Delete assets/detection.js

assets/detection.js

@@ -1,94 +0,0 @@
-const video = document.getElementById("video");
-const canvas = document.getElementById("canvas");
-const ctx = canvas.getContext("2d");
-const startButton = document.getElementById("start");
-
-async function loadModel() {
-  console.log("Loading model...");
-  const model = await tf.loadGraphModel(
-    "https://tfhub.dev/tensorflow/ssd_mobilenet_v2/1/default/1", // Replace with your model URL if required
-    { fromTFHub: true }
-  );
-  console.log("Model loaded successfully.");
-  return model;
-}
-
-function speak(text) {
-  const synth = window.speechSynthesis;
-  const utterance = new SpeechSynthesisUtterance(text);
-  synth.speak(utterance);
-}
-
-async function setupCamera() {
-  const stream = await navigator.mediaDevices.getUserMedia({
-    video: { width: 640, height: 480 },
-  });
-  video.srcObject = stream;
-  return new Promise((resolve) => {
-    video.onloadedmetadata = () => resolve(video);
-  });
-}
-
-async function detectObjects(model) {
-  console.log("Starting detection...");
-
-  video.play();
-  canvas.width = video.videoWidth;
-  canvas.height = video.videoHeight;
-
-  async function processFrame() {
-    ctx.drawImage(video, 0, 0, canvas.width, canvas.height);
-
-    const inputTensor = tf.browser
-      .fromPixels(video)
-      .resizeBilinear([300, 300])
-      .expandDims(0)
-      .div(tf.scalar(255));
-
-    const predictions = await model.executeAsync(inputTensor);
-
-    const [boxes, scores, classes] = predictions;
-
-    ctx.clearRect(0, 0, canvas.width, canvas.height);
-    ctx.drawImage(video, 0, 0, canvas.width, canvas.height);
-
-    const detectionThreshold = 0.5;
-
-    scores.arraySync()[0].forEach((score, index) => {
-      if (score > detectionThreshold) {
-        const bbox = boxes.arraySync()[0][index];
-        const classId = classes.arraySync()[0][index];
-        const label = `Object ${classId}`;
-
-        const x = bbox[1] * canvas.width;
-        const y = bbox[0] * canvas.height;
-        const width = (bbox[3] - bbox[1]) * canvas.width;
-        const height = (bbox[2] - bbox[0]) * canvas.height;
-
-        // Draw bounding box
-        ctx.strokeStyle = "red";
-        ctx.lineWidth = 2;
-        ctx.strokeRect(x, y, width, height);
-
-        // Draw label
-        ctx.fillStyle = "red";
-        ctx.font = "16px Arial";
-        ctx.fillText(label, x, y > 10 ? y - 5 : y + 20);
-
-        // Speak detected object
-        speak(`Detected ${label}`);
-      }
-    });
-
-    requestAnimationFrame(processFrame);
-  }
-
-  processFrame();
-}
-
-startButton.addEventListener("click", async () => {
-  startButton.disabled = true;
-  const model = await loadModel();
-  await setupCamera();
-  detectObjects(model);
-});