[OSM-talk] Pictures of opening hours signs for machine learning purposes
iboates at gmail.com
Sun Apr 11 11:19:30 UTC 2021
>Is it possible to set up the language that should be detected in Amazon
It seems not, I guess it only has one model and it only detects unaccented
"standard" latin characters. But from what I saw it seemed at least fairly
consistent when mapping ö -> o, ü -> u, etc. I tried passing an image that
had "ß" in it and it just didn't pick it up at all. So that could be a
On Sun, Apr 11, 2021 at 12:58 PM Toggenburger Lukas <
Lukas.Toggenburger at fhgr.ch> wrote:
> > I didn’t do any additional work on deduplicating the images. I’m not
> sure why you think this is important if you’re going to use it for ML
> @Bryce: It's important if one wants to splitt off a test dataset in order
> to have a good estimate how good the recognition works: If you have almost
> the same image in the training dataset and the test dataset, your estimated
> real-world performance will be better than it really is. (An alternative
> approach would be to make sure that pictures of the same opening hours sign
> either end up in the training dataset or the test dataset, but not both.
> But having such a set of pictures in the test dataset makes it hard to
> calculate a success rate.)
> > Keep in mind I’m not doing any ML training, so having a larger sample
> size doesn’t benefit me.
> > I wanted a large number of test images in order to measure the expected
> accuracy of the OCR
> > and algorithm in a real-world settings. My plan now is to build a
> stand-alone app for testing
> > during surveying, improve the recognition by building better spatial
> models of how the text is
> > laid out, and then finally integrate it into Go Map!!
> @Bryce: Ok, in that case you only need one set of images. But you would
> still profit from
> a) a large (test) dataset
> b) annotations of the expected results (opening hours) to compare
> different implementations against each other
> > I’m working on this at https://github.com/bryceco/OpeningHoursPhoto
> @ Bryce: Cool! Thanks for sharing!
> > The data is not big but not tiny either (about 23MB) I've put them into a
> > github repo:
> > https://github.com/iboates/osm-opening-hours-signs-rekognition-results
> @Isaac: Thanks for sharing!
> > It will probably then have trouble detecting the "ß" character if it
> > up (will probably often show up as "B", but from what I understand it
> > doesn't appear in Swiss German.
> Yes, "ß" is practically never used in Switzerland (except maybe by german
> shop owners in our case...), instead "ss" will be used.
> Is it possible to set up the language that should be detected in Amazon
> Best regards
> Von: Isaac Boates <iboates at gmail.com>
> Gesendet: Samstag, 10. April 2021 21:40
> An: Bryce Cogswell
> Cc: Toggenburger Lukas; talk at openstreetmap.org
> Betreff: Re: [OSM-talk] Pictures of opening hours signs for machine
> learning purposes
> I took the images from the "deduplicated in Bryce's download link and ran
> them through Amazon Rekognition for text extraction. So no actual training
> or modelling done by me, but it's a pretty cheap service (1.20 USD per 1000
> images on the Frankfurt server). It gives back a JSON for every image with
> precise details about what it found, where it is on the image, etc. So I
> saved the results for each image with a JSON with the same name as the
> image, just with ".json" as a file extension.
> I didn't go through the results in detail just yet, I wanted to share them
> first so anyone can dig through them to see what's in there & potentially
> get ideas from them. One thing I did notice however is that it does not
> detect accented characters, so "Öffnungszeiten" becomes "Offnungszeiten".
> It will probably then have trouble detecting the "ß" character if it comes
> up (will probably often show up as "B", but from what I understand it
> doesn't appear in Swiss German.
> The data is not big but not tiny either (about 23MB) I've put them into a
> github repo:
> Also just as a disclaimer I am not affiliated with Amazon in any way, I
> just had some experience with this specific product from them and thought
> it would be good to just run the data through a "state of the art"
> pre-built ML solution.
> On Sat, Apr 10, 2021 at 4:04 PM Isaac Boates <iboates at gmail.com<mailto:
> iboates at gmail.com>> wrote:
> @Lukas: I was having a bit of trouble getting the guest account
> permissions set up on my AWS but then Bryce went ahead and posted a direct
> link, thanks for that!
> On Sat, Apr 10, 2021 at 5:52 AM Bryce Cogswell via talk <
> talk at openstreetmap.org<mailto:talk at openstreetmap.org>> wrote:
> @Bryce: Did you already make significant efforts regarding deduplicating /
> sorting or otherwise processing the images? If yes, maybe you could share
> this altered dataset with Isaac and other interested parties?
> I didn’t do any additional work on deduplicating the images. I’m not sure
> why you think this is important if you’re going to use it for ML training.
> @Bryce: Congratulations! I already saw some correctly recognized
> specimens! That is certainly encouraging, isn't it? Do you already know
> if/how you would proceed further? If you would be okay with publishing with
> what you already have, maybe others could build upon that.
> I remember one idea we had: If users of such a recognition feature would
> be willing to (automatically, with little/no effort) share the pictures to
> increase the pool of pictures you could create a virtuos cycle, especially
> if you can motivate them to either mark detections as correct or let them
> fix it as needed.
> Keep in mind I’m not doing any ML training, so having a larger sample size
> doesn’t benefit me. I wanted a large number of test images in order to
> measure the expected accuracy of the OCR and algorithm in a real-world
> settings. My plan now is to build a stand-alone app for testing during
> surveying, improve the recognition by building better spatial models of how
> the text is laid out, and then finally integrate it into Go Map!!
> I’m working on this at https://github.com/bryceco/OpeningHoursPhoto but
> the code is super rough at this point.
> The image set it is at
> http://gomaposm.com/opening_hours/opening_hours.zip> (12.5GB download)
> talk mailing list
> talk at openstreetmap.org<mailto:talk at openstreetmap.org>
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