| <!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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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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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|
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| const formData = new FormData();
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| formData.append('image', file);
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|
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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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|
|
