agentbrush 0.1.0

Image editing toolkit for AI agents. Photoshop for Claude Code, Codex, Cursor, and friends.

AgentBrush

Image editing toolkit for AI agents. Photoshop for Claude Code, Codex, Cursor, and friends.

Built from 134 production sessions of print-on-demand image processing. Battle-tested algorithms for background removal, green screen processing, border cleanup, text rendering, compositing, validation, and more.

Install

pip install agentbrush

With AI image generation support:

pip install agentbrush[generate]

Quick Start

Python API

from agentbrush import remove_background, remove_greenscreen, cleanup_border

# Remove black background (edge-based flood fill, safe for artwork)
result = remove_background("input.png", "output.png", color="black", threshold=25)
print(result.summary())
# [OK] output.png
#   Size: 1024x1024px
#   Transparent: 72.3%  Opaque: 27.7%
#   pixels_removed: 758432

# Remove green screen (multi-pass: flood fill + color sweep)
result = remove_greenscreen("input.png", "output.png", halo_passes=20)

# Clean up white sticker border from AI-generated art
result = cleanup_border("input.png", "output.png", passes=15, threshold=185)

Every function returns a Result object:

result.success         # True if no errors
result.width           # Output width in px
result.height          # Output height in px
result.transparent_pct # Percentage of transparent pixels
result.warnings        # Non-fatal issues
result.errors          # Fatal issues
result.metadata        # Operation-specific data
result.summary()       # Human-readable string

CLI

# Background removal
agentbrush remove-bg input.png output.png --color black --threshold 25 --smooth

# Green screen removal
agentbrush greenscreen input.png output.png --upscale 3 --halo-passes 20

# Border cleanup
agentbrush border-cleanup input.png output.png --passes 15 --green-halo-passes 20

# Text rendering
agentbrush text input.png output.png "HELLO" --font mono --bold --size 72
agentbrush text new:1664x1664 output.png "BUG\nFEATURE" --bold --center

# Compositing
agentbrush composite base.png art.png output.png --position 100,200
agentbrush composite paste-centered output.png --overlay art.png --canvas 4500x5400 --fit

# Resize
agentbrush resize input.png output.png --width 4500 --height 5400
agentbrush resize input.png output.png --scale 3.0
agentbrush resize input.png output.png --width 2700 --height 1050 --fit --pad

# Validate design against product specs
agentbrush validate check design.png --type sticker
agentbrush validate compare source.png processed.png --max-loss 10

# Format conversion
agentbrush convert input.png output.jpg --quality 95

# AI image generation (requires openai package)
agentbrush generate --provider openai --prompt "cat coding" --output cat.png

Exit codes: 0 = success, 1 = validation failure, 2 = input error.

Agent Skills

AgentBrush ships as an Agent Skills package. Copy skill/agent-brush/ into your project's .claude/skills/ directory:

cp -r skill/agent-brush/ .claude/skills/agent-brush/

Claude Code (and other compatible tools) will automatically discover the skill and use it when processing images. The skill includes:

• SKILL.md — instructions and quick reference for the agent
• references/ — product specs, troubleshooting guides
• scripts/ — standalone wrappers that work without pip install

Usage Without Install

The standalone scripts work directly from a git clone — no pip install needed:

git clone https://github.com/ultrathink-art/agentbrush.git
cd agentbrush

# Run scripts directly (auto-detects src/ directory)
python skill/agent-brush/scripts/remove_bg.py input.png output.png --color black
python skill/agent-brush/scripts/validate.py check design.png --type sticker
python skill/agent-brush/scripts/greenscreen.py input.png output.png --upscale 3

Requirements: Python >= 3.10 and Pillow >= 12.1 (pip install 'Pillow>=12.1'). Older versions fail at runtime (get_flattened_data API requires Pillow 12.1+, type union syntax requires Python 3.10+).

Modules

Module	Description	Key function
background	Edge-based flood fill bg removal	remove_background()
greenscreen	Multi-pass green screen pipeline	remove_greenscreen()
border	White border erosion + green halo	cleanup_border()
text	Pillow text rendering (accurate)	add_text(), render_text()
composite	Image layering + centering	composite(), paste_centered()
resize	Resize with fit/pad/scale modes	resize_image()
validate	Design QA against product specs	validate_design(), compare_images()
convert	Format conversion (PNG/JPEG/WEBP)	convert_image()
generate	AI image generation (optional)	generate_image()

Core Primitives

Low-level functions available for custom pipelines:

from agentbrush.core import (
    flood_fill_from_edges,   # BFS flood fill (4-conn or 8-conn)
    is_near_color,           # Color distance matching
    parse_color,             # Parse "black", "white", "R,G,B" strings
    smooth_edges,            # 1px edge feathering
    smooth_alpha_edges,      # Gaussian alpha blur (edges only)
    find_artwork_bounds,     # Opaque pixel bounding box
    crop_to_content,         # Crop to content with padding
    find_opaque_centroid,    # Center of mass for opaque region
    ensure_single_shape,     # Remove floating elements (8-connected BFS)
    count_components,        # Connected component count
    find_font,               # Cross-platform font discovery
)

Product Presets

Built-in dimensions for print-on-demand products:

Product	Width	Height	Transparent	Notes
T-shirt	4500	5400	Required	Apparel
Hoodie	4500	5400	Required	Apparel
Hat	1890	765	Required	Wide horizontal
Mug (11oz)	2700	1050	Recommended	Wrap-around
Sticker	1664	1664	Required	Die-cut, single shape
Desk mat	9200	4500	No	Large format
Poster	5400	7200	No	Portrait

Why Edge-Based Flood Fill?

Threshold-based removal (magick -fuzz -transparent black) scans every pixel and removes anything "close enough" to the target color — including internal outlines, dark shadows, and fine details inside the artwork.

AgentBrush starts flood fill from image edges only. Interior pixels that happen to match the background color are never touched because flood fill can't reach them without crossing through the artwork.

Threshold-based:              Edge-based flood fill:
removes ALL dark pixels       removes ONLY edge-connected dark pixels
+-----------------+           +-----------------+
|                 |           |                 |
|    #########    |           |    #########    |
|   #         #   | <- loses  |   #*********#   | <- preserved!
|   #         #   |   detail  |   #*********#   |
|    #########    |           |    #########    |
|                 |           |                 |
+-----------------+           +-----------------+

Examples

Full pipeline guides with code:

• Sticker Pipeline — AI art -> green screen -> border cleanup -> validate die-cut
• T-Shirt Pipeline — artwork -> transparent bg -> resize to 4500x5400
• Mug Pipeline — sticker adaptation -> wrap format -> multi-sticker composition

Testing

pip install -e ".[dev]"
pytest tests/ -v

All tests use synthetic Pillow-generated fixtures (no production images). 126 tests covering all modules.

Dependencies

• Required: Pillow >= 12.1
• Optional: openai >= 1.0 (for generate command)
• Dev: pytest >= 7.0, pytest-cov

License

MIT