File size: 5,081 Bytes
d8d37b0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Image to Text - Hugging Face Transformers.js</title>
<script type="module">
// Import the library
import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.4';
// Make it available globally
window.pipeline = pipeline;
</script>
<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.0/dist/css/bootstrap.min.css" rel="stylesheet">
<link rel="stylesheet" href="css/styles.css"></head>
<body>
<div class="container-main">
<!-- Page Header -->
<div class="header">
<div class="header-logo">
<img src="images/logo.png" alt="logo">
</div>
<div class="header-main-text">
<h1>Hugging Face Transformers.js</h1>
</div>
<div class="header-sub-text">
<h3>Free AI Models for JavaScript Web Development</h3>
</div>
</div>
<hr> <!-- Separator -->
<!-- Back to Home button -->
<div class="row mt-5">
<div class="col-md-12 text-center">
<a href="index.html" class="btn btn-outline-secondary"
style="color: #3c650b; border-color: #3c650b;">Back to Main Page</a>
</div>
</div>
<!-- Content -->
<div class="container mt-5">
<!-- Centered Titles -->
<div class="text-center">
<h2>Computer Vision</h2>
<h4>Image to Text</h4>
</div>
<!-- Actual Content of this page -->
<div id="image-to-text-container" class="container mt-4">
<h5>Generate a Caption for an Image w/ Xenova/vit-gpt2-image-captionin:</h5>
<div class="d-flex align-items-center">
<label for="imageToTextURLText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter
image to Caption URL:</label>
<input type="text" class="form-control flex-grow-1" id="imageToTextURLText"
value="https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg"
placeholder="Enter image" style="margin-right: 15px; margin-left: 15px;">
<button id="ImagetoTextButton" class="btn btn-primary" onclick="captionImage()">Caption</button>
</div>
<div class="mt-4">
<h4>Output:</h4>
<pre id="outputArea"></pre>
</div>
</div>
<hr> <!-- Line Separator -->
<div id="image-to-text-local-container" class="container mt-4">
<h5>Generate a Caption for a Local Image:</h5>
<div class="d-flex align-items-center">
<label for="imagetoTextLocalFile" class="mb-0 text-nowrap"
style="margin-right: 15px;">Select Local Image:</label>
<input type="file" id="imagetoTextLocalFile" accept="image/*" />
<button id="CaptionButtonLocal" class="btn btn-primary"
onclick="captionImageLocal()">Caption</button>
</div>
<div class="mt-4">
<h4>Output:</h4>
<pre id="outputAreaLocal"></pre>
</div>
</div>
<!-- Back to Home button -->
<div class="row mt-5">
<div class="col-md-12 text-center">
<a href="index.html" class="btn btn-outline-secondary"
style="color: #3c650b; border-color: #3c650b;">Back to Main Page</a>
</div>
</div>
</div>
</div>
<script>
let captioner;
// Initialize the sentiment analysis model
async function initializeModel() {
captioner = await pipeline('image-to-text', 'Xenova/vit-gpt2-image-captioning');
}
async function captionImage() {
const textFieldValue = document.getElementById("imageToTextURLText").value.trim();
const result = await captioner(textFieldValue);
document.getElementById("outputArea").innerText = JSON.stringify(result, null, 2);
}
async function captionImageLocal() {
const fileInput = document.getElementById("imagetoTextLocalFile");
const file = fileInput.files[0];
if (!file) {
alert('Please select an image file first.');
return;
}
// Create a Blob URL from the file
const url = URL.createObjectURL(file);
const result = await captioner(url);
document.getElementById("outputAreaLocal").innerText = JSON.stringify(result, null, 2);
}
// Initialize the model after the DOM is completely loaded
window.addEventListener("DOMContentLoaded", initializeModel);
</script>
</body>
</html> |