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<!DOCTYPE html>
<html lang="en">
<head></head>
<meta charset="UTF-8">
<title>Sign Language Interpreter</title>
<script>
window.console = window.console || function (t) { };
</script>
<!-- For Android
<link rel="stylesheet" type="text/css" href="http://127.0.0.1:8125/assets/static/browser_detect.css" />
-->
<!-- For Web -->
<link rel="stylesheet" type="text/css" href="static/browser_detect.css" />
</head>
<body translate="no">
<!-- For Android
<script src="../assets/ipc/androidjs.js"></script>
<script src="http://127.0.0.1:8125/assets/static/drawing_utils.js" crossorigin="anonymous"></script>
<script src="http://127.0.0.1:8125/assets/static/hands.js" crossorigin="anonymous"></script>
<script src="http://127.0.0.1:8125/assets/static/tfjs-core"></script>
<script src="http://127.0.0.1:8125/assets/static/tfjs-backend-cpu"></script>
<script src="http://127.0.0.1:8125/assets/static/tf-tflite.min.js"></script>
<script src="http://127.0.0.1:8125/assets/static/vision_wasm_internal.js" crossorigin="anonymous"></script>
-->
<!-- For Web -->
<script src="https://cdn.jsdelivr.net/npm/@mediapipe/drawing_utils/drawing_utils.js"
crossorigin="anonymous"></script>
<script src="https://cdn.jsdelivr.net/npm/@mediapipe/hands/hands.js" crossorigin="anonymous"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-core"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-cpu"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-tflite/dist/tf-tflite.min.js"></script>
<div class="container">
<video id="webcam" style="display:none" autoplay="" playsinline=""></video>
<div class="canvas_wrapper" id="canvas_wrapper">
<button id="switch-camera" style="display:none; position: absolute; top:10px; left:10px; padding:5px; height:40px; width:40px; text-align: center; border-radius: 12.25px; font-size: 20px; font-weight: 900; border:none; background-color: #f2f2f2; color:black;
box-shadow: 0px 4px 20px 4px rgba(0, 0, 0, 0.38); z-index:100">
<span>⟳</span>
</button>
<canvas class="output_canvas" id="output_canvas" width="100%" height="300%"></canvas>
<center>
<button id="webcamButton" style="font-weight: 600; color:black;">
<span>Enable Webcam</span>
</button>
</center>
</div>
</div>
<center>
<img id="output_image" style="display:none"></img>
<div class="wrapper_result">
<div id="predicted_result">></div>
</div>
<div class="wrapper_text">
<textarea id="text" onkeyup="set_output_array(this.value)"></textarea>
<button id="text-to-speech" onclick="speak(document.getElementById('text').value)">
<span>Listen 🔊</span>
</button>
</div>
<center>
<script>
const originalFetch = window.fetch;
// Override the fetch function
window.fetch = async function (input, init) {
// Convert input to URL if it's a Request object
const url = typeof input === 'string' ? input : input.url;
var newUrl = url
if (url == 'https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.0/wasm/vision_wasm_internal.wasm') {
// newUrl = 'http://127.0.0.1:8125/assets/static/vision_wasm_internal.wasm' //For Android
newUrl = 'https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.0/wasm/vision_wasm_internal.wasm' // For Web
}
console.log("This was FETCHED: ", newUrl)
// Call the original fetch function with the new URL
return originalFetch(newUrl, init);
};
var synthesis = window.speechSynthesis;
if ('speechSynthesis' in window) {
var synthesis = window.speechSynthesis;
// Get the first `en` language voice in the list
var voice = synthesis.getVoices().filter(function (voice) {
return voice.lang === 'en';
})[0];
// Create an utterance object
} else {
speechSupported = false;
console.log('Text-to-speech not supported.');
}
function speak(text) {
if (!speechSupported) {
const audioPlayer = document.getElementById('audioPlayer');
if (prevSpeech != text) {
prevSpeech = text
audioPlayer.src = 'http://127.0.0.1:8125/speech?t=' + text; // Set the audio source
console.log("Set src: ", audioPlayer.src)
}
audioPlayer.play() // Play the audio
.then(() => {
console.log('Audio is playing');
})
.catch(error => {
console.error('Error playing audio:', error);
prevSpeech = ''
});
} else if ('speechSynthesis' in window) {
var utterance = new SpeechSynthesisUtterance(text);
utterance.voice = voice;
utterance.pitch = 0.6;
utterance.rate = 0.8;
utterance.volume = 0.8;
synthesis.speak(utterance);
} else {
console.log("Text to speech is now not supported")
}
}
var word_list = []
function set_output_array(text) {
console.log(text)
word_list = text.split("");
console.log(word_list)
}
</script>
<script type="module">
//import { HandLandmarker, FilesetResolver } from "http://127.0.0.1:8125/assets/static/tasks-vision@0.10.0" // For Android
import { HandLandmarker, FilesetResolver } from "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.0"; // For Web
let handLandmarker = undefined;
let runningMode = "IMAGE";
let enableWebcamButton;
let webcamRunning = false;
var time_since_letter = 0
var last_letter_time = 0
var is_first_run = 1
// Before we can use HandLandmarker class we must wait for it to finish
// loading. Machine Learning models can be large and take a moment to
// get everything needed to run.
const createHandLandmarker = async () => {
const vision = await FilesetResolver.forVisionTasks("https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.0/wasm");
handLandmarker = await HandLandmarker.createFromOptions(vision, {
baseOptions: {
modelAssetPath: `https://storage.googleapis.com/mediapipe-models/hand_landmarker/hand_landmarker/float16/1/hand_landmarker.task`,
delegate: "GPU"
},
runningMode: runningMode,
numHands: 1
});
};
createHandLandmarker();
const MODEL_PATH = "/exported"
var objectDetector = tflite.loadTFLiteModel(MODEL_PATH);
/********************************************************************
// Continuously grab images
********************************************************************/
var global_res = 0;
const video = document.getElementById("webcam");
const canvasElement = document.getElementById("output_canvas");
const canvasCtx = canvasElement.getContext("2d");
var x_array = []
var y_array = []
var video_facing_mode = "user"
// Check if webcam access is supported.
const hasGetUserMedia = () => { var _a; return !!((_a = navigator.mediaDevices) === null || _a === void 0 ? void 0 : _a.getUserMedia); };
// If webcam supported, add event listener to button for when user
// wants to activate it.
if (hasGetUserMedia()) {
enableWebcamButton = document.getElementById("webcamButton");
enableWebcamButton.addEventListener("click", enableCam);
document.getElementById("switch-camera").addEventListener("click", switch_camera);
}
else {
console.warn("getUserMedia() is not supported by your browser");
}
async function switch_camera() {
if (video_facing_mode == 'user') {
webcamRunning = false
video_facing_mode = 'environment'
await load_camera()
webcamRunning = true
}
else {
webcamRunning = false
video_facing_mode = 'user'
await load_camera()
webcamRunning = true
}
}
// Enable the live webcam view and start detection.
function enableCam(event) {
if (!handLandmarker) {
console.log("Wait! objectDetector not loaded yet.");
return;
}
if (webcamRunning === true) {
webcamRunning = false;
enableWebcamButton.innerText = "ENABLE PREDICTIONS";
}
else {
webcamRunning = true;
enableWebcamButton.style = "display:none"
document.getElementById("switch-camera").style.display = "block"
}
// getUsermedia parameters.
load_camera()
}
function load_camera() {
const constraints = {
video: {
facingMode: video_facing_mode
}
};
// Activate the webcam stream.
navigator.mediaDevices.getUserMedia(constraints).then((stream) => {
video.srcObject = stream;
video.addEventListener("loadeddata", predictWebcam);
});
}
let lastVideoTime = -1;
let results = undefined;
console.log(video);
async function predictWebcam() {
if (video.videoHeight == 0) {
return
}
canvasElement.width = window.innerWidth;
// Start detecting the stream.
if (runningMode === "IMAGE") {
runningMode = "VIDEO";
await handLandmarker.setOptions({ runningMode: "VIDEO" });
}
let startTimeMs = performance.now();
if (lastVideoTime !== video.currentTime) {
lastVideoTime = video.currentTime;
results = handLandmarker.detectForVideo(video, startTimeMs);
}
canvasCtx.save();
canvasCtx.clearRect(0, 0, canvasElement.width, canvasElement.height);
canvasCtx.drawImage(video, 0, 0, canvasElement.width, (video.videoHeight / video.videoWidth) * canvasElement.width)
if (is_first_run == 1) {
var elem_rect = document.getElementById("output_canvas").getBoundingClientRect()
console.log(elem_rect.height | 0);
document.getElementById("canvas_wrapper").style.height = (elem_rect.height | 0).toString() + "px"
is_first_run = 0
}
if (results.landmarks && results.handednesses[0]) {
var current_time = Math.round(Date.now())
document.getElementById("predicted_result").style.width = String((current_time - last_letter_time) / 10) + "%"
if (results.handednesses[0][0].categoryName == "Left") {
annotateImage()
console.log("LEFT")
//detectSign()
} else {
console.log("RIGHT")
var current_result = "_"
var previous_result = document.getElementById("predicted_result").innerText
document.getElementById("predicted_result").innerText = current_result
if (previous_result == current_result) {
if (current_time - last_letter_time > 1000) {
last_letter_time = current_time
word_list.push(" ")
console.log(word_list)
document.getElementById("text").value = word_list.join('')
}
}
else {
last_letter_time = current_time
}
}
}
else {
if (30 > calculateCanvasBrightness(canvasElement)) {
var current_result = "<"
var previous_result = document.getElementById("predicted_result").innerText
document.getElementById("predicted_result").innerText = current_result
var current_time = Math.round(Date.now())
console.log(current_time - last_letter_time)
if (previous_result == current_result) {
if (current_time - last_letter_time > 400) {
last_letter_time = current_time
word_list.pop()
console.log(word_list)
document.getElementById("text").value = word_list.join('')
}
}
else {
last_letter_time = current_time
}
} else {
last_letter_time = Math.round(Date.now())
document.getElementById("predicted_result").style.width = String(0) + "%"
}
}
canvasCtx.restore();
// Kepp predicting
if (webcamRunning === true) {
window.requestAnimationFrame(predictWebcam);
}
}
function annotateImage() {
//console.log(results.landmarks)
if (results.landmarks[0]) {
x_array = []
y_array = []
results.landmarks[0].forEach(iterate)
//console.log(x_array)
var image_height = (video.videoHeight / video.videoWidth) * canvasElement.width
var image_width = canvasElement.width
var min_x = Math.min(...x_array) * image_width
var min_y = Math.min(...y_array) * image_height
var max_x = Math.max(...x_array) * image_width
var max_y = Math.max(...y_array) * image_height
var sect_height = max_y - (min_y)
var sect_width = max_x - (min_x)
var center_x = (min_x + max_x) / 2
var center_y = (min_y + max_y) / 2
var sect_diameter = 50
if (sect_height > sect_width) {
sect_diameter = sect_height
//console.log("sect_height", sect_diameter)
}
if (sect_height < sect_width) {
sect_diameter = sect_width
// console.log("sect_width", sect_diameter)
}
sect_diameter = sect_diameter + 50
var sect_radius = sect_diameter / 2
var crop_top = center_y - sect_radius
var crop_bottom = center_y + sect_radius
var crop_left = center_x - sect_radius
var crop_right = center_x + sect_radius
if (crop_top < 0) {
crop_top = 0
}
if (crop_left < 0) {
crop_left = 0
}
if (crop_right > image_width) {
crop_right = image_width
}
if (crop_bottom > image_height) {
crop_bottom = image_height
}
canvasCtx.beginPath();
canvasCtx.rect(crop_left, crop_top, crop_right - crop_left, crop_bottom - crop_top);
canvasCtx.stroke();
}
/* for (const landmarks of results.multiHandLandmarks) {
drawConnectors(canvasCtx, landmarks, HAND_CONNECTIONS, {
color: "#00FF00",
lineWidth: 5
});
drawLandmarks(canvasCtx, landmarks, { color: "#FF0000", lineWidth: 2 });
}*/
// console.log(results)
const landmarks = results.landmarks;
if (landmarks[0]) {
var hand = landmarks[0]
// Thumb connections
drawConnection(hand[4], hand[3], '#ffe5b4', 5); // 4-3
drawConnection(hand[3], hand[2], '#ffe5b4', 5); // 3-2
drawConnection(hand[2], hand[1], '#ffe5b4', 5); // 2-1
// Index connections
drawConnection(hand[8], hand[7], '#804080', 5); // 8-7
drawConnection(hand[7], hand[6], '#804080', 5); // 7-6
drawConnection(hand[6], hand[5], '#804080', 5); // 6-5
// Middle connections
drawConnection(hand[12], hand[11], '#ffcc00', 5); // 12-11
drawConnection(hand[11], hand[10], '#ffcc00', 5); // 11-10
drawConnection(hand[10], hand[9], '#ffcc00', 5); // 10-9
// Ring connections
drawConnection(hand[16], hand[15], '#30ff30', 5); // 16-15
drawConnection(hand[15], hand[14], '#30ff30', 5); // 15-14
drawConnection(hand[14], hand[13], '#30ff30', 5); // 14-13
// Pinky connections
drawConnection(hand[20], hand[19], '#1565c0', 5); // 20-19
drawConnection(hand[19], hand[18], '#1565c0', 5); // 19-18
drawConnection(hand[18], hand[17], '#1565c0', 5); // 18-17
drawConnection(hand[0], hand[1], '#808080', 5); // 0-1
drawConnection(hand[0], hand[5], '#808080', 5); // 0-5
drawConnection(hand[0], hand[17], '#808080', 5); // 0-17
drawConnection(hand[5], hand[9], '#808080', 5); // 5-9
drawConnection(hand[9], hand[13], '#808080', 5); // 9-13
drawConnection(hand[13], hand[17], '#808080', 5); // 13-17
// Thumb
drawLandmarks(canvasCtx, hand[2], '#ffe5b4'); // Thumb tip (2)
drawLandmarks(canvasCtx, hand[3], '#ffe5b4'); // Thumb base (3)
drawLandmarks(canvasCtx, hand[4], '#ffe5b4'); // Thumb base (4)
// Index
drawLandmarks(canvasCtx, hand[6], '#804080'); // Index tip (6)
drawLandmarks(canvasCtx, hand[7], '#804080'); // Index base (7)
drawLandmarks(canvasCtx, hand[8], '#804080'); // Index base (8)
// Middle
drawLandmarks(canvasCtx, hand[10], '#ffcc00'); // Middle tip (10)
drawLandmarks(canvasCtx, hand[11], '#ffcc00'); // Middle base (11)
drawLandmarks(canvasCtx, hand[12], '#ffcc00'); // Middle base (12)
// Ring
drawLandmarks(canvasCtx, hand[14], '#30ff30'); // Ring tip (14)
drawLandmarks(canvasCtx, hand[15], '#30ff30'); // Ring base (15)
drawLandmarks(canvasCtx, hand[16], '#30ff30'); // Ring base (16)
// Pinky
drawLandmarks(canvasCtx, hand[18], '#1565c0'); // Pinky tip (18)
drawLandmarks(canvasCtx, hand[19], '#1565c0'); // Pinky base (19)
drawLandmarks(canvasCtx, hand[20], '#1565c0'); // Pinky base (20)
drawLandmarks(canvasCtx, hand[0], '#ff3030'); // Wrist (0)
drawLandmarks(canvasCtx, hand[1], '#ff3030'); // Palm base (1)
drawLandmarks(canvasCtx, hand[5], '#ff3030'); // Index palm (5)
drawLandmarks(canvasCtx, hand[9], '#ff3030'); // Middle palm (9)
drawLandmarks(canvasCtx, hand[13], '#ff3030'); // Ring palm (13)
drawLandmarks(canvasCtx, hand[17], '#ff3030'); // Pinky palm (17)
cropCanvas(canvasElement, crop_left, crop_top, crop_right - crop_left, crop_bottom - crop_top)
}
// Add more drawing calls for each landmark collection as needed
//# sourceURL=pen.js
}
function iterate(x, y) {
x_array.push(x.x)
y_array.push(x.y)
}
const cropCanvas = (sourceCanvas, left, top, width, height) => {
let destCanvas = document.createElement('canvas');
destCanvas.width = 224;
var cropAspectRatio = width / height;
destCanvas.height = 224 / cropAspectRatio
destCanvas.getContext("2d").drawImage(
sourceCanvas,
left, top, width, height, // source rect with content to crop
0, 0, 224, destCanvas.height); // newCanvas, same size as source
var predictionInput = tf.browser.fromPixels(destCanvas.getContext("2d").getImageData(0, 0, 224, 224))
predict(tf.expandDims(predictionInput, 0));
}
async function predict(inputTensor) {
//console.log("in predict")
var letter_list = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z", "#"]
objectDetector.then(function (res) {
var prediction = res.predict(inputTensor);
var outputArray = prediction.dataSync(); // Get the output as an array
var predictedClass = outputArray.indexOf(Math.max(...outputArray)); // Get the index
var current_result = letter_list[predictedClass]
var previous_result = document.getElementById("predicted_result").innerText
document.getElementById("predicted_result").innerText = current_result
var current_time = Math.round(Date.now())
if (previous_result == current_result) {
if (current_time - last_letter_time > 1000) {
last_letter_time = current_time
word_list.push(current_result)
console.log(word_list)
document.getElementById("text").value = word_list.join('')
}
}
else {
last_letter_time = current_time
}
console.log(letter_list[predictedClass]);
}, function (err) {
console.log(err);
});
}
function drawLandmarks(canvasCtx, landmarks, color) {
var image_height = (video.videoHeight / video.videoWidth) * canvasElement.width
var image_width = canvasElement.width
canvasCtx.fillStyle = color;
canvasCtx.strokeStyle = 'white';
canvasCtx.lineWidth = 1;
canvasCtx.beginPath();
canvasCtx.arc(landmarks.x * image_width, landmarks.y * image_height, 6, 0, 2 * Math.PI);
canvasCtx.fill();
canvasCtx.stroke();
}
function drawConnection(startNode, endNode, strokeColor, strokeWidth) {
var image_height = (video.videoHeight / video.videoWidth) * canvasElement.width
var image_width = canvasElement.width
canvasCtx.strokeStyle = strokeColor;
canvasCtx.lineWidth = strokeWidth;
canvasCtx.beginPath();
canvasCtx.moveTo(startNode.x * image_width, startNode.y * image_height);
canvasCtx.lineTo(endNode.x * image_width, endNode.y * image_height);
canvasCtx.stroke();
}
function calculateCanvasBrightness(canvas) {
const context = canvas.getContext('2d');
// Get the image data from the canvas
const imageData = context.getImageData(0, 0, canvas.width, canvas.height);
const data = imageData.data;
let totalBrightness = 0;
let pixelCount = 0;
// Loop through each pixel
for (let i = 0; i < data.length; i += 4) {
const r = data[i]; // Red
const g = data[i + 1]; // Green
const b = data[i + 2]; // Blue
// Calculate brightness for this pixel
const brightness = 0.299 * r + 0.587 * g + 0.114 * b;
totalBrightness += brightness;
pixelCount++;
}
// Calculate average brightness
const averageBrightness = totalBrightness / pixelCount;
return averageBrightness;
}
</script>
<script src="https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.0/wasm/vision_wasm_internal.js"
crossorigin="anonymous"></script>
</body>
</html> |