Victor Phan
340 lines
117 KiB
HTML
340 lines
117 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 - 20251221_121852</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 - 21/12/2025 12:18:53</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">44.9%</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">43.8%</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">510</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">128</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">7</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">CNN</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">[105.6, 9.3, 106.2, 9.8]</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">2023-03-01/2023-05-31</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_cnn_20251221_121846.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>0.333</td>
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<td>0.500</td>
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<td>0.400</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>0.311</td>
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<td>0.826</td>
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<td>0.452</td>
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<td>23</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>0.500</td>
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<td>0.045</td>
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<td>0.083</td>
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<td>22</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>0.440</td>
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<td>0.524</td>
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<td>0.478</td>
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<td>21</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>1.000</td>
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<td>0.444</td>
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<td>0.615</td>
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<td>9</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>0.833</td>
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<td>0.500</td>
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<td>0.625</td>
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<td>30</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>0.000</td>
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<td>0.000</td>
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<td>0.000</td>
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<td>11</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>0.488</td>
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<td>0.406</td>
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<td>0.379</td>
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<td>128</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>0.511</td>
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<td>0.438</td>
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<td>0.401</td>
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<td>128</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;">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: 21/12/2025 12:18:53</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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