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<title>Image Classification - Hugging Face Transformers.js</title>
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import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.4';
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<h1>Hugging Face Transformers.js</h1>
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<div class="header-sub-text">
<h3>Free AI Models for JavaScript Web Development</h3>
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<h2>Computer Vision</h2>
<h4>Image Classification</h4>
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<div id="image-classification-container" class="container mt-4">
<h5>Classify an Image:</h5>
<div class="d-flex align-items-center">
<label for="imageClassificationURLText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter
image URL:</label>
<input type="text" class="form-control flex-grow-1" id="imageClassificationURLText"
value="https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg"
placeholder="Enter image" style="margin-right: 15px; margin-left: 15px;">
<button id="ClassifyButton" class="btn btn-primary" onclick="classifyImage()">Classify</button>
</div>
<div class="mt-4">
<h4>Output:</h4>
<pre id="outputArea"></pre>
</div>
</div>
<hr> <!-- Line Separator -->
<div id="image-classification-local-container" class="container mt-4">
<h5>Classify a Local Image:</h5>
<div class="d-flex align-items-center">
<label for="imageClassificationLocalFile" class="mb-0 text-nowrap"
style="margin-right: 15px;">Select Local Image:</label>
<input type="file" id="imageClassificationLocalFile" accept="image/*" />
<button id="ClassifyButtonLocal" class="btn btn-primary"
onclick="classifyImageLocal()">Classify</button>
</div>
<div class="mt-4">
<h4>Output:</h4>
<pre id="outputAreaLocal"></pre>
</div>
</div>
<hr> <!-- Line Separator -->
<div id="image-classification-top-container" class="container mt-4">
<h5>Classify an Image and Return Top n Classes:</h5>
<div class="d-flex align-items-center">
<label for="imageClassificationTopURLText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter
image URL:</label>
<input type="text" class="form-control flex-grow-1" id="imageClassificationTopURLText"
value="https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg"
placeholder="Enter image" style="margin-right: 15px; margin-left: 15px;">
<button id="ClassifyTopButton" class="btn btn-primary" onclick="classifyTopImage()">Classify</button>
</div>
<div class="mt-4">
<h4>Output:</h4>
<pre id="outputAreaTop"></pre>
</div>
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<script>
let classifier;
// Initialize the sentiment analysis model
async function initializeModel() {
classifier = await pipeline('image-classification', 'Xenova/vit-base-patch16-224');
}
async function classifyImage() {
const textFieldValue = document.getElementById("imageClassificationURLText").value.trim();
const result = await classifier(textFieldValue);
document.getElementById("outputArea").innerText = JSON.stringify(result, null, 2);
}
async function classifyImageLocal() {
const fileInput = document.getElementById("imageClassificationLocalFile");
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 classifier(url);
document.getElementById("outputAreaLocal").innerText = JSON.stringify(result, null, 2);
}
async function classifyTopImage() {
const textFieldValue = document.getElementById("imageClassificationTopURLText").value.trim();
const result = await classifier(textFieldValue, { topk: 3 });
document.getElementById("outputAreaTop").innerText = JSON.stringify(result, null, 2);
}
// Initialize the model after the DOM is completely loaded
window.addEventListener("DOMContentLoaded", initializeModel);
</script>
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