Announcing Open-Source Word Clouds by WordCram

Dan Berni..

Announcing Open-Source Word Clouds by WordCram

in Library and Tool Development • 3 years ago

Inspired by Wordle, built on Processing.

Word clouds are images of non-overlapping words, sized by relative importance (usually word frequency). WordCram takes weighted words, and makes word clouds. It'll count up your words for you, if you like. You can pick the colors, the fonts, the layout strategy, how words are sized, and how they're angled -- good, clean customization is a big deal to WordCram.

Development is currently focused on speed and good layout strategies. Near-future plans include more text processors, and more pre-baked word colorers, layout strategies, and other components.

Get the source: http://github.com/danbernier/WordCram
Read the news: http://wordcram.org
Follow the tweets: http://twitter.com/wordcram

See WordCram in action: http://www.openprocessing.org/visuals/?visualID=12413 , http://www.flickr.com/photos/bonsai_giant/tags/wordcram/

Replies(7)

darhem

Re: Announcing Open-Source Word Clouds by WordCram

1 year ago

Great Job;

is there any possibility for shape-based word clouding via this library?

Dan Berni..

Re: Announcing Open-Source Word Clouds by WordCram

1 year ago

> is there any possibility for shape-based word clouding via this library?

Not right now, but I've hacked out something close, before, so I'm optimistic. It's open-source, so if you'd like to take a crack at it, feel free... :)

calsign

Re: Announcing Open-Source Word Clouds by WordCram

1 year ago

Your OpenProcessing link returns a 404 error; it appears that you have a trailing comma on the link.

EDIT (after looking at the links...): Your library looks great... there are a lot of people around the forum who have asked for this kind of functionality at one point in time. Great job!

Dan Berni..

Re: Announcing Open-Source Word Clouds by WordCram

1 year ago

@calsign, thanks - I fixed the OpenProcessing link, & updated the others to point to the new blog & github repo. And thanks for the kind words! I'd love to keep adding to WordCram, eventually supporting shapes like @darhern asked for. And I'd really like to port it to javascript...

ariffinas..

Re: Announcing Open-Source Word Clouds by WordCram

1 year ago

Great Job man, very nice interactive typography... peace!

gmassol

Re: Announcing Open-Source Word Clouds by WordCram

9 months ago

Very nice Dan,

I'm experimenting with your library and I have a question on how to use drawNext() with a customCanvas? I've managed to create a wordCram withCustomCanvas and show all my words with drawAll() then displaying the image without problem but I don't figure out how to do that with drawNext? Also is the smooth enabled when you use a custom canvas? What I'd like to do is overlaying some text on top of an image and show one words after another.

Another question actually, I'd like the wordcram not to limit itself to the size of the canvas, that's why I'm using a customCanvas 2 times bigger than the size of the sketch, though is there any option to do that more easily ad to force all the words to render even if they are outside of the canvas size? You know what I mean?

Cheers and thanks for the library,

G.

Dan Berni..

Re: Announcing Open-Source Word Clouds by WordCram

8 months ago

Re: using drawNext() w/ a customCanvas, if you look in the WordCram examples, under OtherExamples, there's a renderToBuffer example that does just what you're looking for. Here it is on github: https://github.com/danbernier/WordCram/blob/master/example/OtherExamples/renderToBuffer/renderToBuffer.pde

If you want your custom canvas to use smooth(), you just call it on the canvas before you start calling wordcram.drawNext().

WordCram defaults to trying to place every word, but it only tries to place each word so many times, before moving on. You can force more words to be drawn by setting maxAttemptsToPlaceWord() to something high, though it'll slow down the sketch. I think it tries ~700 times for the heaviest word, and progressively less, for each word. Setting it to ~1000 should get you more words.

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