🎨 Moggu - Ultra-Fast Image Processing Tool

A lightning-fast, terminal-based image processing application built in Rust that delivers professional-grade filters in under 200ms, even for large images.

⚡ Key Features

🚀 Blazing Fast Performance

• Sub-200ms processing for most operations, even on heavy files (10MB+)
• Multi-threaded processing with optimized algorithms
• Memory-efficient operations using Rust's zero-cost abstractions
• Real-time progress tracking

🎯 21+ Professional Filters

• Basic Filters: Grayscale conversion
• Color Manipulation: Brightness, contrast, saturation, hue rotation, inversion, sepia
• Blur & Sharpening: Gaussian blur, box blur, sharpen, edge detection
• Artistic Effects: Oil painting, vignette, noise, thresholding
• Geometric Operations: Rotation (90°/180°/270°), horizontal/vertical flip, crop

💻 Intuitive Terminal UI

• Beautiful, responsive interface with color-coded categories
• Built-in file browser with async file dialogs
• Smart parameter validation with range checking
• Interactive help system with keyboard shortcuts
• Category filtering for easy navigation

🖼️ Advanced Image Preview

• Inline image display directly in terminal
• Support for chafa and viu rendering engines
• Preview processed images without leaving the application
• Terminal-friendly image viewing

🛠️ Installation

From crates.io (Recommended)

cargo install moggu

From Source

git clone https://github.com/yourusername/moggu
cd moggu
cargo install --path .

Prerequisites

# Install Rust
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
source $HOME/.cargo/env

Image Preview Dependencies (Recommended)

For the best image preview experience, install chafa:

Linux

# Arch Linux / Manjaro
sudo pacman -S chafa

# Ubuntu / Debian
sudo apt update && sudo apt install chafa

# Fedora / RHEL / CentOS
sudo dnf install chafa
# or for older versions:
sudo yum install chafa

# openSUSE
sudo zypper install chafa

# Alpine Linux
sudo apk add chafa

# Gentoo
sudo emerge media-gfx/chafa

# NixOS
nix-env -iA nixpkgs.chafa
# or add to configuration.nix:
# environment.systemPackages = [ pkgs.chafa ];

macOS

# Homebrew (recommended)
brew install chafa

# MacPorts
sudo port install chafa

# Nix (if using Nix on macOS)
nix-env -iA nixpkgs.chafa

Windows

# Windows Subsystem for Linux (WSL) - Ubuntu
sudo apt update && sudo apt install chafa

# Chocolatey (if available)
choco install chafa

# Scoop (if available)
scoop install chafa

# MSYS2
pacman -S mingw-w64-x86_64-chafa

# Manual Installation:
# 1. Download from: https://github.com/hpjansson/chafa/releases
# 2. Extract to a directory in your PATH
# 3. Or use Windows Terminal with WSL for best experience

Alternative: Cross-platform Rust-based image viewer

# If chafa is not available, install viu (pure Rust)
cargo install viu

# Or sixel-image (for terminals with sixel support)
cargo install sixel-image

Terminal Compatibility Check:

# Test if your terminal supports chafa
echo "Testing chafa..." && chafa --version

# Test image display (replace with any image file)
chafa your-image.jpg

# Test viu if installed
viu your-image.jpg

Note: For Windows users, we highly recommend using Windows Terminal with WSL2 for the best experience, as native Windows terminals have limited image display capabilities.

🎮 Usage

Quick Start

1. Launch: cargo run
2. Select Files: Use built-in browser (f for input, o for output) or type paths
3. Choose Filter: Navigate with ↑/↓ or j/k, cycle categories with c
4. Set Parameters: Enter values or use defaults
5. Process: Automatic processing with real-time progress
6. Preview: Press v to view results inline

Keyboard Controls

Global

• q - Quit application
• h - Toggle help
• Esc - Go back
• r - Reset to start

File Input

• f - Open file browser (input)
• o - Open file browser (output)
• Tab/Enter - Next field

Filter Selection

• ↑/↓ or j/k - Navigate filters
• c - Cycle categories
• Enter - Select filter

Parameter Input

• Tab/Enter - Next parameter
• ↑ - Previous parameter
• Backspace - Delete

Results

• v - View processed image
• c - Clear displayed images
• r - Process another image

🎨 Filter Categories

🔵 Basic (1 filter)

• Grayscale: Convert to grayscale

🟣 Color (4 filters)

• Saturate: Adjust color saturation (0.0-3.0)
• Invert: Invert all colors
• Hue Rotate: Shift hue spectrum (-360° to 360°)
• Sepia: Apply warm sepia tone

🟦 Enhancement (7 filters)

• Brightness: Adjust luminosity (-100 to 100)
• Contrast: Modify contrast (0.1-3.0)
• Gaussian Blur: Smooth blur (0.1-20.0 sigma)
• Box Blur: Fast blur (1-50 radius)
• Sharpen: Enhance details (0.1-3.0)
• Edge Detection: Sobel edge detection
• Thresholding: Binary threshold (0-255)

🟪 Artistic (4 filters)

• Vignette: Dark edge effect (0.1-1.0)
• Noise: Add random noise (1-100)
• Oil Painting: Artistic oil effect (radius 1-10, levels 5-50)

🟨 Geometric (6 filters)

• Rotate: 90°, 180°, 270° rotation
• Flip: Horizontal/vertical mirroring
• Crop: Custom rectangle cropping

🟩 Utility (1 filter)

• Advanced cropping with position control

🔧 Technical Details

Architecture

• Language: Rust 2024 Edition
• UI Framework: Ratatui with Crossterm
• Image Processing: Custom algorithms + image crate
• Async Runtime: Tokio for file operations
• Concurrency: Multi-threaded processing

Optimization Features

• SIMD Instructions: Vectorized operations
• Memory Pooling: Reduced allocations
• Lazy Loading: On-demand processing
• Pipeline Architecture: Streaming transforms
• Zero-Copy Operations: Direct memory access

Supported Formats

• Input: PNG, JPEG, BMP, TIFF, GIF
• Output: PNG, JPEG, BMP, TIFF

🖥️ Terminal Compatibility

Recommended Terminals

• Kitty (Best image preview support)
• iTerm2 (macOS)
• Alacritty
• GNOME Terminal
• Windows Terminal

Image Preview Support

• chafa (Recommended) - Rich color display
• viu - Fast Unicode display
• Fallback - File path display

🤝 Contributing

1. Fork the repository
2. Create feature branch: git checkout -b feature-name
3. Commit changes: git commit -am 'Add feature'
4. Push branch: git push origin feature-name
5. Submit pull request

📝 License

MIT License - see LICENSE for details.

**⚡ Built for speed. Designed for productivity. Perfect for