Update assets/detection.js

assets/detection.js

@@ -3,7 +3,6 @@ const canvas = document.getElementById("canvas");
 const ctx = canvas.getContext("2d");
 const button = document.getElementById("start");
 
-// Text-to-Speech for audio feedback
 function speak(text) {
   const synth = window.speechSynthesis;
   const utterance = new SpeechSynthesisUtterance(text);
@@ -21,7 +20,7 @@ async function setupCamera() {
 }
 
 async function detectObjects() {
-  // Load YOLO model using TensorFlow.js or another library
+  console.log("Loading model...");
   const model = await tf.loadGraphModel("https://path-to-your-yolo-model/model.json");
 
   canvas.width = video.videoWidth;
@@ -30,27 +29,24 @@ async function detectObjects() {
   async function processFrame() {
     ctx.drawImage(video, 0, 0, canvas.width, canvas.height);
 
-    // Preprocess the video frame for YOLO model
     const inputTensor = tf.browser.fromPixels(video).resizeBilinear([640, 480]).expandDims(0);
     const predictions = await model.executeAsync(inputTensor);
 
-    // Parse predictions and draw bounding boxes
+    console.log("Predictions:", predictions);
+
     predictions.forEach((prediction) => {
       const [x, y, width, height] = prediction.bbox;
       const label = prediction.class;
       const confidence = prediction.score;
 
-      // Draw the bounding box
       ctx.strokeStyle = "red";
       ctx.lineWidth = 2;
       ctx.strokeRect(x, y, width, height);
 
-      // Draw the label
       ctx.fillStyle = "red";
       ctx.font = "18px Arial";
       ctx.fillText(`${label} (${(confidence * 100).toFixed(2)}%)`, x, y - 10);
 
-      // Provide audio feedback
       speak(`${label} detected with ${(confidence * 100).toFixed(2)}% confidence.`);
     });
 
@@ -61,7 +57,7 @@ async function detectObjects() {
 }
 
 button.addEventListener("click", async () => {
-  button.disabled = true; // Disable the button after starting
+  button.disabled = true;
   await setupCamera();
   video.play();
   detectObjects();