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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Facial Expression Recognition</title>
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<style>
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body {
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font-family: Arial, sans-serif;
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background-color: #f4f4f4;
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text-align: center;
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margin: 0;
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padding: 0;
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}
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.container {
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width: 70%;
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margin: auto;
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padding: 20px;
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background: white;
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border-radius: 8px;
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box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
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margin-top: 50px;
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}
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button, input[type="file"] {
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margin: 10px;
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padding: 10px 15px;
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border: none;
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border-radius: 5px;
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background: #007BFF;
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color: white;
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cursor: pointer;
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}
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button:hover {
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background: #0056b3;
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}
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input[type="file"] {
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cursor: pointer;
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}
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.output {
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margin-top: 20px;
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font-size: 18px;
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color: #333;
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}
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</style>
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</head>
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<body>
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<h1>Facial Expression Recognition</h1>
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<div class="container">
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<h2>Real-Time Detection</h2>
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<video id="video" width="480" height="360" autoplay></video>
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<button onclick="startRealTimePrediction()">Start Real-Time Detection</button>
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<div id="realTimeOutput" class="output"></div>
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<h2>Image Upload</h2>
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<input type="file" id="imageInput" accept="image/*">
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<button onclick="uploadImage()">Upload and Predict</button>
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<div id="uploadOutput" class="output"></div>
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</div>
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<script>
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function startRealTimePrediction() {
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const video = document.getElementById('video');
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navigator.mediaDevices.getUserMedia({ video: true })
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.then(stream => {
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video.srcObject = stream;
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})
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.catch(err => {
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console.error("Error accessing camera: ", err);
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});
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setInterval(() => {
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const canvas = document.createElement('canvas');
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canvas.width = video.videoWidth;
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canvas.height = video.videoHeight;
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canvas.getContext('2d').drawImage(video, 0, 0);
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const imageData = canvas.toDataURL('image/png');
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fetch('/predict', {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json'
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},
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body: JSON.stringify({ image: imageData })
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})
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.then(response => response.json())
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.then(data => {
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document.getElementById('realTimeOutput').textContent = `Prediction: ${data.prediction}`;
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})
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.catch(error => console.error('Error:', error));
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}, 1000);
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}
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function uploadImage() {
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const input = document.getElementById('imageInput');
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const file = input.files[0];
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if (!file) {
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alert('Please upload an image.');
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return;
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}
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const formData = new FormData();
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formData.append('image', file);
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fetch('/predict', {
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method: 'POST',
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body: formData
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})
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.then(response => response.json())
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.then(data => {
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document.getElementById('uploadOutput').textContent = `Prediction: ${data.prediction}`;
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})
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.catch(error => console.error('Error:', error));
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}
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</script>
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</body>
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</html>
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