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Tech riderRev. 3 Oct 2026

phomo

Ch 066.9of 23 Photo Mosaic Software
  1. 1Runs onLinux, Mac, Windows
  2. 2CostsFree plan
  3. 3Platformdesktop
  4. 4Custom tile libraryYes
  5. 5Tile reuse controlsYes
  6. 6Output formatsPNG
6 lines stated Written from the maker's own pages: github.com
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The phomo homepage

Overview

phomo is a free tool that creates photographic mosaics by arranging tile images to recreate a master image. It compares color distributions between tiles and regions of the master, then assigns tiles using a linear sum assignment algorithm. The project can be installed with pip as a Python package or run through its `phomo` command, which accepts a master image and a directory of tile images. Command-line options include cropping and resizing the master and tiles, black-and-white conversion, grid display, and control over how often tiles appear. Matching choices include greyscale, norm, and luv_approx distance metrics, color equalization, and color-distribution matching. A greedy assignment mode is described as improving performance while reducing accuracy. CUDA acceleration is available through an extra, requiring a CUDA-compatible GPU and toolkit. The package requires Python >=3.9 and <3.13, runs on Linux, macOS, and Windows, and lists PNG as its output format. It is published under the MIT License.

Who it is for

phomo suits people comfortable using a Python package or command-line tool to build image mosaics from their own tile library. It offers controls for image preparation and tile matching across Linux, macOS, and Windows.

What is good

  • Free Python package and command-line utility.
  • Offers multiple tile-matching metrics and color controls.
  • Supports Linux, macOS, and Windows.
  • Published under the MIT License.

What to know first

  • Requires Python >=3.9 and <3.13.
  • CUDA acceleration requires a compatible GPU and toolkit.
  • Greedy assignment trades accuracy for performance.

Verdict

phomo exposes mosaic creation through a Python package and CLI, with several image and matching controls. CUDA acceleration has additional hardware and toolkit requirements, while greedy assignment sacrifices accuracy for performance.

phomo plans and pricing

All plans
phomo Free Python package and CLI utility · CUDA acceleration requires a compatible GPU and CUDA toolkit github.com · 3 Oct 2026

Compared on photo mosaic software

Free plan
Yesgithub.com
Platform
desktopgithub.com
Custom tile library
Yesgithub.com
Tile reuse controls
Yesgithub.com
Output formats
PNGgithub.com

Facts

Purpose
phomo creates photographic mosaics by arranging tile images to recreate a master image.github.com · 3 Oct 2026
Tile matching
It compares tile images with master image regions using color distribution differences, then assigns tiles to regions with a linear sum assignment algorithm.github.com · 3 Oct 2026
Python package
The project can be installed with pip and used as a Python package.github.com · 3 Oct 2026
Command line
The package provides a `phomo` command that accepts a master image and a directory of tile images.github.com · 3 Oct 2026
GPU support
GPU acceleration is available through the CUDA extra and requires a CUDA-compatible GPU and CUDA toolkit.github.com · 3 Oct 2026
Image controls
CLI options include cropping and resizing the master and tile images, black-and-white conversion, grid display, and tile appearance count.github.com · 3 Oct 2026
Matching options
The CLI offers greyscale, norm, and luv_approx distance metrics, color equalization, and options to match color distributions.github.com · 3 Oct 2026
Performance option
A greedy tile assignment option is described as improving performance at the expense of accuracy.github.com · 3 Oct 2026
Platforms
PyPI lists macOS, Windows, and Linux operating system classifiers for the package.pypi.org · 3 Oct 2026
Python versions
PyPI states that the package requires Python >=3.9 and <3.13.pypi.org · 3 Oct 2026
License
The project is published under the MIT License.github.com · 3 Oct 2026
Maintainer
PyPI identifies Loic Coyle as the author and lists one maintainer.pypi.org · 3 Oct 2026

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