Victor Phan
340 lines
117 KiB
HTML
Executable File
340 lines
117 KiB
HTML
Executable File
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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_164522</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 16:45:23</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">50.6%</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">50.8%</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_163841.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>0.375</td>
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<td>0.250</td>
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<td>0.300</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>0.364</td>
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<td>0.870</td>
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<td>0.513</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>0.615</td>
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<td>0.364</td>
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<td>0.457</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>0.700</td>
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<td>0.778</td>
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<td>0.737</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>0.941</td>
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<td>0.533</td>
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<td>0.681</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>0.491</td>
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<td>0.474</td>
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<td>0.452</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>0.548</td>
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<td>0.508</td>
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<td>0.489</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 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;">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 16:45:23</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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