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README.md
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body { font-family: Arial, sans-serif; margin: 40px; line-height: 1.6; color: #333; }
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</ul>
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<h2>🔍 Use Case</h2>
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<p>
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<h2>🧠 Model Overview</h2>
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<ul>
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<li><strong>Architecture:</strong> CNN (Conv2D, MaxPooling, Dense)</li>
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<li><strong>Input:</strong> 224x224 RGB</li>
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<li><strong>Output:</strong>
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<li><strong>Accuracy:</strong> ~92%
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<li><strong>
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</ul>
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<h2>📦 How to Use</h2>
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pred = model.predict(img_array)
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classes = ['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash', 'biodegradable']
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print("Prediction:", classes[np.argmax(pred)])
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</code></pre>
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<h2>📁 Files</h2>
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<ul>
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<li><code>GarbageMLModel_CS549.h5</code> – Trained
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<li><code>label_map.json</code> –
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</ul>
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<h2>👤 Author</h2>
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</html>
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body { font-family: Arial, sans-serif; margin: 40px; line-height: 1.6; color: #333; }
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h1 { color: #2c3e50; }
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h2 { color: #34495e; }
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code { font-family: Consolas, monospace; }
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pre {
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background: #1e1e1e;
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color: #f8f8f2;
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padding: 16px;
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border-radius: 8px;
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overflow-x: auto;
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}
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ul { margin: 0; padding-left: 20px; }
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a { color: #2980b9; text-decoration: none; }
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a:hover { text-decoration: underline; }
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</style>
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</head>
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<body>
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</ul>
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<h2>🔍 Use Case</h2>
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<p>Helps automate waste sorting for better recycling. Great for demos, PoC apps, or smart bin integration.</p>
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<h2>🧠 Model Overview</h2>
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<ul>
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<li><strong>Architecture:</strong> CNN (Conv2D, MaxPooling, Dense)</li>
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<li><strong>Input:</strong> 224x224 RGB</li>
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<li><strong>Output:</strong> 7-class probability vector</li>
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<li><strong>Accuracy:</strong> ~92% (validation)</li>
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<li><strong>Explainability:</strong> Supports Grad-CAM</li>
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</ul>
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<h2>📦 How to Use</h2>
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pred = model.predict(img_array)
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classes = ['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash', 'biodegradable']
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print("Prediction:", classes[np.argmax(pred)])</code></pre>
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<h2>📁 Files</h2>
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<ul>
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<li><code>GarbageMLModel_CS549.h5</code> – Trained model</li>
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<li><code>label_map.json</code> – Label mapping</li>
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</ul>
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<h2>👤 Author</h2>
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</body>
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</html>
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