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_120153</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 12:01:54</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">78.2%</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">72.0%</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_120129.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>0.667</td>
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<td>0.780</td>
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<td>0.719</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>0.595</td>
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<td>0.647</td>
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<td>0.620</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>0.534</td>
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<td>0.589</td>
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<td>0.560</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>0.656</td>
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<td>0.720</td>
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<td>0.686</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 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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 12:01:54</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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