21. Interpolating, Tips Tricks and Geen GPS in Fotos, Press on Photo geeft een heel ander effect bij fotos toevoegen
Blijkbaar kun je in de (Android?) app op zes verschillende manieren fotos toevoegen. De manier kan er voor zorgen dat de GPS coordinaten ook uit een later toegevoegde foto gehaald kan worden.
- Tap the green plus icon, tap “Choose Image,” choose one photo, then tap the camera icon to add more photos
- Tap the green plus icon, tap “Choose Image” and long-press to choose multiple photos at once
- Tap the green plus icon, tap “No Photo” and tap the camera icon to add photos, manually changing all the other settings
- Find a photo in your photos or gallery app and share the photo with iNaturalist, then tap the camera icon to add more photos
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Long-press to select multiple photos in your photos or gallery app to share multiple photos as a single observation in iNaturalist
Something else?'
What I’m seeing is that long-pressing in the photos app to **share multiple photos with iNat as a **single observation currently does what you’re asking for, i.e. it consistently imports coordinates from one of the photos even if another doesn’t have coordinates. Strangely, choosing multiple photos from within the iNat app does not have that effect. If we made both of these behave the same (i.e. we always get coordinates when we can), would that solve your issue, @erininmd?
Not importing coordinates (or any other metadata) when tapping the photos icon on the observation edit screen to add additional photos is intentional. I think we may have done that at some point and it was extremely jarring. Actually I think what we did was prompt you whether or not you wanted to use the metadata from a new photo you were importing and most people found that insanely confusing (I kind of liked it).
I’m not entirely convinced @pisum’s solution of choosing which photo to import coordinates from solves a problem a lot of people are having. I could imagine it being useful in situations where the coordinates are way off on the first photo you took but much better on the last, but that seems like a distant edge case. Just my opinion, though. Could be interesting to show the coordinates from all photos on the location chooser just so you can change the coordinates if the app got coordinates from one bad egg.
https://forum.inaturalist.org/t/look-for-location-in-more-than-1-picture/3679/12
For example, in this observation: https://www.inaturalist.org/observations/25972355 5
Both of the in focus pictures lacked location tagging, and it wasn’t until I tried the out of focus image that I was able to get the coordinates.No location found:
https://photos.app.goo.gl/ZSAR3CKhq2Hx7wbx9Found coordinates in the 3rd picture
https://photos.app.goo.gl/f92HPdfdXuMBfPx26 1
https://forum.inaturalist.org/t/interpolating-coordinates/5170
Interpolating, Tips Tricks and Geen GPS in Fotos, Press on Photo geeft een heel ander effect bij fotos toevoegen (21)
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Op dit moment wordt het zelfde determinatie model gebruikt maar gevoed met veel meer soorten en veel meer fotos waardoor het 210 dagen duurt om het volledige model door te rekenen.
Voor de rest worden er niet te veel aanpassingen gedaan. Om het model sneller door te laten rekenen was nieuwe hardware aangeschaft maar door COVID Corona wilde ze niet het risico lopen om COVID op te lopen en was het voordeel van de nieuwe hardware te weinig tov gelopen risico's . https://www.inaturalist.org/posts/31806-a-new-vision-model#activity_comment_5737746
We're currently training a new model based on an export in September that had ~18 million images of 35k+ taxa. It's running with the same setup that we've used on previous models, but with a lot more data, so it will probably take ~210 days and be done some time next Spring. We're simultaneously experimenting with an updated system (TensorFlow 2, Xception vs Inception) that seems to be much faster, e.g. it seems like it might do the same job in 40-60 days, so if it seems like the new system performs about the same as the old one in terms of accuracy, inference speed, etc., we might just switch over to that and have a new model deployed in January or February 2021.
FWIW, COVID has kind of put a hitch in our goal of training 2 models a year. We actually ordered some new hardware right before our local shelter in place orders were issued, and we didn't feel the benefit of the new hardware outweighed the COVID risk of spending extended time inside at the office to assemble everything and get it running. Uncertainty about when it would be safe to do so was part of why we didn't start training a new model in the spring (that and the general insanity of the pandemic), but eventually we realized things weren't likely to get much better any time soon so we just started a new training job on the old system.
The Academy is actually open to the public again now, with fairly stringent admission protocols for both the public and staff, so we might decide to go in an build out that new machine, but right now we're still continuing with this training job and experimenting with newer, faster software at home.
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