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_112532</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 11:25:33</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">77.0%</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">70.6%</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_112458.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>0.579</td>
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<td>0.647</td>
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<td>0.611</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>0.594</td>
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<td>0.731</td>
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<td>0.655</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>0.926</td>
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<td>0.962</td>
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<td>0.943</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>0.464</td>
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<td>0.500</td>
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<td>0.481</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>0.523</td>
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<td>0.575</td>
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<td>0.547</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>0.645</td>
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<td>0.706</td>
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<td>0.674</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 11:25:33</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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