link -->
|
||||
<span class="link-block">
|
||||
<a href="#" class="external-link button is-normal is-rounded is-dark">
|
||||
<span class="icon">
|
||||
<img src="https://huggingface.co/front/assets/huggingface_logo.svg" alt="Hugging Face Logo" style="width: 20px; height: 20px;">
|
||||
</span>
|
||||
<span>Weights</span>
|
||||
</a>
|
||||
</span>
|
||||
|
||||
<!-- Dataset Link -->
|
||||
<span class="link-block">
|
||||
<a href="#" class="external-link button is-normal is-rounded is-dark">
|
||||
<span class="icon">
|
||||
<img src="https://huggingface.co/front/assets/huggingface_logo.svg" alt="Hugging Face Logo" style="width: 20px; height: 20px;">
|
||||
</span>
|
||||
<span>MMLottie-2M Dataset</span>
|
||||
</a>
|
||||
</span>
|
||||
|
||||
<!-- Demo Link -->
|
||||
<span class="link-block">
|
||||
<a href="#" class="external-link button is-normal is-rounded is-dark">
|
||||
<span class="icon">
|
||||
<i class="fas fa-play"></i>
|
||||
</span>
|
||||
<span>Demo</span>
|
||||
</a>
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- Banner Video -->
|
||||
<section class="section">
|
||||
<div class="container is-max-desktop">
|
||||
<div class="columns is-centered has-text-centered" style="margin-top: -20px">
|
||||
<video src="./assets/OmniLottie-main-demo.mp4" width="100%" autoplay loop muted playsinline></video>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- Abstract -->
|
||||
<section class="section">
|
||||
<div class="container is-max-desktop">
|
||||
<div class="columns is-centered has-text-centered" style="margin-top: -80px">
|
||||
<div class="column is-four-fifths">
|
||||
<h2 class="title is-2">Abstract</h2>
|
||||
<div class="content has-text-justified">
|
||||
<p>
|
||||
<b>OmniLottie</b> is a versatile framework that generates high-quality vector animations from multi-modal instructions.
|
||||
For flexible motion and visual content control, we focus on Lottie, a light-weight JSON formatting for both shapes and animation behaviors representation.
|
||||
However, the raw Lottie JSON files contain extensive invariant structural metadata and formatting tokens, posing significant challenges for learning vector animation generation.
|
||||
Therefore, we introduce a well-designed <b>Lottie tokenizer</b> that transforms JSON files into structured sequences of commands and parameters representing shapes, animation functions and control parameters.
|
||||
Such tokenizer enables us to build OmniLottie upon pretrained vision–language models to follow multi-modal interleaved instructions and generate high-quality vector animations.
|
||||
To further advance research in vector animation generation, we curate <b>MMLottie-2M</b>, a large-scale dataset of professionally designed vector animations paired with textual and visual annotations.
|
||||
With extensive experiments, we validate that OmniLottie can produce vivid and semantically aligned vector animations that adhere closely to multi-modal human instructions.
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- Highlights -->
|
||||
<section class="hero" id="teaser" style="margin-bottom: 50px; margin-top: 50px;">
|
||||
<div class="container is-max-desktop">
|
||||
<div class="columns is-centered" style="margin-top: 15px">
|
||||
<div class="column is-full-width">
|
||||
<h2 class="title is-4">Highlights</h2>
|
||||
<div class="columns is-centered" style="text-align: center">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/OmniLottie-teaser.jpg" alt="OmniLottie Teaser">
|
||||
</div>
|
||||
</div>
|
||||
<div class="content has-text-justified" style="padding-top: 15px">
|
||||
OmniLottie is capable of generating high-quality vector animations across a wide spectrum of complexity — from simple icons to intricate animated illustrations.
|
||||
It demonstrates remarkable versatility through multiple generation modalities, including <b>Text-to-Lottie</b>, <b>Text-Image-to-Lottie</b>, and <b>Video-to-Lottie</b>,
|
||||
making it a powerful and flexible solution for diverse creative and professional animation tasks.
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Method Overview -->
|
||||
<div class="columns is-centered" style="margin-top: 15px">
|
||||
<div class="column is-full-width">
|
||||
<h2 class="title is-4">Method Overview</h2>
|
||||
<div class="columns is-centered" style="text-align: center">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/OmniLottie-pipeline.jpg" alt="OmniLottie Pipeline">
|
||||
</div>
|
||||
</div>
|
||||
<div class="content has-text-justified" style="padding-top: 15px">
|
||||
OmniLottie is built on a pre-trained vision-language model (Qwen2.5-VL) and incorporates a Lottie tokenizer.
|
||||
The model tokenizes both text and image/video inputs as prefix tokens, while the Lottie tokenizer encodes vector animation commands into a unified representation space.
|
||||
The Lottie tokenizer abstracts Lottie animations into compact sequences of animation commands and control parameters, removing redundant metadata while preserving full generative flexibility.
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Lottie Tokenizer Details -->
|
||||
<div class="columns is-centered" style="margin-top: 15px">
|
||||
<div class="column is-full-width">
|
||||
<h2 class="title is-4">Lottie Tokenizer</h2>
|
||||
<div class="columns is-centered" style="text-align: center">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/OmniLottie-tokenizer.jpg" alt="Lottie Tokenizer">
|
||||
</div>
|
||||
</div>
|
||||
<div class="content has-text-justified" style="padding-top: 15px">
|
||||
Our Lottie tokenizer converts raw JSON files into compact sequences of shape, effect, and animation commands with their associated parameters.
|
||||
This representation substantially shortens sequence lengths (81% reduction compared to raw JSON), improves token efficiency, and enables OmniLottie to learn a clean distribution over animation primitives.
|
||||
The tokenizer supports five fundamental layer types: Precomposition, Solid, Null, Shape, and Text layers, each identified by a unique type parameter.
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- Generation Process -->
|
||||
<section class="section">
|
||||
<div class="container is-max-desktop" style="margin-top: 30px;">
|
||||
<h3 class="title is-4">Generation Process of OmniLottie</h3>
|
||||
<div>
|
||||
<section class="section" style="overflow:hidden">
|
||||
<div class="container">
|
||||
<div id="post_images" class="carousel">
|
||||
<div class="item-1">
|
||||
<video poster="" autoplay="" muted loop="" style="pointer-events: none;">
|
||||
<source src="./assets/OmniLottie-demo-text2lottie.mp4" type="video/mp4">
|
||||
</video>
|
||||
<p class="has-text-centered"><b>Text-to-Lottie Generation</b></p>
|
||||
</div>
|
||||
<div class="item-2">
|
||||
<video poster="" autoplay="" muted loop="" style="pointer-events: none;">
|
||||
<source src="./assets/OmniLottie-demo-image2lottie.mp4" type="video/mp4">
|
||||
</video>
|
||||
<p class="has-text-centered"><b>Text-Image-to-Lottie Generation</b></p>
|
||||
</div>
|
||||
<div class="item-3">
|
||||
<video poster="" autoplay="" muted loop="" style="pointer-events: none;">
|
||||
<source src="./assets/OmniLottie-demo-video2lottie.mp4" type="video/mp4">
|
||||
</video>
|
||||
<p class="has-text-centered"><b>Video-to-Lottie Generation</b></p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<script src="https://cdn.jsdelivr.net/npm/bulma-carousel@4.0.3/dist/js/bulma-carousel.min.js"></script>
|
||||
<script>
|
||||
bulmaCarousel.attach('#post_images', {
|
||||
slidesToScroll: 1,
|
||||
slidesToShow: 1,
|
||||
loop: true,
|
||||
});
|
||||
</script>
|
||||
</div>
|
||||
|
||||
<!-- Comparison Results -->
|
||||
<div class="columns is-centered" style="margin-top: 20px">
|
||||
<div class="column is-full-width">
|
||||
<h2 class="title is-4">Comparison with SOTA Methods</h2>
|
||||
|
||||
<h3 class="title is-5">Text-to-Lottie</h3>
|
||||
<div class="content has-text-justified">
|
||||
<p>OmniLottie achieves near-perfect success rates, the best FVD, and the strongest motion alignment compared to baselines including DeepSeek, GPT-4o, and Recraft.</p>
|
||||
</div>
|
||||
<div class="columns is-centered">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/OmniLottie-t2lottie.jpg" alt="Text-to-Lottie Comparison">
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<h3 class="title is-5">Text-Image-to-Lottie</h3>
|
||||
<div class="content has-text-justified">
|
||||
<p>OmniLottie ranks first in FVD, object alignment, and motion alignment while maintaining high reliability. Methods such as AniClipart and LiveSketch exhibit low success rates and significantly longer runtimes.</p>
|
||||
</div>
|
||||
<div class="columns is-centered">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/OmniLottie-ti2lottie.jpg" alt="Text-Image-to-Lottie Comparison">
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<h3 class="title is-5">Video-to-Lottie</h3>
|
||||
<div class="content has-text-justified">
|
||||
<p>OmniLottie preserves temporal and structural fidelity most effectively, achieving the best FVD, PSNR, SSIM, and DINO scores.</p>
|
||||
</div>
|
||||
<div class="columns is-centered">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/OmniLottie-v2lottie.jpg" alt="Video-to-Lottie Comparison">
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Quantitative Results Table -->
|
||||
<div class="columns is-centered" style="margin-top: 20px">
|
||||
<div class="column is-full-width">
|
||||
<h2 class="title is-4">Quantitative Results</h2>
|
||||
<div class="columns is-centered">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/OmniLottie-quantitative-table.jpg" alt="Quantitative Results">
|
||||
</div>
|
||||
</div>
|
||||
<div class="content has-text-justified" style="padding-top: 15px">
|
||||
OmniLottie achieves 97.3%, 92.0%, and 90.7% success rates for Text-to-Lottie, Text-Image-to-Lottie, and Video-to-Lottie tasks respectively,
|
||||
substantially outperforming all baselines while producing richer token sequences that enable more expressive and detailed vector animation generation.
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Dataset Section -->
|
||||
<div class="columns is-centered" style="margin-top: 20px">
|
||||
<div class="column is-full-width">
|
||||
<h3 class="title is-4">MMLottie-2M Dataset</h3>
|
||||
<div class="columns is-centered">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/MMLottie-dataset.jpg" alt="MMLottie-2M Dataset">
|
||||
</div>
|
||||
</div>
|
||||
<div class="content has-text-justified" style="padding-top: 15px">
|
||||
The MMLottie-2M dataset consists of two million Lottie animations paired with multi-modal annotations including text descriptions, keyframe images, and rendered videos.
|
||||
Data is collected from major online platforms (LottieFiles, IconScout, Flaticon, Iconfont, Icons8) and augmented with SVG-derived animations.
|
||||
The dataset undergoes comprehensive processing including Lottie cleaning, spatial-temporal normalization, video rendering, and coarse-to-fine captioning using VLMs.
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Data Pipeline -->
|
||||
<div class="columns is-centered" style="margin-top: 20px">
|
||||
<div class="column is-full-width">
|
||||
<h3 class="title is-4">Data Processing Pipeline</h3>
|
||||
<div class="columns is-centered">
|
||||
<div class="column" style="align-self: center">
|
||||
<img src="./assets/OmniLottie-data-pipeline.jpg" alt="Data Processing Pipeline">
|
||||
</div>
|
||||
</div>
|
||||
<div class="content has-text-justified" style="padding-top: 15px">
|
||||
Our data processing pipeline includes five stages: (1) Data collection from web sources and SVG conversion,
|
||||
(2) Lottie cleaning to remove non-visual and non-parameterizable layers,
|
||||
(3) Spatial-temporal normalization to 512×512 canvas and unified timeline,
|
||||
(4) Video rendering with random backgrounds, and
|
||||
(5) Multi-modal annotation using a coarse-to-fine VLM captioning strategy.
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<br>
|
||||
|
||||
<!-- Related Links -->
|
||||
<div class="columns is-centered">
|
||||
<div class="column is-full-width">
|
||||
<h2 class="title is-3">Related Links</h2>
|
||||
<div class="content has-text-justified">
|
||||
<p>
|
||||
<b>We thank the following excellent open-source works:</b>
|
||||
</p>
|
||||
<p>
|
||||
<a href="https://omnisvg.github.io/"><b>OmniSVG</b></a>: A unified framework for SVG generation that leverages pre-trained VLMs. We build upon its methodology for vector graphics generation.
|
||||
</p>
|
||||
<p>
|
||||
<a href="https://icon-shop.github.io/"><b>IconShop</b></a>: The first work leveraging LLMs to generate monochrome, icon-level SVGs. We referred to its parametric implementation.
|
||||
</p>
|
||||
<p>
|
||||
<b>Concurrent Works:</b>
|
||||
</p>
|
||||
<p>
|
||||
<a href="https://aniclipart.github.io/"><b>AniClipart</b></a>: Animates static clipart using text-to-video diffusion priors.
|
||||
</p>
|
||||
<p>
|
||||
<a href="#"><b>LiveSketch</b></a>: Generates sketch animations through optimization-based approaches.
|
||||
</p>
|
||||
<p>
|
||||
<a href="https://starvector.github.io/"><b>StarVector</b></a>: Equips LLM with an image encoder for Image-to-SVG generation.
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Acknowledgements -->
|
||||
<div class="columns is-centered">
|
||||
<div class="column is-full-width">
|
||||
<h2 class="title is-3">Acknowledgements</h2>
|
||||
<div class="content has-text-justified">
|
||||
<p>
|
||||
We thank all the contributors for dataset construction and valuable discussions.
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- BibTeX -->
|
||||
<section class="section" id="BibTeX">
|
||||
<div class="container is-max-desktop content">
|
||||
<h2 class="title">BibTeX</h2>
|
||||
<pre><code>@article{omnilottie2025,
|
||||
title={OmniLottie: A Unified Scalable Vector Animation Generation Model},
|
||||
author={Author1 and Author2 and Author3 and Author4 and Author5 and Author6 and Author7 and Author8 and Author9 and Author10},
|
||||
journal={arXiv preprint arXiv:XXXX.XXXXX},
|
||||
year={2025}
|
||||
}</code></pre>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
<!-- Footer -->
|
||||
<footer class="footer">
|
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<div class="container">
|
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|
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<div class="column is-8">
|
||||
<div class="content">
|
||||
<p style="text-align:center">
|
||||
Source code mainly borrowed from <a href="https://keunhong.com/">Keunhong Park</a>'s <a href="https://nerfies.github.io/">Nerfies website</a>.
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
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|
||||
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</html>
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||||
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||||
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||||
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||||
_this.init();
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||||
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}
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||||
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||||
/**
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||||
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||||
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||||
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||||
_createClass(bulmaSlider, [{
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||||
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/**
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||||
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||||
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|
||||
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this._bindEvents();
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
}, {
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||||
key: 'onSliderInput',
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||||
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||||
e.preventDefault();
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|
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// Get new output position
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||||
var newPosition = this._getSliderOutputPosition();
|
||||
|
||||
// Set output position
|
||||
this.output.style['left'] = newPosition.position;
|
||||
}
|
||||
|
||||
// Check for prefix and postfix
|
||||
var prefix = this.output.hasAttribute('data-prefix') ? this.output.getAttribute('data-prefix') : '';
|
||||
var postfix = this.output.hasAttribute('data-postfix') ? this.output.getAttribute('data-postfix') : '';
|
||||
|
||||
// Update output with slider value
|
||||
this.output.value = prefix + this.element.value + postfix;
|
||||
|
||||
this.emit('bulmaslider:ready', this.element.value);
|
||||
}
|
||||
}], [{
|
||||
key: 'attach',
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||||
value: function attach() {
|
||||
var _this3 = this;
|
||||
|
||||
var selector = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : 'input[type="range"].slider';
|
||||
var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {};
|
||||
|
||||
var instances = new Array();
|
||||
|
||||
var elements = isString(selector) ? document.querySelectorAll(selector) : Array.isArray(selector) ? selector : [selector];
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||||
elements.forEach(function (element) {
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||||
if (typeof element[_this3.constructor.name] === 'undefined') {
|
||||
var instance = new bulmaSlider(element, options);
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||||
element[_this3.constructor.name] = instance;
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instances.push(instance);
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||||
} else {
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||||
instances.push(element[_this3.constructor.name]);
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||||
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||||
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|
||||
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||||
return instances;
|
||||
}
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||||
}]);
|
||||
|
||||
return bulmaSlider;
|
||||
}(__WEBPACK_IMPORTED_MODULE_0__events__["a" /* default */]);
|
||||
|
||||
/* harmony default export */ __webpack_exports__["default"] = (bulmaSlider);
|
||||
|
||||
/***/ }),
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||||
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function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } }
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var EventEmitter = function () {
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function EventEmitter() {
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var listeners = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : [];
|
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||||
_classCallCheck(this, EventEmitter);
|
||||
|
||||
this._listeners = new Map(listeners);
|
||||
this._middlewares = new Map();
|
||||
}
|
||||
|
||||
_createClass(EventEmitter, [{
|
||||
key: "listenerCount",
|
||||
value: function listenerCount(eventName) {
|
||||
if (!this._listeners.has(eventName)) {
|
||||
return 0;
|
||||
}
|
||||
|
||||
var eventListeners = this._listeners.get(eventName);
|
||||
return eventListeners.length;
|
||||
}
|
||||
}, {
|
||||
key: "removeListeners",
|
||||
value: function removeListeners() {
|
||||
var _this = this;
|
||||
|
||||
var eventName = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : null;
|
||||
var middleware = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : false;
|
||||
|
||||
if (eventName !== null) {
|
||||
if (Array.isArray(eventName)) {
|
||||
name.forEach(function (e) {
|
||||
return _this.removeListeners(e, middleware);
|
||||
});
|
||||
} else {
|
||||
this._listeners.delete(eventName);
|
||||
|
||||
if (middleware) {
|
||||
this.removeMiddleware(eventName);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
this._listeners = new Map();
|
||||
}
|
||||
}
|
||||
}, {
|
||||
key: "middleware",
|
||||
value: function middleware(eventName, fn) {
|
||||
var _this2 = this;
|
||||
|
||||
if (Array.isArray(eventName)) {
|
||||
name.forEach(function (e) {
|
||||
return _this2.middleware(e, fn);
|
||||
});
|
||||
} else {
|
||||
if (!Array.isArray(this._middlewares.get(eventName))) {
|
||||
this._middlewares.set(eventName, []);
|
||||
}
|
||||
|
||||
this._middlewares.get(eventName).push(fn);
|
||||
}
|
||||
}
|
||||
}, {
|
||||
key: "removeMiddleware",
|
||||
value: function removeMiddleware() {
|
||||
var _this3 = this;
|
||||
|
||||
var eventName = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : null;
|
||||
|
||||
if (eventName !== null) {
|
||||
if (Array.isArray(eventName)) {
|
||||
name.forEach(function (e) {
|
||||
return _this3.removeMiddleware(e);
|
||||
});
|
||||
} else {
|
||||
this._middlewares.delete(eventName);
|
||||
}
|
||||
} else {
|
||||
this._middlewares = new Map();
|
||||
}
|
||||
}
|
||||
}, {
|
||||
key: "on",
|
||||
value: function on(name, callback) {
|
||||
var _this4 = this;
|
||||
|
||||
var once = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : false;
|
||||
|
||||
if (Array.isArray(name)) {
|
||||
name.forEach(function (e) {
|
||||
return _this4.on(e, callback);
|
||||
});
|
||||
} else {
|
||||
name = name.toString();
|
||||
var split = name.split(/,|, | /);
|
||||
|
||||
if (split.length > 1) {
|
||||
split.forEach(function (e) {
|
||||
return _this4.on(e, callback);
|
||||
});
|
||||
} else {
|
||||
if (!Array.isArray(this._listeners.get(name))) {
|
||||
this._listeners.set(name, []);
|
||||
}
|
||||
|
||||
this._listeners.get(name).push({ once: once, callback: callback });
|
||||
}
|
||||
}
|
||||
}
|
||||
}, {
|
||||
key: "once",
|
||||
value: function once(name, callback) {
|
||||
this.on(name, callback, true);
|
||||
}
|
||||
}, {
|
||||
key: "emit",
|
||||
value: function emit(name, data) {
|
||||
var _this5 = this;
|
||||
|
||||
var silent = arguments.length > 2 && arguments[2] !== undefined ? arguments[2] : false;
|
||||
|
||||
name = name.toString();
|
||||
var listeners = this._listeners.get(name);
|
||||
var middlewares = null;
|
||||
var doneCount = 0;
|
||||
var execute = silent;
|
||||
|
||||
if (Array.isArray(listeners)) {
|
||||
listeners.forEach(function (listener, index) {
|
||||
// Start Middleware checks unless we're doing a silent emit
|
||||
if (!silent) {
|
||||
middlewares = _this5._middlewares.get(name);
|
||||
// Check and execute Middleware
|
||||
if (Array.isArray(middlewares)) {
|
||||
middlewares.forEach(function (middleware) {
|
||||
middleware(data, function () {
|
||||
var newData = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : null;
|
||||
|
||||
if (newData !== null) {
|
||||
data = newData;
|
||||
}
|
||||
doneCount++;
|
||||
}, name);
|
||||
});
|
||||
|
||||
if (doneCount >= middlewares.length) {
|
||||
execute = true;
|
||||
}
|
||||
} else {
|
||||
execute = true;
|
||||
}
|
||||
}
|
||||
|
||||
// If Middleware checks have been passed, execute
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||||
if (execute) {
|
||||
if (listener.once) {
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||||
listeners[index] = null;
|
||||
}
|
||||
listener.callback(data);
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||||
}
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||||
});
|
||||
|
||||
// Dirty way of removing used Events
|
||||
while (listeners.indexOf(null) !== -1) {
|
||||
listeners.splice(listeners.indexOf(null), 1);
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||||
}
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||||
}
|
||||
}
|
||||
}]);
|
||||
|
||||
return EventEmitter;
|
||||
}();
|
||||
|
||||
/* harmony default export */ __webpack_exports__["a"] = (EventEmitter);
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||||
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||||
/***/ })
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||||
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||||
});
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Vendored
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Vendored
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/*!
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* Font Awesome Free 5.15.1 by @fontawesome - https://fontawesome.com
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* License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
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*/
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||||
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|
||||
window.HELP_IMPROVE_VIDEOJS = false;
|
||||
window.HELP_IMPROVE_VIDEOJS = false;
|
||||
|
||||
$(document).ready(function() {
|
||||
// Check for click events on the navbar burger icon
|
||||
$(".navbar-burger").click(function() {
|
||||
// Toggle the "is-active" class on both the "navbar-burger" and the "navbar-menu"
|
||||
$(".navbar-burger").toggleClass("is-active");
|
||||
$(".navbar-menu").toggleClass("is-active");
|
||||
|
||||
});
|
||||
|
||||
let options = {
|
||||
slidesToScroll: 1,
|
||||
slidesToShow: 4,
|
||||
loop: false,
|
||||
infinite: false,
|
||||
pagination: false,
|
||||
autoplay: false,
|
||||
autoplaySpeed: 3000,
|
||||
}
|
||||
|
||||
// Initialize all div with carousel class
|
||||
let carousels = bulmaCarousel.attach('.carousel', options);
|
||||
|
||||
// Loop on each carousel initialized
|
||||
for(let i = 0; i < carousels.length; i++) {
|
||||
// Add listener to event
|
||||
carousels[i].on('before:show', state => {
|
||||
console.log(state);
|
||||
});
|
||||
}
|
||||
|
||||
// Access to bulmaCarousel instance of an element
|
||||
let element = document.querySelector('#my-element');
|
||||
if (element && element.bulmaCarousel) {
|
||||
// bulmaCarousel instance is available as element.bulmaCarousel
|
||||
element.bulmaCarousel.on('before-show', function(state) {
|
||||
console.log(state);
|
||||
});
|
||||
}
|
||||
|
||||
/*
|
||||
let player = document.getElementById('interpolation-video');
|
||||
player.addEventListener('loadedmetadata', function() {
|
||||
$('#interpolation-slider').on('input', function(event) {
|
||||
console.log(this.value, player.duration);
|
||||
player.currentTime = player.duration / 100 * this.value;
|
||||
})
|
||||
}, false);
|
||||
*/
|
||||
|
||||
bulmaSlider.attach();
|
||||
})
|
||||
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Reference in new issue
Block a user