Hey folks!
A few months back a colleague of mine was looking for some unstructured images to analyze as part of a demo for the Google Cloud Vision API https://cloud.google.com/blog/big-data/2016/05/explore-the-galaxy-of-images-with-cloud-vision-api. Luckily, I knew just the place https://commons.wikimedia.org/wiki/Category:Media_needing_categories, and the resulting demo http://vision-explorer.reactive.ai/, built by Reactive Inc., is pretty awesome. It was shared on-stage by Jeff Dean during the keynote https://www.youtube.com/watch?v=HgWHeT_OwHc&feature=youtu.be&t=2h1m19s at GCP NEXT 2016.
I wanted to quickly share the data from the programmatically identified images so it could be used to help categorize the media in the Commons. There's about 80,000 images worth of data:
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map.txt https://storage.googleapis.com/gcs-samples2-explorer/reprocess/map.txt (5.9MB): A single text file mapping id to filename in a "id : filename" format, one per line
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results.tar.gz https://storage.googleapis.com/gcs-samples2-explorer/reprocess/results.tar.gz (29.6MB): a tgz'd directory of json files representing the output of the API https://cloud.google.com/vision/reference/rest/v1/images/annotate#response-body, in the format "${id}.jpg.json"
We're making this data available under the CC0 license, and these links will likely be live for at least a few weeks.
If you're interested in working with the Cloud Vision API to tag other images in the Commons, talk to the WMF Community Tech team.
Thanks for your help!