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| <html lang="en"> | |
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| <meta charset="UTF-8"> | |
| <title>Zero Shot Image Classification - 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; | |
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| <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> | |
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| <!-- Content --> | |
| <div class="container mt-5"> | |
| <!-- Centered Titles --> | |
| <div class="text-center"> | |
| <h2>Computer Vision</h2> | |
| <h4>Zero Shot Image Classification</h4> | |
| </div> | |
| <!-- Actual Content of this page --> | |
| <div id="zero-shot-image-classification-container" class="container mt-4"> | |
| <h5>Zero Shot Image Classification w/ Xenova/clip-vit-base-patch32:</h5> | |
| <div class="d-flex align-items-center mb-2"> | |
| <label for="zeroShotImageClassificationURLText" class="mb-0 text-nowrap" | |
| style="margin-right: 15px;">Enter | |
| image URL:</label> | |
| <input type="text" class="form-control flex-grow-1" id="zeroShotImageClassificationURLText" | |
| value="https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg" | |
| placeholder="Enter image" style="margin-right: 15px; margin-left: 15px;"> | |
| </div> | |
| <div class="d-flex align-items-center"> | |
| <label for="labelsText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Labels (comma | |
| separated):</label> | |
| <input type="text" class="form-control flex-grow-1" id="labelsText" value="tiger, horse, dog" | |
| placeholder="Enter labels (comma separated)" style="margin-right: 15px; margin-left: 15px;"> | |
| <button id="classifyButton" class="btn btn-primary ml-2" onclick="classifyImage()">Classify</button> | |
| </div> | |
| <div class="mt-4"> | |
| <h4>Output:</h4> | |
| <pre id="outputArea"></pre> | |
| </div> | |
| </div> | |
| <hr> <!-- Line Separator --> | |
| <div id="zero-shot-image-classification-local-container" class="container mt-4"> | |
| <h5>Zero Shot Image Classification Local File:</h5> | |
| <div class="d-flex align-items-center mb-2"> | |
| <label for="imageClassificationLocalFile" class="mb-0 text-nowrap" | |
| style="margin-right: 15px;">Select Local Image:</label> | |
| <input type="file" id="imageClassificationLocalFile" accept="image/*" /> | |
| </div> | |
| <div class="d-flex align-items-center"> | |
| <label for="labelsLocalText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter Labels (comma | |
| separated):</label> | |
| <input type="text" class="form-control flex-grow-1" id="labelsLocalText" value="tiger, horse, dog" | |
| placeholder="Enter labels (comma separated)" style="margin-right: 15px; margin-left: 15px;"> | |
| <button id="classifyLocalButton" class="btn btn-primary ml-2" onclick="classifyLocalImage()">Classify</button> | |
| </div> | |
| <div class="mt-4"> | |
| <h4>Output:</h4> | |
| <pre id="outputAreaLocal"></pre> | |
| </div> | |
| </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 classifier; | |
| // Initialize the sentiment analysis model | |
| async function initializeModel() { | |
| classifier = await pipeline('zero-shot-image-classification', 'Xenova/clip-vit-base-patch32'); | |
| } | |
| async function classifyImage() { | |
| const textFieldValue = document.getElementById("zeroShotImageClassificationURLText").value.trim(); | |
| const labels = document.getElementById("labelsText").value.trim().split(",").map(item => item.trim()); | |
| const result = await classifier(textFieldValue, labels); | |
| document.getElementById("outputArea").innerText = JSON.stringify(result, null, 2); | |
| } | |
| async function classifyLocalImage() { | |
| 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 labels = document.getElementById("labelsLocalText").value.trim().split(",").map(item => item.trim()); | |
| const result = await classifier(url, labels); | |
| 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> |