gif2xls 0.2.2

Convert GIF images into XLS files.

Inspired by xkcd.

Converts GIF encoded images into Microsoft Excel formatted workbooks.

Each frame is assigned a worksheet, and each pixel is assigned a cell.

There are two modes: fancy mode (the default) and boring mode. In boring mode (using -b or –boring at the command line), each cell is assigned a 25-bit integer, with bits 0-23 for an RGB value and bit 24 as transparency. In fancy mode, each cell is made square and is assigned a background colour that is as close to the original pixel value as possible.

An additional sheet named “Info” contains some header information, where each row contains a Name, Value pair.

Installation

gif2xls is now available as a PyPI package! Simply run either of the following from anywhere:

pip install gif2xls        # globally, often requires root/Administrator privileges
pip install gif2xls --user # local to current user (add ~/.local/bin to your $PATH)

To install from source, either run the following as root inside the repo directory:

pip install .

or the following to install as a user package (making sure to add ~/.local/bin/ to your $PATH):

pip install . --user

Usage

Syntax:

gif2xls input_file [-b|--boring] [--width cell_width] [-o output_file.xls(x)]

The default mode is “fancy” mode - use the –boring flag to use “boring” mode which doesn’t use any colour formatting.

In “fancy” mode when using a .xlsx formatted output file, you can use the –width flag to specify how wide and high each cell will be in pixels. For example, –width=5 will generate cells that are 5 pixels wide and high each so that the image appears scaled up 5 times.

The output file can either have a .xls or a .xlsx file extension - signalling to gif2xls your output file format.

NOTE: You must use .xlsx output files for GIF images that are larger than 256 pixels wide - classic .xls worksheets do not support more than 256 columns per worksheet. However, you can still use .xls worksheets for fancy mode images, just as long as they are not wider than 256 pixels.

(C) Thomas Bell 2016, MIT License.