WaveSign/index.html at main · nglkk/WaveSign · GitHub

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<!DOCTYPE html>
<html lang="en">
    <head>
        <title>WaveSign Application</title>
        <h1>WaveSign</h1>
    </head>
    <body>
        <div>Teachable Machine Image Model</div>
            <button id = "toggle-webcam" type="button" onclick="toggleWebcam()">Start/Stop</button>

            <form id = "image-upload-form">
                <label for="image-upload">Upload an image:</label>
                <input type="file" id="image-upload" accept="image/*" onchange="handleImageUpload(event)">
                <br><button id = "submit-button" type = "submit">Submit Image</button>
                <br>
                <img id = "uploaded-image" style = "display: none; max-width: 200px; margin-top: 10px;">
            </form>

            <a href = "aslData.html">
                <button type = "button">View ASL Images</button>
            </a>

        <div id="webcam-container"></div>
        <div id="label-container"></div>

        <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@latest/dist/tf.min.js"></script>
        <script src="https://cdn.jsdelivr.net/npm/@teachablemachine/image@latest/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/";

            let model, webcam, labelContainer, maxPredictions;

            // Load the image model and setup the webcam

            async function loadModel() {
                if (!model) {
                    const modelURL = URL + "model.json";
                    const metadataURL = URL + "metadata.json";
                    model = await tmImage.load(modelURL, metadataURL);
                    maxPredictions = model.getTotalClasses();
                }

                labelContainer = document.getElementById("label-container");
                labelContainer.innerHTML = "";
                for (let i = 0; i < maxPredictions; i++) {
                    labelContainer.appendChild(document.createElement("div"));
                }
            }

            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() {
                // predict can take in an image, video or canvas html element
                const 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;
                }
            }

            async function toggleWebcam() {
                const button = document.getElementById("toggle-webcam");

                if (!webcam) {
                    await startWebcam();
                    button.textContent = "Start/Stop Webcam";
                } else {
                    stopWebcam();
                    button.textContent = "Start/Stop Webcam";
                }
            }

            async function predictImage(imageElement) {
                await loadModel();

                const prediction = await model.predict(imageElement);
                labelContainer.innerHTML = "";
                for (let i = 0; i < maxPredictions; i++) {
                    const classPrediction = prediction[i].className + ": " + prediction[i].probability.toFixed(2);
                    const div = document.createElement("div");
                    div.innerHTML = classPrediction;
                    labelContainer.appendChild(div);
                }
            }

            let uploadedImage = null;

            function handleImageUpload(event) {
                const file = event.target.files[0];
                const imageElement = document.getElementById("uploaded-image");

                if (!file) {
                    alert("Please upload an image.");
                    return;
                }

                const reader = new FileReader();
                reader.onload = function(e) {
                    imageElement.src = e.target.result;
                    imageElement.style.display = "block";

                    // Stop and hide webcam if active
                    if (webcam) {
                        webcam.stop();
                        webcam.canvas.remove();
                        webcam = null;
                    }

                    imageElement.onload = async function() {
                        await loadModel();
                        await predictImage(imageElement);
                    };
                };
                reader.readAsDataURL(file);
            }

            document.getElementById("image-upload-form").addEventListener("submit", function(event) {
                event.preventDefault();

                const imageElement = document.getElementById("uploaded-image");

                if (!imageElement || !imageElement.src || imageElement.style.display === "none") {
                    alert("Please upload an image.");
                    return;
                }

                predictImage(imageElement);

            });

            async function startWebcam() {
                await loadModel();

                const imageElement = document.getElementById("uploaded-image");
                imageElement.style.display = "none";

                if (webcam) return;

                const flip = true;
                webcam = new tmImage.Webcam(200, 200, flip);
                await webcam.setup(); // request access to the webcam
                await webcam.play();

                document.getElementById("webcam-container").appendChild(webcam.canvas);
                window.requestAnimationFrame(loop);
            }

            function stopWebcam() {
                if (webcam) {
                    webcam.stop();
                    webcam.canvas.remove();
                    webcam = null;
                }
            }

        </script>

        <style>
            #start-stop-button {
                font-weight: bold;
                font-size: 20px;
                margin-bottom: 16px;
            }
            #stop-button, #webcam-button, #submit-button {
                margin-bottom: 16px;
            }
        </style>
    </body>
</html>