🖼️ Image Processing Application

A cloud-based Django application for processing images with various filters and storing them in AWS S3.

✨ Features

• 6 Image Filters: Grayscale, Sepia, Poster, Blur, Edge Detection, Solar
• Drag & Drop Upload: Easy image upload interface
• AWS S3 Integration: Automatic cloud storage
• Responsive Design: Works on desktop and mobile
• Docker Support: Easy deployment with Docker
• Gallery View: Browse all processed images

🚀 Quick Start

Option 1: Automated Setup (Recommended)

git clone https://github.com/pneman1/CloudImage.git
cd CloudImage
chmod +x setup.sh
./setup.sh
source venv/bin/activate
python manage.py runserver

Option 2: Manual Setup

1. Clone the repository

   git clone https://github.com/pneman1/CloudImage.git
   cd CloudImage

2. Create virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Run migrations

   python manage.py migrate

5. Start development server

   python manage.py runserver

6. Access the application

   • Main app: http://localhost:8000
   • Upload images: http://localhost:8000/images/upload/
   • Gallery: http://localhost:8000/images/gallery/

Docker Deployment

1. Build and run with Docker Compose

   docker-compose up -d

2. Access the application

   • Main app: http://localhost:8000
   • Nginx proxy: http://localhost:80

🔧 Configuration

Environment Variables

Create a .env file with the following variables:

# Django Settings
SECRET_KEY=your-secret-key-here
DEBUG=True
ALLOWED_HOSTS=localhost,127.0.0.1

# Database (for production)
DATABASE_URL=postgresql://user:password@localhost:5432/image_processing

# AWS S3 Configuration
AWS_ACCESS_KEY_ID=your-aws-access-key
AWS_SECRET_ACCESS_KEY=your-aws-secret-key
AWS_STORAGE_BUCKET_NAME=your-s3-bucket-name
AWS_S3_REGION_NAME=us-east-1

AWS S3 Setup

1. Create S3 bucket

   ./setup-s3.sh

2. Or configure manually

   aws configure

3. Test S3 integration

   • Upload an image through the web interface
   • Check your S3 bucket for the processed image

📁 Project Structure

ImageProcessing/
├── apps/                    # Django applications
│   ├── core/               # Core functionality
│   ├── images/             # Image processing
│   ├── storage/            # S3 storage utilities
│   └── common/             # Shared utilities
├── config/                 # Django configuration
├── templates/              # HTML templates
├── static/                # Static files (CSS, JS)
├── media/                  # Media files
├── deployment/             # Deployment configurations
├── requirements.txt        # Python dependencies
├── Dockerfile             # Docker configuration
├── docker-compose.yml     # Docker Compose setup
└── manage.py              # Django management script

🎨 Image Filters

The application supports 6 different image filters:

1. Grayscale - Convert to black and white
2. Sepia - Vintage brown tone effect
3. Poster - Reduce colors for poster effect
4. Blur - Gaussian blur effect
5. Edge Detection - Highlight edges
6. Solar - Invert colors for solar effect

🚀 Deployment

Local Docker Deployment

# Build and start services
docker-compose up -d

# View logs
docker-compose logs -f

# Stop services
docker-compose down

Production Deployment

1. Configure environment variables

   cp production.env.example .env
   # Edit .env with your production values

2. Deploy with production configuration

   docker-compose -f docker-compose.prod.yml up -d

3. Set up SSL (optional)

   • Configure Nginx with SSL certificates
   • Update security settings in Django

🔧 Development

Running Tests

python manage.py test

Database Management

# Create migrations
python manage.py makemigrations

# Apply migrations
python manage.py migrate

# Create superuser
python manage.py createsuperuser

Static Files

# Collect static files
python manage.py collectstatic

📊 Monitoring

Logs

• Django logs: Check console output
• Docker logs: docker-compose logs -f
• Nginx logs: docker-compose logs nginx

Performance

• Image processing: Optimized with NumPy
• S3 uploads: Asynchronous processing
• Caching: Redis for session storage

🛠️ Troubleshooting

Common Issues

1. "ModuleNotFoundError"

   • Ensure virtual environment is activated
   • Install dependencies: pip install -r requirements.txt

2. "Database connection failed"

   • Check database configuration
   • Run migrations: python manage.py migrate

3. "S3 upload failed"

   • Verify AWS credentials
   • Check S3 bucket permissions
   • Ensure bucket exists

4. "Static files not found"

   • Run: python manage.py collectstatic
   • Check STATIC_ROOT setting

Debug Mode

Enable debug mode for development:

# In config/settings.py
DEBUG = True

📝 API Endpoints

• GET / - Home page
• GET /images/upload/ - Upload form
• POST /images/upload/ - Process image
• GET /images/result/<id>/ - View processed image
• GET /images/gallery/ - Browse all images
• GET /images/download/<id>/ - Download image

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Django framework
• Pillow for image processing
• Bootstrap for UI components
• AWS S3 for cloud storage
• Docker for containerization

📞 Support

For issues and questions:

• Create an issue on GitHub
• Check the troubleshooting section
• Review the deployment guide

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Built with ❤️ using Django, AWS S3, and Docker