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<html lang="tr">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Teachable Machine Görüntü Modeli</title>
<script src="https://cdn.tailwindcss.com"></script>
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap" rel="stylesheet">
<style>
/* Custom styles that can't be done with Tailwind */
input[type="file"]::-webkit-file-upload-button {
visibility: hidden;
}
input[type="file"]::before {
content: 'Görsel Yükle';
display: inline-block;
background: linear-gradient(to bottom, #3b82f6, #2563eb);
border-radius: 9999px;
padding: 0.5rem 1rem;
outline: none;
white-space: nowrap;
-webkit-user-select: none;
cursor: pointer;
font-weight: 600;
font-size: 0.875rem;
color: white;
margin-right: 10px;
}
input[type="file"]:hover::before {
background: linear-gradient(to bottom, #2563eb, #1d4ed8);
}
input[type="file"]:active::before {
background: #1d4ed8;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
.loading-spinner {
border: 4px solid #f3f4f6;
border-top: 4px solid #3b82f6;
border-radius: 50%;
width: 30px;
height: 30px;
animation: spin 1s linear infinite;
}
</style>
</head>
<body class="font-sans bg-blue-50 min-h-screen flex flex-col items-center justify-center p-5 text-gray-800">
<div class="w-full max-w-3xl mx-auto text-center">
<!-- Header Section -->
<div class="mb-8">
<h1 class="text-3xl md:text-4xl font-bold text-blue-600 mb-4">Teachable Machine Görüntü Modeli</h1>
<p class="text-gray-600 max-w-2xl mx-auto">
Yapay zeka modelinizle görüntüleri analiz edin. Kameranızı kullanabilir veya bir görsel yükleyebilirsiniz.
</p>
</div>
<!-- Controls Section -->
<div class="bg-white rounded-xl shadow-lg p-6 mb-8 w-full max-w-md mx-auto">
<div class="space-y-4">
<button
onclick="startWebcam()"
class="w-full bg-blue-500 hover:bg-blue-600 text-white font-medium py-3 px-6 rounded-full transition-all duration-200 transform hover:-translate-y-1 shadow-md"
>
<div class="flex items-center justify-center space-x-2">
<svg xmlns="http://www.w3.org/2000/svg" class="h-5 w-5" viewBox="0 0 20 20" fill="currentColor">
<path d="M2 6a2 2 0 012-2h6a2 2 0 012 2v8a2 2 0 01-2 2H4a2 2 0 01-2-2V6zM14 6a2 2 0 012-2h2a2 2 0 012 2v8a2 2 0 01-2 2h-2a2 2 0 01-2-2V6z" />
</svg>
<span>Kamerayı Başlat</span>
</div>
</button>
<div class="relative">
<input
type="file"
id="imageUpload"
accept="image/*"
class="w-full border-2 border-dashed border-blue-200 rounded-lg p-4 bg-blue-50 text-blue-500 font-medium cursor-pointer focus:outline-none focus:ring-2 focus:ring-blue-300 focus:border-transparent"
>
</div>
<button
onclick="processUploadedImage()"
class="w-full bg-green-500 hover:bg-green-600 text-white font-medium py-3 px-6 rounded-full transition-all duration-200 transform hover:-translate-y-1 shadow-md"
>
<div class="flex items-center justify-center space-x-2">
<svg xmlns="http://www.w3.org/2000/svg" class="h-5 w-5" viewBox="0 0 20 20" fill="currentColor">
<path fill-rule="evenodd" d="M3 17a1 1 0 011-1h12a1 1 0 110 2H4a1 1 0 01-1-1zm3.293-7.707a1 1 0 011.414 0L9 10.586V3a1 1 0 112 0v7.586l1.293-1.293a1 1 0 111.414 1.414l-3 3a1 1 0 01-1.414 0l-3-3a1 1 0 010-1.414z" clip-rule="evenodd" />
</svg>
<span>Görseli Analiz Et</span>
</div>
</button>
</div>
</div>
<!-- Media Display Section -->
<div class="flex flex-col md:flex-row items-center justify-center gap-8 w-full mb-8">
<div id="media-container" class="bg-white border-4 border-blue-200 rounded-xl overflow-hidden shadow-xl w-56 h-56 flex items-center justify-center">
<div class="text-gray-400 text-center p-4">
<svg xmlns="http://www.w3.org/2000/svg" class="h-12 w-12 mx-auto mb-2" fill="none" viewBox="0 0 24 24" stroke="currentColor">
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M4 16l4.586-4.586a2 2 0 012.828 0L16 16m-2-2l1.586-1.586a2 2 0 012.828 0L20 14m-6-6h.01M6 20h12a2 2 0 002-2V6a2 2 0 00-2-2H6a2 2 0 00-2 2v12a2 2 0 002 2z" />
</svg>
<p>Kamera veya görsel burada görünecek</p>
</div>
</div>
<div id="label-container" class="bg-white rounded-xl shadow-xl p-6 w-full max-w-md">
<h3 class="text-xl font-semibold text-gray-700 mb-4">Analiz Sonuçları</h3>
<div class="space-y-3 text-gray-600">
<div class="py-2 border-b border-gray-100">Model yükleniyor...</div>
</div>
</div>
</div>
<!-- Loading Spinner -->
<div id="loadingSpinner" class="loading-spinner hidden my-4"></div>
<!-- Info Box -->
<div class="bg-blue-100 border-l-4 border-blue-500 text-blue-700 p-4 rounded-lg max-w-2xl mx-auto mt-6" role="alert">
<div class="flex items-center">
<svg xmlns="http://www.w3.org/2000/svg" class="h-6 w-6 mr-2" fill="none" viewBox="0 0 24 24" stroke="currentColor">
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M13 16h-1v-4h-1m1-4h.01M21 12a9 9 0 11-18 0 9 9 0 0118 0z" />
</svg>
<p class="font-medium">İpucu:</p>
</div>
<p class="mt-2">Kamerayı başlatın veya bir görsel yükleyin. Model görüntüyü analiz edecek ve sonuçları gösterecektir.</p>
</div>
</div>
<!-- TensorFlow.js and Teachable Machine libraries -->
<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">
// Teachable Machine modelinizin URL'si
// Kendi modelinizi kullanıyorsanız bu URL'yi değiştirmeniz gerekmektedir.
const URL = "https://teachablemachine.withgoogle.com/models/SMwI3_lD/";
let model, webcam, labelContainer, maxPredictions;
let isWebcamActive = false; // Kameranın aktif olup olmadığını takip eder
let loopId; // requestAnimationFrame döngüsünün ID'si
// Sayfa yüklendiğinde modeli önceden yükle
window.onload = async () => {
await loadModel();
};
// Modeli yükleme fonksiyonu
async function loadModel() {
const modelURL = URL + "model.json";
const metadataURL = URL + "metadata.json";
try {
model = await tmImage.load(modelURL, metadataURL);
maxPredictions = model.getTotalClasses();
labelContainer = document.getElementById("label-container");
// Clear existing content
labelContainer.querySelector('div.space-y-3').innerHTML = '';
// Create divs for each prediction class
for (let i = 0; i < maxPredictions; i++) {
const div = document.createElement('div');
div.className = 'py-2 border-b border-gray-100';
labelContainer.querySelector('div.space-y-3').appendChild(div);
}
console.log("Model başarıyla yüklendi.");
} catch (error) {
console.error("Model yüklenirken hata oluştu:", error);
if (labelContainer) {
labelContainer.querySelector('div.space-y-3').innerHTML = '<div class="text-red-500">Hata: Model yüklenemedi. URL\'yi kontrol edin.</div>';
}
}
}
// Kamerayı başlatma fonksiyonu
async function startWebcam() {
// Eğer kamera zaten aktifse veya model yüklenmediyse bir şey yapma
if (isWebcamActive || !model) return;
// Önceki görüntüyü temizle ve yükleme göstergesini gizle
document.getElementById("media-container").innerHTML = '';
document.getElementById("loadingSpinner").classList.add('hidden');
clearLabelContainer();
try {
const flip = true; // Web kamerasını yatayda çevir
webcam = new tmImage.Webcam(224, 224, flip); // Genişlik, yükseklik, çevirme ayarı
await webcam.setup(); // Web kamerasına erişim izni iste
await webcam.play(); // Web kamerasını başlat
document.getElementById("media-container").appendChild(webcam.canvas);
isWebcamActive = true;
loopId = window.requestAnimationFrame(loop); // Sürekli tahmin için animasyon döngüsünü başlat
console.log("Kamera başlatıldı.");
} catch (error) {
console.error("Kamera başlatılırken hata oluştu:", error);
isWebcamActive = false;
if (labelContainer) {
labelContainer.querySelector('div.space-y-3').innerHTML = '<div class="text-red-500">Hata: Kameraya erişim sağlanamadı. Lütfen izin verin.</div>';
}
}
}
// Kamera döngüsü
async function loop() {
if (webcam && isWebcamActive) {
webcam.update(); // Web kamerası çerçevesini güncelle
await predict(webcam.canvas); // Tahmin yap
loopId = window.requestAnimationFrame(loop); // Bir sonraki kare için tekrar çağır
}
}
// Yüklenen görseli işleme fonksiyonu
async function processUploadedImage() {
// Eğer kamera aktifse durdur
stopWebcam();
const imageUpload = document.getElementById("imageUpload");
const file = imageUpload.files[0];
if (!file) {
showToast("Lütfen bir görsel dosyası seçin.", "warning");
return;
}
if (!model) {
showToast("Model henüz yüklenmedi. Lütfen bekleyin.", "error");
return;
}
// Önceki görüntüyü temizle ve yükleme göstergesini göster
document.getElementById("media-container").innerHTML = '';
document.getElementById("loadingSpinner").classList.remove('hidden');
clearLabelContainer();
const reader = new FileReader();
reader.onload = async (e) => {
const img = new Image();
img.onload = async () => {
document.getElementById("media-container").innerHTML = '';
document.getElementById("media-container").appendChild(img);
await predict(img); // Görsel üzerinde tahmin yap
document.getElementById("loadingSpinner").classList.add('hidden');
};
img.onerror = () => {
console.error("Görsel yüklenirken hata oluştu.");
document.getElementById("loadingSpinner").classList.add('hidden');
if (labelContainer) {
labelContainer.querySelector('div.space-y-3').innerHTML = '<div class="text-red-500">Hata: Görsel yüklenemedi.</div>';
}
};
img.src = e.target.result;
};
reader.readAsDataURL(file); // Dosyayı base64 string olarak oku
}
// Tahmin yapma fonksiyonu (hem kanvas hem de görsel için)
async function predict(inputElement) {
if (model && inputElement) {
const prediction = await model.predict(inputElement);
// Her sınıf için tahmin sonuçlarını göster
const resultDivs = labelContainer.querySelectorAll('div.space-y-3 > div');
for (let i = 0; i < maxPredictions; i++) {
const probability = prediction[i].probability.toFixed(2);
const percentage = Math.round(probability * 100);
// Create a progress bar
const progressBar = `
<div class="w-full bg-gray-200 rounded-full h-2.5 mt-1">
<div class="bg-blue-600 h-2.5 rounded-full" style="width: ${percentage}%"></div>
</div>
`;
resultDivs[i].innerHTML = `
<div class="flex justify-between items-center">
<span class="font-medium">${prediction[i].className}:</span>
<span class="font-semibold">${percentage}%</span>
</div>
${progressBar}
`;
}
}
}
// Kamerayı durdurma fonksiyonu
function stopWebcam() {
if (isWebcamActive && webcam) {
webcam.stop();
window.cancelAnimationFrame(loopId);
isWebcamActive = false;
console.log("Kamera durduruldu.");
}
}
// Etiket kapsayıcısını temizleme fonksiyonu
function clearLabelContainer() {
if (labelContainer) {
const resultDivs = labelContainer.querySelectorAll('div.space-y-3 > div');
resultDivs.forEach(div => {
div.innerHTML = '';
});
}
}
// Toast mesajı gösterme fonksiyonu
function showToast(message, type = 'info') {
const colors = {
info: 'bg-blue-500',
warning: 'bg-yellow-500',
error: 'bg-red-500',
success: 'bg-green-500'
};
const toast = document.createElement('div');
toast.className = `fixed bottom-4 right-4 text-white px-4 py-2 rounded-lg shadow-lg ${colors[type]} animate-fade-in`;
toast.textContent = message;
document.body.appendChild(toast);
setTimeout(() => {
toast.classList.remove('animate-fade-in');
toast.classList.add('animate-fade-out');
setTimeout(() => {
toast.remove();
}, 300);
}, 3000);
}
</script>
<p style="border-radius: 8px; text-align: center; font-size: 12px; color: #fff; margin-top: 16px;position: fixed; left: 8px; bottom: 8px; z-index: 10; background: rgba(0, 0, 0, 0.8); padding: 4px 8px;">Made with <img src="https://enzostvs-deepsite.hf.space/logo.svg" alt="DeepSite Logo" style="width: 16px; height: 16px; vertical-align: middle;display:inline-block;margin-right:3px;filter:brightness(0) invert(1);"><a href="https://enzostvs-deepsite.hf.space" style="color: #fff;text-decoration: underline;" target="_blank" >DeepSite</a> - 🧬 <a href="https://enzostvs-deepsite.hf.space?remix=yusra21/teachable-machine" style="color: #fff;text-decoration: underline;" target="_blank" >Remix</a></p></body>
</html> |