GCP has a number of models-as-a-service https://cloud.google.com/products/machine-learning/ that might be useful. On Mon, Apr 3, 2017 at 6:46 PM Daniel Mietchen < daniel.mietchen@googlemail.com> wrote:
Hi Jordan, can your pipeline help with video or perhaps even audio as well? There are lots of such files as well that need categorization. Thanks, Daniel
On Tue, Apr 4, 2017 at 12:05 AM, Jordan Adler jmadler@google.com wrote:
Looks like some of these images still need categorization. I think
there's
still an unrealized opportunity here to use the results I shared to work
the
backlog of the category on the Commons.
On Thu, Aug 11, 2016 at 1:47 PM Pine W wiki.pine@gmail.com wrote:
Forwarding.
Pine
---------- Forwarded message ---------- From: "Jordan Adler" jmadler@google.com Date: Aug 11, 2016 13:06 Subject: [Commons-l] Programmatically categorizing media in the Commons with Machine Learning To: "commons-l@wikimedia.org" commons-l@lists.wikimedia.org Cc: "Ray Sakai" rsakai@reactive.co.jp, "Ram Ramanathan" ramramanathan@google.com, "Kazunori Sato" kazsato@google.com
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. Luckily, I knew just the place, and the resulting demo, built by
Reactive
Inc., is pretty awesome. It was shared on-stage by Jeff Dean during the keynote 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 (5.9MB): A single text file mapping id to filename in a "id : filename" format, one per line
results.tar.gz (29.6MB): a tgz'd directory of json files representing
the
output of the API, 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!
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