ASCII Art Converter

   _____    __________________ .___.___     _____          __    
  /  _  \  /   _____/\_   ___ \|   |   |   /  _  \________/  |_  
 /  /_\  \ \_____  \ /    \  \/|   |   |  /  /_\  \_  __ \   __\ 
/    |    \/        \\     \___|   |   | /    |    \  | \/|  |   
\____|__  /_______  / \______  /___|___| \____|__  /__|   |__|   
        \/        \/         \/                  \/              
_________                                   __                   
\_   ___ \  ____   _______  __ ____________/  |_  ___________    
/    \  \/ /  _ \ /    \  \/ // __ \_  __ \   __\/ __ \_  __ \   
\     \___(  <_> )   |  \   /\  ___/|  | \/|  | \  ___/|  | \/   
 \______  /\____/|___|  /\_/  \___  >__|   |__|  \___  >__|      
        \/            \/          \/                 \/         

A powerful and flexible Python library and command-line tool for converting images to ASCII art, Braille art, and edge detection art with support for color, dithering, and various customization options.

⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠿⠛⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠏⠈⠀⡿⢻⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡿⢿⠛⠀⠀⢰⠁⠸⠿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⠀⠀⠀⠀⠀⢀⡞⠈⢿⣿⣧⠉⣿⣿⣿⡿⠛⣻⣿⣿⣿⡟⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⢿⠀⠀⠀⠀⢀⡍⠀⠀⠀⢿⡟⢾⣿⣿⣿⢇⣾⣿⣿⠿⣿⣿⣿⣿⣿⣿⡟⠻⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣧⡛⠀⠀⠀⠀⠛⠀⠀⠀⠀⠘⠀⢸⣿⣿⢃⣸⣿⣿⣿⣦⣌⢿⣿⣿⢻⣿⣷⢀⣾⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠿⠿⠿⣿⣿⣿⡿⠀⠈⠙⣿⠂⠀⠀⠀⠀⠀⣾⣿⠇⡼⢹⣿⣿⣿⣿⣿⡟⣿⣿⡀⠻⠇⣾⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⡿⠟⠋⠉⠀⠀⠀⠀⠀⠻⣛⡉⢀⣤⢆⡀⡀⢾⣿⣷⣦⠄⣸⣿⣿⠀⠃⠀⠹⢿⣿⣿⠋⠀⣿⣿⡆⢀⣶⡌⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣛⣁⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠉⢸⣿⣿⢏⡴⠋⠀⠀⠉⠋⣰⣿⣿⡟⣰⣶⣦⣄⠀⢠⣴⣦⣄⣿⣿⣇⠘⠛⠉⠙⠻⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣦⡀⠀⠀⠀⠀⠀⠀⠀⠨⠛⠁⠊⠂⣴⣊⡤⣴⢂⣿⣿⣿⡇⠙⠿⠟⠛⡁⠈⠉⠉⢹⣿⣿⡇⠰⠁⠀⠀⠀⠀⠙⢿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣧⠀⠀⢀⣀⡀⠀⠀⠀⠀⠀⠀⠈⣿⣿⡇⢷⠘⣿⣿⠿⠁⠒⠿⢿⡿⠿⠟⠂⠀⢾⣿⣿⠇⠀⠀⠀⠀⠀⠀⠀⠀⠙⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣶⣾⣿⣿⣿⣿⣦⣀⣤⠖⠒⠀⠈⠛⠁⠀⠓⢦⠅⣀⣐⠚⠁⠀⠀⠲⠀⠀⠀⠢⡈⠡⠒⠀⠀⢀⣠⣤⣶⣶⣦⣤⣌⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠿⣋⣤⡴⠒⠀⣀⣤⣤⡄⢀⣴⣾⣿⣿⣿⠁⠀⣴⣾⣷⡀⢀⠂⢠⣤⣤⣤⣶⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡿⢋⣴⣷⣿⠟⣿⠛⢀⠞⣵⣿⣿⣿⠃⡀⢀⢿⣿⣿⣿⡾⠟⣷⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣷⣿⣿⡏⣠⣤⡉⠦⢀⣼⣿⣿⣿⠃⠈⡀⡘⠈⣿⣿⣿⣿⣠⣽⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡟⠏⠘⣿⡿⠀⣸⣼⣿⣿⣿⠃⢀⣬⠻⢻⣦⡘⣿⣿⣿⡇⠻⡹⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠋⢀⡼⠋⣼⣿⣿⣿⣿⣿⣿⠇⣾⣿⣿⣿⣶⣷⢻⣿⣿⣿⢸⢀⠋⣹⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡟⠛⢿⣿⣿⣿⣿⡧⠈⠳⢁⣿⡟⣿⣿⣿⣯⣿⣿⣿⣿⣿⣿⣿⣿⠀⢿⣿⣿⠈⠛⠁⢿⠟⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡧⠈⢿⣟⠛⡛⠈⣡⣼⣦⠌⣿⢁⣿⣿⡏⣸⣿⣿⣿⣿⣿⣿⣿⠃⠀⠘⢛⣻⡇⠳⣄⠀⢠⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡔⠃⠀⠈⠉⣥⣶⠛⠿⠋⠀⠁⠾⡿⠟⠃⠁⠀⠈⠙⠛⠛⠋⠀⠀⠀⠀⠾⡿⠋⠀⠈⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣄⢰⣶⡄⠻⠇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡀⠀⠀⠀⠀⣀⠀⡀⠀⠀⠀⠀⠀⠀⢠⣶⣾⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣭⣅⣠⣶⣦⣶⣤⠀⠤⠄⠀⠀⠀⢠⣤⣷⣶⣾⣶⣾⣿⡆⠠⠀⠀⠀⠐⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣟⣛⣛⡀⠀⠀⠀⣀⣀⣈⣛⣛⣉⣯⣭⣉⣉⣁⣀⣀⣀⣀⣀⣀⣩⣭⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿

Features

• Multiple Rendering Modes:

  • Density-based ASCII art
  • Braille pattern art
  • Edge detection art

• Color Support:

  • 24-bit true color
  • 256-color palette
  • 16-color palette
  • Various color sampling methods (center, average, dominant)

• Customization Options:

  • Adjustable character aspect ratio
  • Multiple character sets (standard, detailed, blocks, simple, etc.)
  • Custom character sets
  • Brightness, contrast, gamma, and sharpness adjustments
  • Dithering support (Floyd-Steinberg, ordered, Atkinson)

• Interactive Mode:

  • Real-time preview and adjustment
  • Live parameter tweaking
  • Convenient saving options

• Batch Processing:

  • Process multiple images at once
  • Consistent configuration across images

• Output Formats:

  • Plain text
  • HTML with styling
  • ANSI color codes for terminals

Installation

Prerequisites

• Python 3.7+
• Pillow (PIL fork) for image processing
• NumPy for numerical operations

Installation Steps

1. Clone the repository:

git clone https://github.com/our0boros/ascii-art-converter.git
cd ascii-art-converter

2. Install dependencies:

pip install -r requirements.txt

Quick Start

Basic Conversion

python -m ascii_art_converter.cli image.png

Set Output Width

python -m ascii_art_converter.cli image.png -w 80

Use Braille Mode

python -m ascii_art_converter.cli image.png -m braille

Edge Detection

python -m ascii_art_converter.cli image.png -m edge -t 0.2

Colored HTML Output

python -m ascii_art_converter.cli image.png -c -o output.html

256-Color Terminal Output

python -m ascii_art_converter.cli image.png --colorize --color-mode 256

Command-Line Interface

Usage

python -m ascii_art_converter.cli [-h] [-o OUTPUT] [-w WIDTH] [-H HEIGHT] [--max-width MAX_WIDTH]
                                  [--min-width MIN_WIDTH] [--char-ratio CHAR_RATIO] [-m {density,braille,edge}]
                                  [--charset CHARSET] [--custom-charset CUSTOM_CHARSET] [-i] [-t THRESHOLD]
                                  [--edge-detector {sobel,prewitt,laplacian,canny,scharr}] [--edge-sigma EDGE_SIGMA]
                                  [--edge-charset EDGE_CHARSET] [--braille-threshold BRAILLE_THRESHOLD]
                                  [--dither {none,floyd_steinberg,ordered,atkinson}] [-c] [--color-mode {24bit,256,16}]
                                  [--color-sample {center,average,dominant}] [--contrast CONTRAST]
                                  [--brightness BRIGHTNESS] [--gamma GAMMA] [--sharpness SHARPNESS]
                                  [--complexity-factor COMPLEXITY_FACTOR] [--demo] [-a] [-v]
                                  [input]

Positional Arguments

input                 Input image file

Optional Arguments

-h, --help            show this help message and exit
-o OUTPUT, --output OUTPUT
                      Output file (txt, html, or ansi)
-w WIDTH, --width WIDTH
                      Output width in characters
-H HEIGHT, --height HEIGHT
                      Output height in characters
--max-width MAX_WIDTH
                      Maximum auto width
--min-width MIN_WIDTH
                      Minimum auto width
--char-ratio CHAR_RATIO
                      Character aspect ratio (width/height)
-m {density,braille,edge}, --mode {density,braille,edge}
                      Rendering mode
--charset CHARSET     Character set: standard, detailed, blocks, simple, binary, dots, geometric
--custom-charset CUSTOM_CHARSET
                      Custom character string (dark to light)
-i, --invert          Invert brightness
-t THRESHOLD, --threshold THRESHOLD
                      Edge detection threshold (0-1)
--edge-detector {sobel,prewitt,laplacian,canny,scharr}
                      Edge detection algorithm
--edge-sigma EDGE_SIGMA
                      Gaussian blur sigma for edge detection
--edge-charset EDGE_CHARSET
                      Character set for edge mode
--braille-threshold BRAILLE_THRESHOLD
                      Threshold for braille dots (0-1)
--dither {none,floyd_steinberg,ordered,atkinson}
                      Dithering method for braille
-c, --colorize        Enable color output
--color-mode {24bit,256,16}
                      Terminal color mode
--color-sample {center,average,dominant}
                      Color sampling method
--contrast CONTRAST   Contrast adjustment (0.5-2.0)
--brightness BRIGHTNESS
                      Brightness adjustment (0.5-2.0)
--gamma GAMMA         Gamma correction
--sharpness SHARPNESS
                      Sharpness enhancement
--complexity-factor COMPLEXITY_FACTOR
                      Multiplier for auto-size complexity calculation
--demo                Run demo
-a, --analyze         Show analysis of the generated ASCII art
-v, --verbose         Verbose output

Interactive Mode

The converter includes an interactive mode for real-time preview and adjustment of parameters:

python -m ascii_art_converter.interactive image.png

Interactive Commands

Commands:
  w <num>     - Set width
  m <mode>    - Set mode (density/braille/edge)
  c <charset> - Set charset
  i           - Toggle invert
  color       - Toggle color
  t <num>     - Set threshold (edge mode)
  contrast <num> - Set contrast
  render      - Render current settings
  save <file> - Save to file
  q           - Quit

Configuration Options

Character Sets

The converter provides several built-in character sets:

• standard: Standard density-based character set
• detailed: More detailed character set for higher resolution
• blocks: Block characters for bold, contrasting art
• simple: Simplified character set for minimalistic art
• binary: Only two characters (0 and 1) for binary art
• dots: Dot-based characters
• geometric: Geometric shapes

Edge Detectors

Available edge detection algorithms:

• Sobel (default)
• Prewitt
• Laplacian
• Canny
• Scharr

Dithering Methods

Dithering options for Braille mode:

• None (default)
• Floyd-Steinberg
• Ordered
• Atkinson

Advanced Usage

Custom Character Set

Create custom ASCII art using your own character set ordered from darkest to lightest:

python -m ascii_art_converter.cli image.png --custom-charset " .:-=+*#%@"

Complex Image Processing

Combine multiple options for advanced effects:

python -m ascii_art_converter.cli image.png \
    -w 120 \
    --char-ratio 0.45 \
    --mode braille \
    --dither floyd_steinberg \
    --colorize \
    --color-mode 256 \
    --contrast 1.2 \
    --brightness 1.1 \
    --sharpness 1.5

Batch Processing

Use the batch processing functionality to convert multiple images with the same configuration:

from ascii_art_converter.batch import BatchProcessor
from ascii_art_converter.generator import AsciiArtConfig
from ascii_art_converter.constants import RenderMode

# Create a batch processor
processor = BatchProcessor()

# Define configuration
config = AsciiArtConfig(
    width=80,
    mode=RenderMode.DENSITY,
    colorize=True,
    color_depth=8  # 8 for 256-color, 24 for true color
)

# Process all PNG files in a directory
processor.process_directory(
    input_dir="images/",
    output_dir="output/",
    config=config,
    extensions=[".png", ".jpg"]
)

API Usage

The library can be used programmatically in your Python projects:

from PIL import Image
from ascii_art_converter.generator import AsciiArtGenerator, AsciiArtConfig
from ascii_art_converter.constants import RenderMode

# Load an image
image = Image.open("data/test.png")

# Create configuration
config = AsciiArtConfig(
    width=100,
    mode=RenderMode.DENSITY,
    char_aspect_ratio=0.45,
    colorize=True,
    color_depth=24,  # 8 for 256-color, 24 for true color
    contrast=1.2
)

# Generate ASCII art
generator = AsciiArtGenerator()
result = generator.convert(image, config)

# Print the result
print(result.text)

# Save as HTML
from ascii_art_converter.formatters import HtmlFormatter
html_content = HtmlFormatter.format(result, image, True)
with open("output.html", "w", encoding="utf-8") as f:
    f.write(html_content)

# Save as ANSI
from ascii_art_converter.formatters import AnsiColorFormatter
ansi_content = AnsiColorFormatter.format_result(result, color_mode="256")
# with open("output.ansi", "w", encoding="utf-8") as f:
#     f.write(ansi_content)
print(ansi_content)

Examples

Basic ASCII Art

python -m ascii_art_converter.cli image.png -w 80

Colored Braille Art

python -m ascii_art_converter.cli image.png -w 100 -m braille -c --color-mode 256

Edge Detection Art

python -m ascii_art_converter.cli image.png -w 90 -m edge --edge-detector canny -t 0.15

HTML Output with Custom Styling

python -m ascii_art_converter.cli image.png -w 120 --colorize -o output.html

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Development Setup

1. Fork the repository
2. Create a virtual environment:

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

3. Install development dependencies:

   pip install -e .[dev]
   

4. Run tests:

   pytest
   

Code Style

• Follow PEP 8 guidelines
• Use type hints for function signatures and variables
• Write docstrings for all public functions and classes
• Add tests for new functionality

License

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

Acknowledgments

• Inspired by various ASCII art converters and image processing techniques
• Built on top of Pillow and NumPy for robust image manipulation
• Thanks to all contributors who have helped improve this project

Support

If you encounter any issues or have questions, please open an issue on the GitHub repository.