deeplearning/index.html at main · AndyCandy96/deeplearning · GitHub

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<!DOCTYPE html>
<html lang="de">
<head>
    <meta charset="UTF-8">
    <title>TensorFlow.js Beispiel</title>
    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@4.18.0/dist/tf.min.js"></script> <!-- TensorFlow.js -->
    <script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/mobilenet"></script> <!-- Vorgefertigtes Modell -->
    <style>
        body {
            font-family: Arial, sans-serif;
            text-align: center;
            margin-top: 50px;
        }
        img {
            max-width: 300px;
        }
    </style>
</head>
<body>
    <h1>TensorFlow.js - Bild Klassifikation</h1>

    <input type="file" id="upload" accept="image/*">
    <br><br>
    <img id="image" src="" alt="Bild wird hier angezeigt" style="display:none;">

    <h2 id="ergebnis"></h2>

    <script>
        let net;

        async function app() {
            console.log('Modell wird geladen...');
            net = await mobilenet.load(); // Vorgefertigtes Mobilenet-Modell laden
            console.log('Modell geladen.');

            const upload = document.getElementById('upload');
            const imgElement = document.getElementById('image');
            const ergebnisElement = document.getElementById('ergebnis');

            upload.addEventListener('change', async (event) => {
                const file = event.target.files[0];
                const reader = new FileReader();
                reader.onload = function(e) {
                    imgElement.src = e.target.result;
                    imgElement.style.display = 'block';
                };
                reader.readAsDataURL(file);

                reader.onloadend = async function() {
                    await new Promise(resolve => setTimeout(resolve, 100)); // Kleiner Trick, damit das Bild vollständig geladen ist
                    const result = await net.classify(imgElement);
                    console.log(result);
                    ergebnisElement.innerText = `Erkannt: ${result[0].className} (${(result[0].probability * 100).toFixed(2)}%)`;
                };
            });
        }

        app();
    </script>
</body>
</html>