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Update README.md with complete project structure
- Added Descriptions/ folder with 10 technique guides - Added docs/ folder with documentation files - Added tests/ folder with unit tests - Added new configuration files (.pre-commit-config.yaml, pytest.ini) - Updated features section with technique descriptions and default sample image - Enhanced usage guide with new workflow including technique descriptions - Corrected sample images path to sampleImg.jpeg
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README.md

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### Additional Features
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- **Technique Descriptions** - Built-in educational guides for each analysis method
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- **Default Sample Image** - Preloaded image for instant testing without upload
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- **Web-based Interface** - No installation required, runs in browser
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- **Dark Theme** - Professional forensic UI with neon accents
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- **12 Analysis Tabs** - Organized, intuitive workflow
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- **Human-Readable Results** - Authenticity scoring (0-100) and risk levels
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- **Real-time Processing** - Instant visual feedback
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- **Cloud Deployment Ready** - Deploy to Streamlit Cloud in minutes
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VeritasForensics/
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├── app.py # Main Streamlit application
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├── requirements.txt # Python dependencies
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├── requirements-dev.txt # Development dependencies
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├── projectSetup.md # Detailed setup guide
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├── README.md # This file
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├── CHANGELOG.md # Version history
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├── CONTRIBUTING.md # Contribution guidelines
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├── LICENSE # BSD 3-Clause License
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├── pytest.ini # Test configuration
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├── .gitignore # Git ignore rules
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├── .pre-commit-config.yaml # Pre-commit hooks
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├── TECHNIQUE_DESCRIPTIONS_USER_GUIDE.md # User guide for descriptions
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├── analysis/ # Forensic analysis modules
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│ ├── __init__.py
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│ ├── resampling_detector.py # Resampling detection
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│ └── util.py # Helper functions
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├── Descriptions/ # Technique education module (NEW)
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│ ├── ELA.md # ELA guide
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│ ├── Metadata.md # Metadata guide
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│ ├── Histogram.md # Histogram guide
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│ ├── Noise_Ghost.md # Noise/Ghost guide
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│ ├── Quantization.md # Quantization guide
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│ ├── CMFD.md # CMFD guide
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│ ├── PRNU.md # PRNU guide
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│ ├── Frequency.md # FFT/DCT guide
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│ ├── Deepfake.md # Deepfake guide
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│ └── Resampling.md # Resampling guide
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├── docs/ # Documentation
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│ ├── API.md # API documentation
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│ ├── DEPLOYMENT.md # Deployment guide
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│ ├── PROJECT_SUMMARY.md # Project overview
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│ └── TECHNIQUES.md # Techniques reference
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├── tests/ # Unit tests
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│ ├── __init__.py
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│ ├── test_ela.py # ELA tests
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│ ├── test_metadata.py # Metadata tests
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│ └── test_integration.py # Integration tests
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├── assets/ # Static files
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│ ├── style.css # Custom CSS
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│ └── sample_images/ # Test images
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│ └── sample images/ # Sample test images
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│ └── sampleImg.jpeg # Default sample image
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├── .streamlit/ # Streamlit config
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│ └── config.toml # Theme & server settings
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### Basic Workflow
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1. **Upload Image**: Click "Choose an Image" in the sidebar
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2. **Select Technique**: Navigate to the analysis tab you want to use
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3. **Configure Parameters**: Adjust sliders/options as needed
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4. **Run Analysis**: Click the analysis button
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5. **Review Results**: View visualizations and metrics
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1. **View Sample Image**: App loads with default sample image automatically
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2. **Upload Your Image** (Optional): Click "Choose an Image" in sidebar to analyze your own
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3. **Learn About Techniques**: Click technique description buttons in sidebar for guidance
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4. **Select Analysis Tab**: Navigate to the technique you want to use
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5. **Configure Parameters**: Adjust sliders/options as needed
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6. **Run Analysis**: Click the analysis button
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7. **Review Results**: View visualizations, authenticity scores, and interpretations
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### Technique Descriptions (NEW)
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Access built-in educational guides via sidebar buttons:
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- **📚 Technique Descriptions Section** - Click any technique to learn
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- **Non-technical explanations** - Understand what each tool does
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- **Interpretation guides** - Learn to read results (normal vs. suspicious)
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- **Real-world examples** - See practical use cases
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- **Limitations explained** - Understand reliability and caveats
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### Analysis Techniques Explained
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