AilexGPT commited on
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5e954ec
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Update index.js

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  1. index.js +31 -69
index.js CHANGED
@@ -1,79 +1,41 @@
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- import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/[email protected]';
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- // Since we will download the model from the Hugging Face Hub, we can skip the local model check
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- env.allowLocalModels = false;
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-
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- // Reference the elements that we will need
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  const status = document.getElementById('status');
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- const fileUpload = document.getElementById('upload');
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- const imageContainer = document.getElementById('container');
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- const example = document.getElementById('example');
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-
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- const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/city-streets.jpg';
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-
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- // Create a new object detection pipeline
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- status.textContent = 'Loading model...';
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- const detector = await pipeline('object-detection', 'Xenova/detr-resnet-50');
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- status.textContent = 'Ready';
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-
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- example.addEventListener('click', (e) => {
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- e.preventDefault();
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- detect(EXAMPLE_URL);
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- });
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-
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- fileUpload.addEventListener('change', function (e) {
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- const file = e.target.files[0];
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- if (!file) {
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- return;
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- }
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-
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- const reader = new FileReader();
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- // Set up a callback when the file is loaded
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- reader.onload = e2 => detect(e2.target.result);
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-
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- reader.readAsDataURL(file);
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- });
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- // Detect objects in the image
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- async function detect(img) {
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- imageContainer.innerHTML = '';
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- imageContainer.style.backgroundImage = `url(${img})`;
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- status.textContent = 'Analysing...';
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- const output = await detector(img, {
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- threshold: 0.5,
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- percentage: true,
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- });
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- status.textContent = '';
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- output.forEach(renderBox);
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  }
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- // Render a bounding box and label on the image
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- function renderBox({ box, label }) {
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- const { xmax, xmin, ymax, ymin } = box;
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-
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- // Generate a random color for the box
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- const color = '#' + Math.floor(Math.random() * 0xFFFFFF).toString(16).padStart(6, 0);
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-
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- // Draw the box
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- const boxElement = document.createElement('div');
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- boxElement.className = 'bounding-box';
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- Object.assign(boxElement.style, {
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- borderColor: color,
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- left: 100 * xmin + '%',
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- top: 100 * ymin + '%',
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- width: 100 * (xmax - xmin) + '%',
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- height: 100 * (ymax - ymin) + '%',
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- })
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- // Draw label
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- const labelElement = document.createElement('span');
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- labelElement.textContent = label;
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- labelElement.className = 'bounding-box-label';
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- labelElement.style.backgroundColor = color;
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- boxElement.appendChild(labelElement);
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- imageContainer.appendChild(boxElement);
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- }
 
 
 
 
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+ import { pipeline } from 'https://cdn.jsdelivr.net/npm/@xenova/[email protected]';
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+ // Status- und Input-Elemente
 
 
 
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  const status = document.getElementById('status');
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+ const userInput = document.getElementById('user-input');
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+ const sendButton = document.getElementById('send-button');
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+ const chatBox = document.getElementById('chat-box');
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ // Chatbot-Pipeline initialisieren
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+ status.textContent = 'Lade Modell...';
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+ const chatbot = await pipeline('text-generation', 'IhrModellName'); // Ersetzen Sie 'IhrModellName' mit dem Namen des Hugging Face Modells
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+ status.textContent = 'Bereit';
 
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+ // Nachrichtensendefunktion
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+ async function sendMessage() {
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+ const message = userInput.value;
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+ if (!message) return;
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+ displayMessage('Du: ' + message);
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+ userInput.value = '';
 
 
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+ const response = await chatbot(message);
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+ displayMessage('Bot: ' + response[0].generated_text);
 
 
 
 
 
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  }
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+ // Nachricht im Chat anzeigen
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+ function displayMessage(message) {
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+ const messageElement = document.createElement('div');
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+ messageElement.textContent = message;
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+ chatBox.appendChild(messageElement);
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+ }
 
 
 
 
 
 
 
 
 
 
 
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+ // Event-Listener für den Senden-Button
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+ sendButton.addEventListener('click', sendMessage);
 
 
 
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+ // Enter-Taste als Alternative zum Senden
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+ userInput.addEventListener('keypress', function(e) {
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+ if (e.key === 'Enter') {
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+ sendMessage();
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+ }
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+ });