lstlm
/
lcnn


			
				
					
						
						
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							<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>LineDetect Alpha_v1.02</title>
    <style>
        body {
            font-family: Arial, sans-serif;
            margin: 0;
            padding: 0;
            display: flex;
            justify-content: center;
            align-items: center;
            height: 100vh;
            background-color: #f0f4f8;
        }
        .container {
            text-align: center;
            width: 80%;
            max-width: 2000px;
            background-color: #ffffff;
            border-radius: 8px;
            padding: 40px;
            box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
            overflow: auto; /* ?????? */
        }
        h1 {
            color: #333;
            font-size: 24px;
            margin-bottom: 20px;
        }
        h2.subtitle {
            color: #666;
            font-size: 18px;
            margin-bottom: 20px;
        }
        input[type="file"] {
            margin-bottom: 20px;
            padding: 10px;
            font-size: 16px;
            border: 1px solid #ccc;
            border-radius: 4px;
        }
        button {
            padding: 12px 20px;
            background-color: #4CAF50;
            color: white;
            border: none;
            border-radius: 4px;
            font-size: 16px;
            cursor: pointer;
            transition: background-color 0.3s;
        }
        button:hover {
            background-color: #45a049;
        }
        .result {
            visibility: hidden; /* ??????? */
            display: flex;
            flex-direction: column;
            align-items: center;
            margin-top: 40px;
            max-height: 60vh; /* ?????? */
            overflow-y: auto; /* ??????? */
        }
        .result img {
            max-width: 100%; /* ????????? */
            height: auto; /* ??????????? */
            object-fit: cover;
            border-radius: 8px;
            box-shadow: 0 4px 10px rgba(0, 0, 0, 0.1);
            margin-bottom: 20px;
        }
        .uploaded-image {
            width: 512px; /* ???? */
            height: 512px; /* ???? */
            object-fit: cover; /* ???????????????? */
            border-radius: 8px;
            box-shadow: 0 4px 10px rgba(0, 0, 0, 0.1);
        }
    </style>
</head>
<body>
    <div class="container">
        <h1>LineDetect Alpha_v1.02</h1> <!-- ???? -->
        <h2 class="subtitle">请上传图片</h2> <!-- ????? -->
        <input type="file" id="fileInput" accept="image/*" />
        <button onclick="uploadImage()">上传</button> <!-- ?????? -->
        <div class="result">
            <div>
                <h2>原图</h2>
                <img id="uploadedImage" class="uploaded-image" src="" alt="Uploaded Image" style="display: none;" />
            </div>
            <div>
                <h2>结果</h2>
                <img id="resultImage" src="" alt="Prediction Result" style="display: none;" />
            </div>
        </div>
    </div>
    <script>
        async function uploadImage() {
            const fileInput = document.getElementById('fileInput');
            const file = fileInput.files[0];
            if (!file) {
                alert("???????????");
                return;
            }

            // ?? canvas ?????? 512x512
            const resizedImageBlob = await resizeImage(file, 512, 512);

            // ???????
            const uploadedImage = document.getElementById('uploadedImage');
            uploadedImage.src = URL.createObjectURL(resizedImageBlob);
            uploadedImage.style.display = 'block';

            // ???????????
            const formData = new FormData();
            formData.append("file", resizedImageBlob, file.name); // ??????
            const response = await fetch('http://192.168.50.100:808/predict', {
                method: 'POST',
                body: formData,
            });
            if (response.ok) {
                const resultBlob = await response.blob();
                const resultImage = document.getElementById('resultImage');
                resultImage.src = URL.createObjectURL(resultBlob);
                resultImage.style.display = 'block';
                document.querySelector('.result').style.visibility = 'visible'; // ????
            } else {
                alert("?????");
            }
        }

        /**
         * ?? canvas ????
         * @param {File} file - ??????
         * @param {number} width - ????
         * @param {number} height - ????
         * @returns {Promise<Blob>} - ???????? Blob
         */
        async function resizeImage(file, width, height) {
            return new Promise((resolve, reject) => {
                const img = new Image();
                img.onload = () => {
                    const canvas = document.createElement('canvas');
                    canvas.width = width;
                    canvas.height = height;
                    const ctx = canvas.getContext('2d');

                    // ????????????
                    ctx.drawImage(img, 0, 0, width, height);

                    // ? canvas ??? Blob
                    canvas.toBlob(blob => {
                        resolve(blob);
                    }, file.type || 'image/jpeg');
                };
                img.onerror = reject;
                img.src = URL.createObjectURL(file);
            });
        }
    </script>
</body>
</html>