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: - 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 - 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!