Excel Pixel Art

Convert images to Excel pixel art and back. Each cell becomes a pixel with its background colour matching the original image.

Installation

pip install excel-pixel-art

Or install from source:

git clone https://github.com/luigipascal/excelart.git
cd excelart
pip install -e .

Usage

Convert Image to Excel

image2xlsx photo.png
image2xlsx photo.png -o output.xlsx
image2xlsx photo.png --max-size 150

Options:

  • -o, --output: Output Excel file path (default: <input>_excel.xlsx)
  • --max-size: Maximum dimension in cells (default: 100)

Convert Excel Back to Image

xlsx2image output.xlsx
xlsx2image output.xlsx -o recovered.png
xlsx2image output.xlsx --sheet Sheet1

Options:

  • -o, --output: Output image path (default: <input>_reconstructed.png)
  • --sheet: Worksheet name to use (default: 'Image' if present, else active)
  • --background R,G,B: Background colour for missing cells (default: 0,0,0)
  • --no-autocrop: Disable auto-crop to solid-fill bounds

QA & Verification

# Compare with original for fidelity check
xlsx2image output.xlsx --compare original.png

# Generate visual diff heatmap
xlsx2image output.xlsx --compare original.png --diff-image diff.png

# CI pass/fail with threshold
xlsx2image output.xlsx --compare original.png --diff-threshold 5

Python API

from excel_pixel_art import image_to_excel, excel_to_image, compare_images

# Convert image to Excel
image_to_excel("photo.png", "output.xlsx", max_size=100)

# Convert back
excel_to_image("output.xlsx", "recovered.png")

# Compare for QA
compare_images("photo.png", "recovered.png", diff_output="diff.png", diff_threshold=5)

How It Works

  1. Image → Excel: The image is resized to fit within max_size cells, maintaining aspect ratio. Each pixel becomes a cell with a solid fill colour matching the RGB value.

  2. Excel → Image: Cells with solid fills are read back, extracting their ARGB colour values. Auto-crop detects the actual pixel bounds, ignoring stray formatting.

  3. QA Tools: The fidelity report compares reconstructed images against originals, with optional diff heatmaps and threshold-based pass/fail for CI integration.

Features

  • ARGB colour handling - Proper Excel colour format (no transparency bugs)
  • Fill caching - Fast generation even for images with thousands of unique colours
  • Auto-crop - Ignores stray formatting outside the pixel grid
  • Robust extraction - Handles both fgColor and start_color patterns
  • CI-friendly - Threshold-based pass/fail for automated testing

License

MIT

Project links

Data verified by PyPI on Dec 30, 2025
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Avatar for luigipascal from gravatar.com luigipascal

Credits

Author: Rondanini Publishing

GitHub Statistics

Data verified by PyPI on Dec 30, 2025
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python >=3.9

Provides Extra

dev

Tags

excel image-conversion openpyxl pixel-art

Classifiers

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