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_225505</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 22:55:06</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">69.2%</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">69.3%</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">MOBILENET-LRASPP</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_mobilenet-lraspp_20260105_225459.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>0.348</td>
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<td>0.667</td>
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<td>0.457</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>0.733</td>
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<td>0.268</td>
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<td>0.393</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>0.235</td>
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<td>0.444</td>
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<td>0.308</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>0.486</td>
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<td>0.500</td>
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<td>0.493</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>0.767</td>
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<td>0.885</td>
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<td>0.821</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>1.000</td>
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<td>0.962</td>
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<td>0.980</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>0.929</td>
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<td>0.886</td>
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<td>0.907</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>0.774</td>
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<td>0.923</td>
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<td>0.842</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>0.659</td>
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<td>0.692</td>
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<td>0.650</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>0.733</td>
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<td>0.693</td>
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<td>0.687</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 22:55:06</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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