A powerful and flexible Python library for converting images to ASCII art, Braille art, and edge detection art
Project description
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.
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⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡔⠃⠀⠈⠉⣥⣶⠛⠿⠋⠀⠁⠾⡿⠟⠃⠁⠀⠈⠙⠛⠛⠋⠀⠀⠀⠀⠾⡿⠋⠀⠈⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿
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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
- Clone the repository:
git clone https://github.com/our0boros/ascii-art-converter.git
cd ascii-art-converter
- 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 setdetailed: More detailed character set for higher resolutionblocks: Block characters for bold, contrasting artsimple: Simplified character set for minimalistic artbinary: Only two characters (0 and 1) for binary artdots: Dot-based charactersgeometric: 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
- Fork the repository
- Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
- Install development dependencies:
pip install -e .[dev]
- 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.
Project details
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