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<!DOCTYPE html> |
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<html lang="en"> |
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<head> |
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<meta charset="UTF-8"> |
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<title>Object Detection - Hugging Face Transformers.js</title> |
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<script type="module"> |
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import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.5.4'; |
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window.pipeline = pipeline; |
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</script> |
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<link href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.0/dist/css/bootstrap.min.css" rel="stylesheet"> |
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<link rel="stylesheet" href="css/styles.css"> |
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</head> |
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<body> |
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<div class="container-main"> |
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<div class="header"> |
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<div class="header-logo"> |
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<img src="images/logo.png" alt="logo"> |
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</div> |
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<div class="header-main-text"> |
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<h1>Hugging Face Transformers.js</h1> |
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</div> |
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<div class="header-sub-text"> |
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<h3>Free AI Models for JavaScript Web Development</h3> |
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</div> |
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</div> |
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<hr> |
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<div class="row mt-5"> |
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<div class="col-md-12 text-center"> |
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<a href="index.html" class="btn btn-outline-secondary" |
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style="color: #3c650b; border-color: #3c650b;">Back to Main Page</a> |
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</div> |
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</div> |
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<div class="container mt-5"> |
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<div class="text-center"> |
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<h2>Computer Vision</h2> |
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<h4>Object Detection</h4> |
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</div> |
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<div id="object-detection-container" class="container mt-4"> |
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<h5>Run Object Detection with facebook/detr-resnet-50:</h5> |
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<div class="d-flex align-items-center"> |
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<label for="objectDetectionURLText" class="mb-0 text-nowrap" style="margin-right: 15px;">Enter |
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image URL:</label> |
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<input type="text" class="form-control flex-grow-1" id="objectDetectionURLText" |
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value="https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg" |
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placeholder="Enter image" style="margin-right: 15px; margin-left: 15px;"> |
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<button id="DetectButton" class="btn btn-primary" onclick="detectImage()">Detect</button> |
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</div> |
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<div class="mt-4"> |
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<h4>Output:</h4> |
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<pre id="outputArea"></pre> |
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</div> |
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</div> |
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<hr> |
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<div id="object-detection-local-container" class="container mt-4"> |
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<h5>Detect a Local Image:</h5> |
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<div class="d-flex align-items-center"> |
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<label for="objectDetectionLocalFile" class="mb-0 text-nowrap" |
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style="margin-right: 15px;">Select Local Image:</label> |
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<input type="file" id="objectDetectionLocalFile" accept="image/*" /> |
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<button id="DetectButtonLocal" class="btn btn-primary" |
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onclick="detectImageLocal()">Detect</button> |
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</div> |
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<div class="mt-4"> |
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<h4>Output:</h4> |
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<pre id="outputAreaLocal"></pre> |
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</div> |
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</div> |
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<div class="row mt-5"> |
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<div class="col-md-12 text-center"> |
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<a href="index.html" class="btn btn-outline-secondary" |
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style="color: #3c650b; border-color: #3c650b;">Back to Main Page</a> |
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</div> |
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</div> |
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</div> |
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</div> |
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<script> |
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let detector; |
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async function initializeModel() { |
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detector = await pipeline('object-detection', 'Xenova/detr-resnet-50'); |
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} |
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async function detectImage() { |
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const textFieldValue = document.getElementById("objectDetectionURLText").value.trim(); |
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const result = await detector(textFieldValue, { threshold: 0.9 }); |
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document.getElementById("outputArea").innerText = JSON.stringify(result, null, 2); |
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} |
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async function detectImageLocal() { |
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const fileInput = document.getElementById("objectDetectionLocalFile"); |
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const file = fileInput.files[0]; |
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if (!file) { |
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alert('Please select an image file first.'); |
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return; |
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} |
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const url = URL.createObjectURL(file); |
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const result = await detector(url, { threshold: 0.9 }); |
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document.getElementById("outputAreaLocal").innerText = JSON.stringify(result, null, 2); |
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} |
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window.addEventListener("DOMContentLoaded", initializeModel); |
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</script> |
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</body> |
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</html> |
