🚁 UAV Image Analysis System

A comprehensive Streamlit web application for processing and analyzing UAV-captured aerial imagery. This system provides advanced image processing capabilities for agriculture, forestry, and environmental monitoring.

🌟 Features

🖼️ Image Stitching

• Combine multiple aerial images into seamless panoramas
• Automatic image alignment and blending
• Post-processing for optimal results

🌳 Tree Counting

• Automatic detection and counting of trees in aerial imagery
• Adjustable parameters for different tree sizes
• Visual highlighting of detected trees

📍 Area Detection

• Identify and map crop areas and vegetation zones
• Contour detection and bounding box calculation
• Area quantification and mapping

🦠 Disease Detection

• Detect plant diseases and health issues
• Adjustable color range detection
• Morphological processing for accurate detection

📊 Object Counting

• Count various objects and features in images
• Green object detection and filtering
• Customizable area thresholds

📈 Results Dashboard

• Comprehensive analysis and reporting
• Processed image gallery
• Download functionality for results

🚀 Installation

1. Clone or download the project

   # If using git
   git clone <repository-url>
   cd "Project UAV"

2. Install Python dependencies

   pip install -r requirements.txt

3. Run the Streamlit application

   streamlit run app.py

4. Open your browser

   • The application will automatically open in your default browser
   • Default URL: http://localhost:8501

📋 Requirements

• Python 3.8 or higher
• OpenCV 4.8.0 or higher
• Streamlit 1.28.0 or higher
• Other dependencies listed in requirements.txt

🎯 Usage Guide

Getting Started

1. Open the application in your browser
2. Navigate through the sidebar to access different features
3. Upload images using the file uploaders
4. Adjust parameters using the interactive sliders
5. View results and download processed images

Image Stitching

1. Go to "🖼️ Image Stitching" page
2. Upload multiple images (at least 2)
3. Click "🔄 Process Image Stitching"
4. View the stitched panorama
5. Save the result if needed

Tree Counting

1. Go to "🌳 Tree Counting" page
2. Upload a single image
3. Adjust the "Minimum tree area" slider
4. Click "🌳 Count Trees"
5. View detected trees and count

Area Detection

1. Go to "📍 Area Detection" page
2. Upload an image
3. Click "📍 Detect Areas"
4. View detected areas and bounding boxes

Disease Detection

1. Go to "🦠 Disease Detection" page
2. Upload an image
3. Adjust HSV color range sliders
4. Set minimum and maximum disease area
5. Click "🦠 Detect Diseases"
6. View detected disease areas

Object Counting

1. Go to "📊 Object Counting" page
2. Upload an image
3. Adjust minimum object area threshold
4. Click "📊 Count Objects"
5. View detected objects and count

📁 Project Structure

Project UAV/
├── app.py                 # Main Streamlit application
├── requirements.txt       # Python dependencies
├── README.md             # This file
├── processed/            # Output directory for processed images
├── area_detection/       # Area detection backend code
├── count_trees/          # Tree counting backend code
├── Count_new/            # Object counting backend code
├── Image Stitching/      # Image stitching backend code
└── images_nadir_RGB/     # Sample UAV images

🔧 Customization

Adjusting Parameters

• Tree Counting: Modify the minimum area threshold for different tree sizes
• Disease Detection: Adjust HSV color ranges for different disease types
• Object Counting: Change area thresholds for different object sizes
• Image Stitching: The algorithm automatically handles multiple images

Adding New Features

The modular structure allows easy addition of new image processing features:

1. Add new processing functions
2. Create new Streamlit pages
3. Update the sidebar navigation
4. Add new file uploaders and controls

🐛 Troubleshooting

Common Issues

1. OpenCV Installation Issues

   pip uninstall opencv-python
   pip install opencv-python-headless

2. Streamlit Not Starting

   • Ensure all dependencies are installed
   • Check Python version compatibility
   • Verify file paths are correct

3. Image Processing Errors

   • Ensure uploaded images are in supported formats (JPG, PNG)
   • Check image file sizes (very large images may cause memory issues)
   • Verify images are not corrupted

4. Memory Issues

   • Process smaller images
   • Close other applications to free memory
   • Restart the Streamlit application

📊 Performance Tips

• Use appropriately sized images for faster processing
• Adjust parameters based on your specific use case
• Process images in batches for large datasets
• Monitor system resources during processing

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

📄 License

This project is open source and available under the MIT License.

🆘 Support

For issues and questions:

1. Check the troubleshooting section
2. Review the code comments
3. Open an issue in the repository
4. Contact the development team

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🚁 UAV Image Analysis System - Advanced aerial image processing for agriculture, forestry, and environmental monitoring.