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Update camera.html
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‎ng_sandbox/camera.html‎

Lines changed: 135 additions & 108 deletions
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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>Camera + Visual Search</title>
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<title>Camera Visual Search (Cached Embeddings)</title>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@4.11.0/dist/tf.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/mobilenet@3.1.0/dist/mobilenet.min.js"></script>
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<style>
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body { font-family: Arial, sans-serif; text-align: center; padding: 1em; }
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video, canvas { width: 100%; max-width: 400px; }
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#result-img { margin-top: 1em; max-width: 400px; }
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video, canvas, img { width: 100%; max-width: 400px; }
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#status { margin: 1em 0; font-weight: bold; }
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</style>
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</head>
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<body>
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<h1>Visual Search from Camera</h1>
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<h1>Visual Search</h1>
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<p id="status">Loading model…</p>
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<video id="video" autoplay playsinline></video>
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<br />
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<button id="capture-btn">Take Photo</button>
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<canvas id="capture-canvas" style="display:none;"></canvas>
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<h2>Most Similar Match:</h2>
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<img id="result-img" alt="Matching image will appear here">
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<script>
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let model;
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const video = document.getElementById("video");
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const canvas = document.getElementById("capture-canvas");
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const ctx = canvas.getContext("2d");
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const resultImg = document.getElementById("result-img");
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// 1️⃣ Start camera
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async function startCamera() {
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const stream = await navigator.mediaDevices.getUserMedia({ video: true });
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video.srcObject = stream;
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}
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<button id="capture-btn" disabled>Take Photo</button>
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<canvas id="canvas" style="display:none;"></canvas>
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<h2>Best Match</h2>
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<img id="result-img" />
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<script>
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let model;
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let collectionEmbeddings = []; // { url, embedding }
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const video = document.getElementById("video");
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const canvas = document.getElementById("canvas");
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const ctx = canvas.getContext("2d");
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const statusEl = document.getElementById("status");
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const resultImg = document.getElementById("result-img");
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const captureBtn = document.getElementById("capture-btn");
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/* ------------------ Camera ------------------ */
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async function startCamera() {
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const stream = await navigator.mediaDevices.getUserMedia({ video: true });
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video.srcObject = stream;
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}
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/* ------------------ Model ------------------ */
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async function loadModel() {
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model = await mobilenet.load({ version: 2, alpha: 1.0 });
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console.log("MobileNet loaded");
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}
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/* ------------------ JSON ------------------ */
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async function loadCollection() {
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const res = await fetch(
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"https://johnstack.github.io/JavaScript-Sandpit/ng_sandbox/collection.sample.json"
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);
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const json = await res.json();
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return json.items; // adjust if structure differs
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}
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/* ------------------ Embeddings ------------------ */
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async function getEmbedding(img) {
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const tensor = tf.browser.fromPixels(img)
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.resizeNearestNeighbor([224, 224])
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.toFloat()
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.expandDims();
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const embedding = model.infer(tensor, "conv_preds");
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const data = embedding.dataSync();
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tensor.dispose();
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embedding.dispose();
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return data;
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}
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/* ------------------ Similarity ------------------ */
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function cosineSimilarity(a, b) {
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let dot = 0, magA = 0, magB = 0;
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for (let i = 0; i < a.length; i++) {
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dot += a[i] * b[i];
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magA += a[i] * a[i];
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magB += b[i] * b[i];
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}
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return dot / (Math.sqrt(magA) * Math.sqrt(magB));
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}
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/* ------------------ Preload Embeddings ------------------ */
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async function preloadEmbeddings() {
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statusEl.textContent = "Loading image collection…";
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const items = await loadCollection();
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for (let item of items) {
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const img = new Image();
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img.crossOrigin = "anonymous";
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img.src = item.url; // adjust key if needed
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await new Promise(resolve => img.onload = resolve);
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const embedding = await getEmbedding(img);
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collectionEmbeddings.push({
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url: item.url,
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embedding
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});
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// 2️⃣ Load MobileNet
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async function loadModel() {
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model = await mobilenet.load();
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console.log("MobileNet loaded");
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}
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statusEl.textContent = `Indexed ${collectionEmbeddings.length}/${items.length}`;
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}
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// 3️⃣ Fetch JSON collection
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async function loadCollection() {
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const res = await fetch(
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"https://johnstack.github.io/JavaScript-Sandpit/ng_sandbox/collection.sample.json"
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);
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const json = await res.json();
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return json.items; // adjust based on JSON structure
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}
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statusEl.textContent = "Ready! Take a photo.";
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captureBtn.disabled = false;
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}
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// 4️⃣ Compute embedding
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async function getEmbedding(imgElement) {
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const logits = model.infer(imgElement, "conv_preds");
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return logits.dataSync(); // embedding vector
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}
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/* ------------------ Search ------------------ */
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async function findBestMatch(capturedImg) {
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const captureEmbedding = await getEmbedding(capturedImg);
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// 5️⃣ Compute cosine similarity
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function cosineSim(a, b) {
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let dot = 0, magA = 0, magB = 0;
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for (let i = 0; i < a.length; i++) {
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dot += a[i] * b[i];
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magA += a[i] * a[i];
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magB += b[i] * b[i];
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}
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return dot / (Math.sqrt(magA) * Math.sqrt(magB));
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}
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let bestScore = -1;
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let bestMatch = null;
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// 6️⃣ Find nearest
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async function findNearest(captureImg, collection) {
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const captureEmbedding = await getEmbedding(captureImg);
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let bestSim = -1;
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let bestImg = null;
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for (let item of collection) {
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// load collection image
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const tempImg = new Image();
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tempImg.crossOrigin = "anonymous";
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tempImg.src = item.url; // adjust if JSON key differs
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await new Promise((resolve) => {
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tempImg.onload = resolve;
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tempImg.onerror = resolve; // skip broken links
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});
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const emb = await getEmbedding(tempImg);
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const sim = cosineSim(captureEmbedding, emb);
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if (sim > bestSim) {
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bestSim = sim;
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bestImg = item.url;
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}
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}
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return bestImg;
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for (let item of collectionEmbeddings) {
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const score = cosineSimilarity(captureEmbedding, item.embedding);
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if (score > bestScore) {
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bestScore = score;
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bestMatch = item.url;
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}
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// 🔘 Capture button logic
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document.getElementById("capture-btn").addEventListener("click", async () => {
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canvas.width = video.videoWidth;
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canvas.height = video.videoHeight;
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ctx.drawImage(video, 0, 0);
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const dataUrl = canvas.toDataURL("image/jpeg");
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const captureImg = new Image();
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captureImg.src = dataUrl;
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captureImg.onload = async () => {
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resultImg.src = "Searching...";
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const collection = await loadCollection();
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const nearestUrl = await findNearest(captureImg, collection);
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if (nearestUrl) {
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resultImg.src = nearestUrl;
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} else {
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resultImg.alt = "No similar image found";
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}
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};
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});
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// Initialize
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startCamera();
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loadModel();
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</script>
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}
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return bestMatch;
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}
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/* ------------------ Capture ------------------ */
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captureBtn.addEventListener("click", async () => {
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canvas.width = video.videoWidth;
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canvas.height = video.videoHeight;
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ctx.drawImage(video, 0, 0);
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const img = new Image();
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img.src = canvas.toDataURL("image/jpeg");
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img.onload = async () => {
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statusEl.textContent = "Searching…";
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const match = await findBestMatch(img);
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resultImg.src = match;
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statusEl.textContent = "Match found!";
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};
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});
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/* ------------------ Init ------------------ */
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(async function init() {
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await startCamera();
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await loadModel();
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await preloadEmbeddings();
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})();
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</script>
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</body>
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</html>

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