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Phishing-Email-Detection-WebGPU
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Update index.html

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  1. index.html +96 -23
index.html CHANGED
@@ -1,29 +1,102 @@
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  <!DOCTYPE html>
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  <html lang="en">
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-
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  <head>
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- <meta charset="UTF-8" />
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- <link rel="stylesheet" href="style.css" />
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-
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- <meta name="viewport" content="width=device-width, initial-scale=1.0" />
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- <title>Transformers.js - Object Detection</title>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  </head>
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-
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  <body>
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- <h1>Object Detection w/ 🤗 Transformers.js</h1>
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- <label id="container" for="upload">
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- <svg width="25" height="25" viewBox="0 0 25 25" fill="none" xmlns="http://www.w3.org/2000/svg">
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- <path fill="#000"
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- d="M3.5 24.3a3 3 0 0 1-1.9-.8c-.5-.5-.8-1.2-.8-1.9V2.9c0-.7.3-1.3.8-1.9.6-.5 1.2-.7 2-.7h18.6c.7 0 1.3.2 1.9.7.5.6.7 1.2.7 2v18.6c0 .7-.2 1.4-.7 1.9a3 3 0 0 1-2 .8H3.6Zm0-2.7h18.7V2.9H3.5v18.7Zm2.7-2.7h13.3c.3 0 .5 0 .6-.3v-.7l-3.7-5a.6.6 0 0 0-.6-.2c-.2 0-.4 0-.5.3l-3.5 4.6-2.4-3.3a.6.6 0 0 0-.6-.3c-.2 0-.4.1-.5.3l-2.7 3.6c-.1.2-.2.4 0 .7.1.2.3.3.6.3Z">
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- </path>
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- </svg>
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- Click to upload image
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- <label id="example">(or try example)</label>
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- </label>
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- <label id="status">Loading model...</label>
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- <input id="upload" type="file" accept="image/*" />
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-
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- <script src="index.js" type="module"></script>
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- </body>
 
 
 
 
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- </html>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
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+ <title>Phishing Email Detection</title>
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+ <style>
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+ body {
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+ font-family: Arial, sans-serif;
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+ padding: 20px;
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+ }
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+ textarea {
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+ width: 100%;
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+ height: 200px;
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+ margin-bottom: 20px;
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+ }
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+ button {
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+ padding: 10px 20px;
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+ background-color: #4CAF50;
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+ color: white;
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+ border: none;
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+ cursor: pointer;
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+ }
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+ #result {
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+ margin-top: 20px;
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+ padding: 10px;
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+ background-color: #f4f4f4;
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+ }
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+ #loading-message {
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+ margin-top: 20px;
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+ color: blue;
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+ }
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+ </style>
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  </head>
 
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  <body>
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+ <h1>Phishing Email Detection</h1>
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+ <p>Would you like to load the phishing detection model?</p>
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+ <button id="load-model-btn">Yes, Load Model</button>
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+ <button id="cancel-load-btn" style="display: none;">Cancel</button>
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+
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+ <div id="loading-message" style="display: none;">Loading model, please wait...</div>
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+
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+ <div id="email-input-section" style="display: none;">
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+ <textarea id="email-input" placeholder="Paste email content here..."></textarea><br>
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+ <button id="detect-btn">Detect Phishing</button>
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+ <div id="result"></div>
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+ </div>
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+
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+ <script type="module">
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+ // Import transformers.js directly from the CDN
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+ import { pipeline } from "https://cdn.jsdelivr.net/npm/@huggingface/transformers@latest/dist/transformers.min.js";
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+
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+ const modelPath = "https://huggingface.co/aaazKI/phishing-email-detection-distilbert_v2.4.1-ONNX/resolve/main/model.onnx";
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+ let model;
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+ const loadModelBtn = document.getElementById("load-model-btn");
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+ const cancelLoadBtn = document.getElementById("cancel-load-btn");
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+ const emailInputSection = document.getElementById("email-input-section");
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+ const loadingMessage = document.getElementById("loading-message");
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+ const resultDiv = document.getElementById("result");
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+ const detectBtn = document.getElementById("detect-btn");
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+
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+ loadModelBtn.addEventListener("click", async () => {
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+ // Hide buttons and show loading message
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+ loadModelBtn.style.display = "none";
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+ cancelLoadBtn.style.display = "inline-block";
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+ loadingMessage.style.display = "block";
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+
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+ // Load the model asynchronously
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+ try {
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+ model = await pipeline("text-classification", modelPath);
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+ loadingMessage.style.display = "none";
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+ emailInputSection.style.display = "block"; // Show input section once model is loaded
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+ } catch (error) {
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+ loadingMessage.innerText = "Error loading the model. Please try again.";
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+ }
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+ });
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+
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+ cancelLoadBtn.addEventListener("click", () => {
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+ // Reset the UI if the user cancels loading
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+ loadModelBtn.style.display = "inline-block";
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+ cancelLoadBtn.style.display = "none";
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+ loadingMessage.style.display = "none";
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+ });
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+
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+ detectBtn.addEventListener("click", async () => {
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+ const emailText = document.getElementById("email-input").value;
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+ if (!emailText.trim()) {
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+ resultDiv.innerText = "Please enter some text to classify.";
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+ return;
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+ }
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+
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+ // Run inference using the model
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+ const result = await model(emailText);
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+
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+ // Display the result
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+ const prediction = result[0].label;
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+ resultDiv.innerText = `Prediction: ${prediction}`;
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+ });
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+ </script>
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+ </body>
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+ </html>