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index.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<link rel="canonical" href="https://datadaygrind3.github.io/currenSEE/" />
<link rel="manifest" href="/currenSEE/manifest.webmanifest" />
<link rel="icon" href="./images/icon.jpg" />
<link rel="stylesheet" href="index.css" />
<title>currenSEE</title>
</head>
<body>
<audio
src="sounds/welcome.mp3"
id="welcome"
preload="auto"
></audio>
<div
id="camera-container"
style="
position: absolute;
/* left: 45%; */
top: 0%;
height: 100%;
width: 100%;
"
>
<div id="webcam-container"></div>
<div id="label-container"></div>
</div>
<div id="window" onclick="welcome()"></div>
<button
type="button"
onclick="init()"
style="
left: 0%;
top: 0%;
position: absolute;
background-color: rgba(78, 186, 212, 0.5);
font-size: 10vw;
height: 100%;
width: 50%;
"
>
START
</button>
<button
type="button"
class="btn btn-primary"
onclick="help()"
style="
left: 50%;
top: 0%;
position: absolute;
background-color: rgba(218, 153, 78, 0.5);
font-size: 10vw;
height: 100%;
width: 50%;
"
>
HELP
</button>
<script>
if (navigator.serviceWorker) {
navigator.serviceWorker.register("/currenSEE/sw.js", {
scope: "/currenSEE/",
});
}
</script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]/dist/tf.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/@teachablemachine/[email protected]/dist/teachablemachine-image.min.js"></script>
<script type="text/javascript">
// More API functions here:
// https://github.com/googlecreativelab/teachablemachine-community/tree/master/libraries/image
// the link to your model provided by Teachable Machine export panel
const URL = "./my_model/";
var isInitCalled = false;
let model, webcam, labelContainer, maxPredictions, note;
let prediction = [];
let probabilities = [];
let interval = 0;
let currentLabel = "";
function readStart() {
let speech = new SpeechSynthesisUtterance();
speech.lang = "en-US";
speech.text = "Starting current see";
speech.volume = 1;
speech.rate = 1;
speech.pitch = 1;
window.speechSynthesis.speak(speech);
}
// Load the image model and setup the webcam
async function init() {
if (isInitCalled) {
return;
}
readStart();
const modelURL = URL + "model.json";
const metadataURL = URL + "metadata.json";
// load the model and metadata
// Refer to tmImage.loadFromFiles() in the API to support files from a file picker
// or files from your local hard drive
// Note: the pose library adds "tmImage" object to your window (window.tmImage)
model = await tmImage.load(modelURL, metadataURL);
maxPredictions = model.getTotalClasses();
// Convenience function to setup a webcam
const flip = true; // whether to flip the webcam
webcam = new tmImage.Webcam(200, 200, flip); // width, height, flip
await webcam.setup(); // request access to the webcam
await webcam.play();
window.requestAnimationFrame(loop);
// append elements to the DOM
document.getElementById("webcam-container").appendChild(webcam.canvas);
labelContainer = document.getElementById("label-container");
for (let i = 0; i < maxPredictions; i++) {
// and class labels
labelContainer.appendChild(document.createElement("div"));
}
window.speechSynthesis.cancel();
isInitCalled = true;
}
async function loop() {
webcam.update(); // update the webcam frame
await predict();
window.requestAnimationFrame(loop);
}
// run the webcam image through the image model
async function predict() {
// console.log("predict");
// clear the queue and play the new one
probabilities = [];
// predict can take in an image, video or canvas html element
prediction = await model.predict(webcam.canvas);
for (let i = 0; i < maxPredictions; i++) {
const classPrediction =
prediction[i].className +
": " +
prediction[i].probability.toFixed(2);
labelContainer.childNodes[i].innerHTML = classPrediction;
}
if (interval == 0) interval = setInterval(textToAudio, 5000);
}
function textToAudio() {
probabilities = prediction.map((pred) => pred.probability);
let maxProb = Math.max(...probabilities);
let noteIndex = probabilities.indexOf(maxProb);
switch (noteIndex) {
case 0:
note = "2";
break;
case 1:
note = "5";
break;
case 2:
note = "10";
break;
case 3:
note = "50";
break;
case 4:
note = "100";
break;
default:
break;
}
currentLabel = note;
let msg = `That is a ${note} dollar note`;
let speech = new SpeechSynthesisUtterance();
speech.lang = "en-US";
speech.text = msg;
speech.volume = 1;
speech.rate = 1;
speech.pitch = 1;
window.speechSynthesis.speak(speech);
}
</script>
<script src="index.js"></script>
</body>
</html>