Comments (8)
any interest, @imalsogreg ?
from facebook-political-ads.
Since my understanding is that these perceptual hash algorithms are primarily architected in Python, this could either happen as part of the classifier classify
step in Python in this repo, or in a similar, but new, separate script that's also run on a frequent cron.
from facebook-political-ads.
That sounds like a lot of fun :) Let me see if I can get a proof of concept up.
from facebook-political-ads.
Awesome, holler if you have Qs or if there's anything I can help with.
from facebook-political-ads.
Hi, I just stumbled on this.
I have experience making reverse image search engines using features extracted from pre-trained neural networks, and then calculating distance using KNN. There's some more info (code, presentation, video) in this repo:
https://github.com/yinleon/pydata2017
Let me know if this method sounds interesting for this project
(sorry for the shameless self-promotion).
from facebook-political-ads.
Hi @yinleon, that sounds amazing. In my response to your other comment, I posted a link to download the entire dataset of US political ads.
This sounds potentially really promising. Are the extracted features interpretable (e.g. "this one has a picture of Nancy Pelosi")? Can you describe how well it works identifying nearly-identical images versus more heavily modified or cropped images? What about images with text overlays, like memes?
I'm not super familiar with Keras. Would it be possible for me or a colleague to test your implementation on an ordinary MacBook Pro? Or is it easier to set it up on a GPU-enabled AWS instance?
I really appreciate your taking the time to share about your research. You're of course welcome to download and check out our data and I'd love if we could find a way to work together. Happy to talk more about my qualitative observations of the ad images, if that'd be helpful.
from facebook-political-ads.
@jeremybmerrill I sent you an email to talk in depth about this.
from facebook-political-ads.
This sounds awesome!
Pre-trained ResNet probably has lots of features that are relevant for general image search (common objects, body parts), and lacks some that would specifically help categorize political ads (Nancy Pelosi neurons, e.g.). I wonder how hard it would be to retrain ResNet with lots of extra labeled examples, with those labels drawn from politically relevant topics. Your google image scraper could be useful there?
I'd always assumed image classifiers would be terrible for image search, but from your video, apparently it can work great, when you don't throw away all features but the strongest one :P Cool result with KNN search.
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Related Issues (20)
- You have been added to awesome-humane-tech
- Jest complaining about missing key HOT 1
- Want to bring it to Brazil! HOT 1
- Did the ad collector stop working with the new update of Chrome (v66)? HOT 2
- impressions incorrectly set to 0 sometimes
- Classifier data tracking in git leads to large git history HOT 7
- state page combining targeting and candidates HOT 2
- new column, parse out "Paid for by" string from ads HOT 2
- classify ads by whether they're persuasive, mobilization, listbuilding or fundraising HOT 3
- Collecting ads in a new country HOT 1
- Add "homepage_url" key to manifest.json? HOT 3
- How is the add-on detecting country location? HOT 1
- ProPublica 1.6.15 extension content does not fit window when in overflow menu HOT 1
- Notifications glitchy closing while browsing pull-down list HOT 2
- Don't put Facebook first in the title
- Addon says I've categorized 0 ads - I think I've done at least 60 HOT 4
- Facebook posts' context menus spontaneously open (and steal my arrow-key-focus) HOT 16
- get political ads filtered by language from ProPublica? HOT 3
- Ads I'm Seeing empty despite seeing ads HOT 2
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