wikimedia-illustrations

Hypothesis

We hypothesize that if we download some random public-domain images from Wikimedia Commons and inject them randomly into a text, it'll make just about any text look more interesting.

Apparatus

• Python 2.7.6 (probably works with older versions too)
• requests
• BeautifulSoup
• Pillow (it might work with PIL too)
• ImageMagick
• some kind of input text (uses lorem ipsum for now)

Method

• Get URLs for all images from all pages of a Wikimedia Commons category, such as PD_Gutenberg or PD-Art_(PD-Japan), and write that list of URLs to an index file.
• Select n images randomly from that index and download them.
• Convert them to PNGs and resize any that are wider than 400 pixels downward
• Inject those images as illustrations in a given text.

Observations

NOTE 1: to stay (IMO) well within Wikimedia's Terms of use, this script sleeps for 8 seconds after making any major HTTP request.

NOTE 2: just because an image is categorized as public domain on Wikimedia Commons does not mean it is necessarily in the public domain. It's always a good idea to double-check.

$ ./wikimedia-illustrations.py mkindex "PD-Art_(PD-Japan)"
http://commons.wikimedia.org/wiki/Category:PD-Art_(PD-Japan)
http://commons.wikimedia.org//w/index.php?title=Category:PD-Art_(PD-Japan)&filefrom=KitawakiI+Rioanji.jpg#mw-category-media
grabbed 2 category index pages
$ mkdir art
$ ./wikimedia-illustrations.py random 4 art/ Wikimedia-Commons-Category-index-PD-Art_\(PD-Japan\).txt
http://commons.wikimedia.org/wiki/File:Kawanabe_Kyosai_Renshishi2.jpg
http://upload.wikimedia.org/wikipedia/commons/1/10/Kawanabe_Kyosai_Renshishi2.jpg --> art/Kawanabe_Kyosai_Renshishi2.jpg
[...]
$ ristretto art/

This is all pretty crazy and a piece of lab equipment should really be broken off of it.

But anyway, this is what the end result looked like (for me), using illustrations taken from the PD-Gutenberg category. It should give you an idea of what to expect.