348 lines
120 KiB
HTML
348 lines
120 KiB
HTML
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<!DOCTYPE html>
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<html lang="vi">
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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>Training Report - 20260105_123055</title>
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<style>
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* {
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margin: 0;
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padding: 0;
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box-sizing: border-box;
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}
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body {
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font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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background: #f5f5f5;
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padding: 20px;
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line-height: 1.6;
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}
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.container {
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max-width: 1200px;
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margin: 0 auto;
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background: white;
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border-radius: 15px;
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box-shadow: 0 10px 40px rgba(0,0,0,0.1);
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overflow: hidden;
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}
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.header {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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padding: 40px;
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text-align: center;
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}
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.header h1 {
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font-size: 2.5em;
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margin-bottom: 10px;
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}
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.header .subtitle {
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opacity: 0.9;
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font-size: 1.1em;
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}
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.content {
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padding: 40px;
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}
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.section {
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margin-bottom: 40px;
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}
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.section h2 {
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color: #667eea;
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border-bottom: 3px solid #667eea;
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padding-bottom: 10px;
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margin-bottom: 20px;
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font-size: 1.5em;
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}
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.stats-grid {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
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gap: 20px;
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margin-bottom: 30px;
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}
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.stat-card {
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background: linear-gradient(135deg, #667eea15 0%, #764ba215 100%);
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padding: 25px;
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border-radius: 10px;
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text-align: center;
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border: 1px solid #667eea30;
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}
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.stat-card .value {
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font-size: 2.5em;
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font-weight: bold;
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color: #667eea;
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}
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.stat-card .label {
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color: #666;
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margin-top: 5px;
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}
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.stat-card.success .value {
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color: #28a745;
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}
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.stat-card.warning .value {
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color: #ffc107;
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}
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table {
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width: 100%;
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border-collapse: collapse;
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margin: 20px 0;
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}
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th, td {
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padding: 12px 15px;
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text-align: left;
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border-bottom: 1px solid #ddd;
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}
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th {
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background: #667eea;
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color: white;
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}
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tr:hover {
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background-color: #f5f5f5;
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}
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.conf-matrix {
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font-size: 14px;
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}
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.conf-matrix th, .conf-matrix td {
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text-align: center;
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padding: 8px;
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}
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.chart-container {
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text-align: center;
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margin: 20px 0;
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}
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.chart-container img {
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max-width: 100%;
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border-radius: 10px;
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box-shadow: 0 4px 15px rgba(0,0,0,0.1);
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}
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.info-box {
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background: #e3f2fd;
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padding: 20px;
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border-radius: 10px;
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border-left: 5px solid #2196f3;
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margin: 20px 0;
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}
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.info-row {
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display: flex;
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margin: 10px 0;
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}
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.info-label {
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font-weight: bold;
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width: 200px;
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color: #555;
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}
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.info-value {
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color: #333;
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}
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.footer {
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background: #f8f9fa;
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padding: 20px;
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text-align: center;
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color: #666;
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font-size: 14px;
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}
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@media print {
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body {
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background: white;
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padding: 0;
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}
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.container {
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box-shadow: none;
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}
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}
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</style>
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</head>
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<body>
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<div class="container">
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<div class="header">
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<h1>📊 Báo Cáo Training Model</h1>
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<p class="subtitle">Land Classification - 05/01/2026 12:30:56</p>
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</div>
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<div class="content">
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<!-- Summary Stats -->
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<div class="section">
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<h2>📈 Tóm Tắt Kết Quả</h2>
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<div class="stats-grid">
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<div class="stat-card success">
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<div class="value">77.3%</div>
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<div class="label">Train Accuracy</div>
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</div>
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<div class="stat-card warning">
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<div class="value">72.5%</div>
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<div class="label">Test Accuracy</div>
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</div>
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<div class="stat-card">
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<div class="value">868</div>
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<div class="label">Training Samples</div>
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</div>
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<div class="stat-card">
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<div class="value">218</div>
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<div class="label">Testing Samples</div>
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</div>
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<div class="stat-card">
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<div class="value">8</div>
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<div class="label">Số Classes</div>
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</div>
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<div class="stat-card">
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<div class="value">20%</div>
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<div class="label">Test Size</div>
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</div>
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</div>
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</div>
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<!-- Configuration Info -->
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<div class="section">
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<h2>⚙️ Cấu Hình Training</h2>
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<div class="info-box">
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<div class="info-row">
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<span class="info-label">🤖 Model Type:</span>
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<span class="info-value">SWIN-UNET</span>
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</div>
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<div class="info-row">
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<span class="info-label">📍 Khu vực (bbox):</span>
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<span class="info-value">[105.561448, 9.264228, 106.298669, 9.931334]</span>
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</div>
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<div class="info-row">
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<span class="info-label">📅 Thời gian:</span>
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<span class="info-value">2023-03-01/2023-12-31</span>
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</div>
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<div class="info-row">
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<span class="info-label">📐 Độ phân giải:</span>
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<span class="info-value">20m</span>
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</div>
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<div class="info-row">
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<span class="info-label">💾 Model Path:</span>
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<span class="info-value">model_train/model_swin-unet_20260105_123033.joblib</span>
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</div>
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</div>
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</div>
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<!-- Classification Report -->
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<div class="section">
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<h2>📋 Classification Report</h2>
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<table>
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<thead>
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<tr>
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<th>Loại đất</th>
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<th>Precision</th>
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<th>Recall</th>
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<th>F1-Score</th>
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<th>Support</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><strong>0</strong></td>
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<td>0.000</td>
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<td>0.000</td>
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<td>0.000</td>
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<td>12</td>
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</tr>
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<tr>
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<td><strong>1</strong></td>
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<td>0.681</td>
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<td>0.780</td>
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<td>0.727</td>
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<td>41</td>
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</tr>
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<tr>
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<td><strong>2</strong></td>
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<td>0.000</td>
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<td>0.000</td>
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<td>0.000</td>
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<td>9</td>
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</tr>
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<tr>
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<td><strong>3</strong></td>
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<td>0.605</td>
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<td>0.676</td>
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<td>0.639</td>
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<td>34</td>
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</tr>
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<tr>
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<td><strong>4</strong></td>
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<td>0.625</td>
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<td>0.769</td>
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<td>0.690</td>
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<td>26</td>
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</tr>
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<tr>
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<td><strong>5</strong></td>
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<td>0.929</td>
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<td>1.000</td>
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<td>0.963</td>
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<td>26</td>
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</tr>
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<tr>
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<td><strong>6</strong></td>
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<td>0.956</td>
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<td>0.977</td>
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<td>0.966</td>
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<td>44</td>
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</tr>
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<tr>
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<td><strong>7</strong></td>
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<td>0.500</td>
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<td>0.538</td>
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<td>0.519</td>
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<td>26</td>
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</tr>
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<tr style="background-color: #f0f0f0; font-weight: bold;">
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<td>macro avg</td>
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<td>0.537</td>
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<td>0.593</td>
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<td>0.563</td>
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<td>218</td>
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</tr>
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<tr style="background-color: #f0f0f0; font-weight: bold;">
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<td>weighted avg</td>
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<td>0.660</td>
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<td>0.725</td>
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<td>0.690</td>
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<td>218</td>
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</tr>
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</tbody>
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</table>
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</div>
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<!-- Metrics Chart -->
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<div class="section"><h2>📊 Biểu Đồ Metrics</h2><div class="chart-container"><img src="data:image/png;base64,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alt="Metrics Chart"></div></div>
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<div class="section"><h2>📊 Phân Bố Số Mẫu</h2><div class="chart-container"><img 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" alt="Class Distribution"></div></div>
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<!-- Confusion Matrix -->
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<div class="section">
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<h2>🔢 Confusion Matrix</h2>
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<div class="chart-container"><img 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" alt="Confusion Matrix"></div>
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</div>
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<!-- Classes List -->
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<div class="section">
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<h2>🏷️ Danh Sách Các Loại Đất</h2>
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<div class="info-box">
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<ul style="list-style: none; display: flex; flex-wrap: wrap; gap: 10px;">
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<li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">0</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">1</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">2</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">3</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">4</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">5</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">6</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">7</li>
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</ul>
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</div>
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</div>
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</div>
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<div class="footer">
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<p>🌍 Land Classification Training System | Generated: 05/01/2026 12:30:56</p>
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<p>Data Source: Microsoft Planetary Computer (Sentinel-2 L2A, Sentinel-1 RTC)</p>
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</div>
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</div>
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</body>
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</html>
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