As opposed to say, Flat Bed Compressionism…
My latest effort of using search engines, in this case ‘search’ via Metacrawler as a kind of geeky palet-knife.
PixelPLEXUS
where some pixels meet for drinks after a hard day
As opposed to say, Flat Bed Compressionism…
My latest effort of using search engines, in this case ‘search’ via Metacrawler as a kind of geeky palet-knife.
Beautiful! Now, maybe here is what I’m thinking. Could we, possibly, make images like this – but maybe 10 of them? In other words, have 10 searches (whether these be static or dynamic based on current searches, or most popular search terms from the day before) to make images as above, dynamically? Depending on how fast the algorithm is, we can also do one dynamic one based on what people type in… Maybe all in one page, maybe pop-ups, that can be decided later. How were these images created? What do you think?
Yes, lets do that, but…
bear with me as i run through the process of making the latest one ‘Search Our Family Photos’: (or skip to point 4)
1. I treated the recording process as manual generative, IE typed ‘search’ into metacrawler’s image search with size specified as large and restrict to JPG files.
Metacrawler doesn’t serve them up as neatly as google so had to click through to the sites where i saved the the first recognizable image – this is perfect for automating via scripting, and i think could easily done through e.g. a flash interface
2. the images were all saved into a folder
3. ran a photoshop action magnifying the images, sans antialiasing and pasting them into a layered tiff file – 20 of them – into a 7087 px square tiff – this was SLOW
4. from here it gets a bit more ‘performative’ and I’m note sure how to translate it into our automaton (but have some ideas see A. below) – in that i was trying to find an emergent image in the layered synthesis so:
1. disabled all but the bottom two layers, setting the higher one to 50% – then manually rotating and scaling untill it I imagined I saw recognized something new in the image, then same with next layer at 33%, then 25%, then20%, these layers then merged, and the process repeated with the next batch of 5 layers, until it leaves just one layer.
5. finally i perform a kind of signiture filter effect that i do to most all these
A. Finding the emergent: say we make a copy of each source image, reduce it to binary Black/white, just ones and zeros. Then use a ‘little math’ to identify the biggest light area, and automate aligning/positioning this across the layers via scaling and rotation of each entire map, (which will invariably create some cropping artifacts that typically add to the cubist-look factor and fine )
PS. these were produced at high res print resolution, we don’t neccesarily need to do that for an online interpretation, also, it could be live, but seems to make sense to have a kind of automaton up and running, maybe tweaking its process based on results being ranked?
we’ll have to experiment, obviously, but (per mail) tech options include ImageMagick, GD, flash and Jitter…. plus hack google. Word. nice!
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