# Contributing to NAFNet Image Restoration API First off, thank you for considering contributing to NAFNet! It's people like you that make NAFNet such a great project. ## Code of Conduct This project and everyone participating in it is governed by our [Code of Conduct](CODE_OF_CONDUCT.md). By participating, you are expected to uphold this code. --- ## How Can I Contribute? ### Reporting Bugs Before creating bug reports, please check the issue list as you might find out that you don't need to create one. When you are creating a bug report, please include as many details as possible: **Description of the bug** - What you were doing when the bug occurred - Steps to reproduce the problem - Expected behavior - Actual behavior - Relevant logs or error messages **System information** - OS (Linux, macOS, Windows) - Python version - Browser (if related to web interface) - Flask version ### Suggesting Enhancements Enhancement suggestions are tracked as GitHub issues. When creating an enhancement suggestion, please include: - Use case for the enhancement - Why you think this enhancement is useful - Examples of how this enhancement could be implemented ### Pull Requests **Before starting work:** 1. Fork the repository 2. Create a new branch for your feature 3. Make sure your code follows PEP 8 4. Write tests for new features 5. Update documentation **Process:** ```bash # 1. Fork and clone git clone https://github.com/YOUR-USERNAME/NAFNet-Image-Restoration-API.git cd NAFNet-Image-Restoration-API # 2. Create feature branch git checkout -b feature/your-feature-name # 3. Make changes # ... edit files ... # 4. Test your changes python app.py # Test in browser: http://localhost:5000 # 5. Commit changes git add . git commit -m "Add feature: description of your feature" # 6. Push to your fork git push origin feature/your-feature-name # 7. Open Pull Request on GitHub ``` --- ## Development Setup ### Prerequisites - Python 3.8+ - Git - Virtual environment ### Initial Setup ```bash # Clone repository git clone https://github.com/Gtajisan/NAFNet-Image-Restoration-API.git cd NAFNet-Image-Restoration-API # Create virtual environment python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate # Install dependencies pip install -r requirements.txt # Install development tools pip install pytest pytest-cov black flake8 isort ``` ### Running the Application ```bash python app.py ``` Access at `http://localhost:5000` --- ## Code Style ### PEP 8 Compliance This project follows [PEP 8](https://www.python.org/dev/peps/pep-0008/) guidelines. **Check code style:** ```bash flake8 app.py ``` **Auto-format code:** ```bash black app.py isort app.py ``` ### Naming Conventions - **Functions/Variables**: `snake_case` - **Classes**: `PascalCase` - **Constants**: `UPPER_SNAKE_CASE` - **Modules**: `snake_case` ### Docstring Format ```python def enhance_image(input_file): """ Restore and enhance image using image processing techniques. Applies a series of transformations to improve image quality: - Median filtering for denoising - Gaussian blur for smoothing - Contrast, sharpness, and color enhancement Args: input_file (file-like): Image file object or path Returns: PIL.Image: Enhanced image in RGB format Raises: IOError: If file cannot be opened ValueError: If image format is not supported Example: >>> from PIL import Image >>> img = Image.open('input.jpg') >>> restored = enhance_image(img) >>> restored.save('output.png') """ pass ``` ### Comments - Use comments for WHY, not WHAT - Keep comments concise and clear - Update comments when code changes ```python # Good # Median filter preserves edges while removing noise denoised[:,:,i] = ndimage.median_filter(img_np[:,:,i], size=3) # Avoid # Apply median filter denoised[:,:,i] = ndimage.median_filter(img_np[:,:,i], size=3) ``` --- ## Testing ### Running Tests ```bash # Run all tests pytest # Run with coverage pytest --cov=nafnet --cov-report=html # Run specific test file pytest tests/test_api.py # Run with verbose output pytest -v ``` ### Writing Tests ```python # tests/test_api.py import pytest from app import app @pytest.fixture def client(): """Create test client.""" app.config['TESTING'] = True return app.test_client() def test_api_info(client): """Test API info endpoint returns correct data.""" response = client.get('/api/info') assert response.status_code == 200 assert 'name' in response.json assert 'version' in response.json def test_image_upload(client): """Test image upload and processing.""" # Create test image from PIL import Image img = Image.new('RGB', (100, 100), color='red') img.save('/tmp/test.jpg') with open('/tmp/test.jpg', 'rb') as f: response = client.post('/api/fix', data={'file': f}) assert response.status_code == 200 assert response.content_type == 'image/png' ``` --- ## Commit Guidelines ### Commit Message Format ``` ():