re-pixel 1.0.1

A powerful image compression library with multiple algorithms and formats support

Re-pixel 🎨

Re-pixel is a powerful and versatile Python library for image compression that supports multiple formats and algorithms. It provides both a simple Python API and a feature-rich command-line interface for compressing images while maintaining optimal quality.

✨ Features

• Multiple Format Support: JPEG, PNG, WebP
• Smart Compression: Automatic quality optimization for target file sizes
• Batch Processing: Compress entire directories with progress tracking
• Advanced Algorithms: Multiple compression techniques including lossless options
• CLI Interface: Easy-to-use command-line tool with rich output
• Flexible API: Simple Python API for integration into your projects
• Image Analysis: Detailed image information and compression statistics
• Resize & Compress: Automatic resizing with aspect ratio preservation

🚀 Installation

From PyPI (Recommended)

pip install re-pixel

From Source

git clone https://github.com/rakshithkalmadi/re-pixel.git
cd re-pixel
pip install -e .

Development Installation

git clone https://github.com/rakshithkalmadi/re-pixel.git
cd re-pixel
pip install -e ".[dev]"

📖 Quick Start

Python API

from repixel import ImageCompressor

# Initialize compressor
compressor = ImageCompressor()

# Compress a single image
result = compressor.compress(
    input_path="photo.jpg",
    output_path="photo_compressed.jpg",
    quality=80,
    format="jpeg"
)

print(f"Original size: {result['original_size_mb']:.2f} MB")
print(f"Compressed size: {result['compressed_size_mb']:.2f} MB")
print(f"Space saved: {result['space_saved_percent']:.1f}%")

# Batch compress all images in a directory
results = compressor.compress_batch(
    input_dir="photos/",
    output_dir="compressed_photos/",
    quality=85,
    format="webp",
    recursive=True
)

# Optimize quality for target file size
result = compressor.optimize_quality(
    input_path="large_photo.jpg",
    target_size_mb=2.0,
    format="jpeg"
)

Command-Line Interface

# Compress a single image
re-pixel compress photo.jpg -q 80 -f webp -o photo_compressed.webp

# Batch compress images in a directory
re-pixel batch photos/ -o compressed/ -q 85 -f webp --recursive

# Find optimal quality for target size
re-pixel optimize large_photo.jpg --target-size 2.0 -f jpeg -o optimized.jpg

# Get image information
re-pixel info photo.jpg

# List supported formats
re-pixel formats

🔧 Advanced Usage

Custom Compression Settings

from repixel import ImageCompressor

compressor = ImageCompressor()

# JPEG with progressive encoding
result = compressor.compress(
    input_path="photo.jpg",
    output_path="optimized.jpg",
    quality=90,
    format="jpeg",
    optimize=True,
    progressive=True
)

# WebP lossless compression
result = compressor.compress(
    input_path="graphic.png",
    output_path="graphic.webp",
    format="webp",
    lossless=True
)

# PNG with color reduction
result = compressor.compress(
    input_path="image.png",
    output_path="compressed.png",
    quality=70,  # Affects color palette reduction
    compress_level=9
)

Resize and Compress

from repixel.algorithms import AdvancedCompressor

# Resize to fit within bounds and compress
result = AdvancedCompressor.resize_and_compress(
    input_path="high_res.jpg",
    output_path="web_optimized.jpg",
    max_width=1920,
    max_height=1080,
    quality=85,
    format="jpeg"
)

Image Information

from repixel.utils import get_image_info, format_file_size

info = get_image_info("photo.jpg")
print(f"Dimensions: {info['dimensions']}")
print(f"File size: {format_file_size(info['size_bytes'])}")
print(f"Format: {info['format']}")
print(f"Megapixels: {info['megapixels']} MP")

🎛️ CLI Reference

Commands

• compress - Compress a single image
• batch - Compress multiple images in a directory
• optimize - Find optimal quality for target file size
• info - Display image information
• formats - List supported formats

Common Options

• -q, --quality - Compression quality (1-100)
• -f, --format - Output format (jpeg, png, webp)
• -o, --output - Output path
• --optimize - Enable optimization
• --progressive - Enable progressive JPEG
• --lossless - Use lossless compression (WebP)
• -v, --verbose - Verbose output

Examples

# High quality JPEG compression
re-pixel compress input.jpg -q 95 -f jpeg --progressive --optimize

# Batch convert to WebP with custom quality
re-pixel batch photos/ -o webp_photos/ -f webp -q 80 --recursive

# Optimize for web (target 500KB)
re-pixel optimize large.jpg --target-size 0.5 -f jpeg -o web_ready.jpg

# Get detailed image information
re-pixel info photo.jpg --verbose

📊 Format Comparison

Format	Best For	Compression	Transparency	Animation
JPEG	Photos, complex images	Lossy, high	❌	❌
PNG	Graphics, simple images	Lossless	✅	❌
WebP	Web images, modern browsers	Both	✅	✅

🎯 Quality Guidelines

• 95-100: Maximum quality, minimal compression
• 85-95: High quality, good for professional use
• 75-85: Good quality, recommended for web
• 65-75: Medium quality, smaller file sizes
• 50-65: Lower quality, significant compression
• Below 50: Poor quality, maximum compression

🛠️ Development

For comprehensive development instructions, including building, testing, and installation methods, see DEVELOPMENT.md.

Setup Development Environment

git clone https://github.com/rakshithkalmadi/re-pixel.git
cd re-pixel
pip install -e ".[dev]"

Run Tests

python -m pytest tests/ -v

Code Formatting

black repixel/
flake8 repixel/

Type Checking

mypy repixel/

📦 Building and Publishing

Build the Package

python -m build

Upload to PyPI

twine upload dist/*

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

Development Setup

For detailed development instructions, see DEVELOPMENT.md.

Quick start:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Set up development environment (pip install -e ".[dev]")
4. Run tests (python -m pytest tests/ -v)
5. Commit your changes (git commit -m 'Add amazing feature')
6. Push to the branch (git push origin feature/amazing-feature)
7. Open a Pull Request

📄 License

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

🙏 Acknowledgments

• Pillow for image processing capabilities
• OpenCV for advanced image algorithms
• Click for the CLI interface

📞 Support

If you encounter any issues or have questions:

• 🐛 Report bugs
• 💡 Request features
• 📧 Contact: [e-mail]

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Made with ❤️ by Rakshith Kalmadi