imgcolorshine 1.1.0

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imgcolorshine

Transform image colors using OKLCH color attractors - a physics-inspired tool that operates in perceptually uniform color space.

Overview

imgcolorshine applies a gravitational-inspired color transformation where specified "attractor" colors pull the image's colors toward them. The tool works in the OKLCH color space, ensuring perceptually uniform and natural-looking results.

Features

• Perceptually Uniform: Operations in OKLCH color space for intuitive results
• Flexible Color Input: Supports all CSS color formats (hex, rgb, hsl, oklch, named colors)
• Selective Channel Control: Transform lightness, saturation, and/or hue independently
• Multiple Attractors: Blend influences from multiple color targets
• High Performance: Optimized with NumPy and Numba for fast processing
• Memory Efficient: Automatic tiling for large images
• Professional Quality: CSS Color Module 4 compliant gamut mapping

Installation

# Install from PyPI
pip install imgcolorshine

# Or install from source
git clone https://github.com/twardoch/imgcolorshine.git
cd imgcolorshine
pip install -e .

Usage

Basic Example

Transform an image to be more red:

imgcolorshine shine photo.jpg "red;50;75"

Command Syntax

imgcolorshine shine INPUT_IMAGE ATTRACTOR1 [ATTRACTOR2 ...] [OPTIONS]

Each attractor has the format: "color;tolerance;strength"

• color: Any CSS color (e.g., "red", "#ff0000", "oklch(70% 0.2 120)")
• tolerance: 0-100 (radius of influence - how far the color reaches)
• strength: 0-100 (transformation intensity - how much colors are pulled)

Options

• --output_image PATH: Output image file (auto-generated if not specified)
• --luminance BOOL: Enable/disable lightness transformation (default: True)
• --saturation BOOL: Enable/disable chroma transformation (default: True)
• --hue BOOL: Enable/disable hue transformation (default: True)
• --verbose BOOL: Enable verbose logging (default: False)
• --tile_size INT: Tile size for large images (default: 1024)

Examples

Warm sunset effect:

imgcolorshine shine landscape.png \
  "oklch(80% 0.2 60);40;60" \
  "#ff6b35;30;80" \
  --output_image=sunset.png

Shift only hues toward green:

imgcolorshine shine portrait.jpg "green;60;90" \
  --luminance=False --saturation=False

Multiple color influences:

imgcolorshine shine photo.jpg \
  "oklch(70% 0.15 120);50;70" \
  "hsl(220 100% 50%);25;50" \
  "#ff00ff;30;40"

How It Works

1. Color Space: All operations happen in OKLCH space for perceptual uniformity
2. Attraction Model: Each attractor color exerts influence based on:
   • Distance: How similar a pixel's color is to the attractor
   • Tolerance: Maximum distance at which influence occurs
   • Strength: Maximum transformation amount
3. Falloff: Smooth raised-cosine curve for natural transitions
4. Blending: Multiple attractors blend using normalized weighted averaging
5. Gamut Mapping: Out-of-bounds colors are mapped back to displayable range

Understanding Parameters

Tolerance (0-100)

• Low values (0-20): Only very similar colors are affected
• Medium values (30-60): Moderate range of colors transformed
• High values (70-100): Wide range of colors influenced

Strength (0-100)

• Low values (0-30): Subtle color shifts
• Medium values (40-70): Noticeable but natural transformations
• High values (80-100): Strong color replacement

Performance

• Processes a 1920×1080 image in ~2-5 seconds
• Automatic tiling for images larger than 2GB memory usage
• GPU acceleration available with CuPy (10-100x speedup)

Technical Details

• Color Engine: ColorAide for accurate OKLCH operations
• Image I/O: OpenCV (4x faster than PIL for PNG)
• Computation: NumPy + Numba JIT compilation
• Gamut Mapping: CSS Color Module 4 algorithm
• Falloff Function: Raised cosine for smooth transitions

Development

This project follows a structured approach focusing on code quality, documentation, and maintainable development practices.

License

MIT License - see LICENSE file for details.

Credits

• Created by Adam Twardoch
• Developed with Antropic software