Don't use computer vision

Thank you!

So, if you took 100 photos of an extremely rare bird and then put them in one observation… That would improve Al majorly for that species?

March 2020, taxa included in the training set must have at least 100 observations, at least 50 of which must have a community ID


Good points! I also spend a lot of time comparing and using my field guides and internet searches to try to be sure about IDs. As a relative iNat user I still have a lot to learn!

Is only the first photo of an observation used in the training? I thought I remembered reading that somewhere.


@bbinsecte, see This is not an automatic clean-up, but it helps to direct attention to identifications that are systematically incorrect.

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I think tiwane said they use all the photos

I think it only does a compare on the first photo in a new observation.

e.g a new “birds” observation with multiple photos is uploaded. The CV only looks at the first photo on this birds observation to make its suggestions.

We only send the first photo of an observation to the computer vision model.


I think the question is if all photos in an observation of a qualifying species are sent into the big mysterious box that does the training.

Not which photos in an observation are used if you ask to run the CV on your record.


That makes it vital for us to choose the first photo to provide the best information.
Not, you can see the … on the third photo.

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Thanks @cmcheatle. I asked our developers for some confirmation, and here’s what they said in regard to training the model:

  • If a taxon, eg Anas platyrhynchos, has more than 1,000 images, we randomly choose 1,000 images of it for training, and those could be drawn from any photo in an observation.

  • If a taxon has 999 photos or less, we train on basically all of them, with a few left out for testing and validation.


Well, sure, but new users may not know that.

I know I used to just add multiple photos by
(1) batch selecting them my phone gallery without regard to order,
(2) putting them in the order I took them,
(3) taking pics directly from the app, without considering that I needed to put the “best” pic first (I especially used to put wide shots of plants before the close-ups).

Apart from ‘training iNat’ people are time pressed, so I try to crop and sort my own photos.

It can sometimes be a mission to work out what are we looking at, please
Yesterday I said moss, and a bryologist said no, it’s a tiny flowering plant. Zoomed in, I could see Crassula leaves


Yep, I’ve learned (and am still learning) tricks of iNat and now I try to put the pic I think is most diagnostic first.
Not for “training iNat” - as cmcheatle & tiwane clarified, the first pic is not what feeds the CV, but what it looks at on new records before offereing suggestions - but for making it easier on Identifiers, so they don’t have to go through every pic I attached.


I’ve talked to a few mycologists who hate iNaturalist. They won’t use it, neither submitting or IDing.

I think there are a lot of plant peeps on iNat. Don’t know why no one has been checking out your plant obs. I’ll take a look at them for you.

As an amateur mycologist I’m curious why mycologists won’t use. I know two who do one of whom practically preaches iNat.
I will say that I’ve seen an inordinate number of dead wrong fungal CV id’s lately. Seems to be mostly new observers.


Oh, you don’t need to feel obligated to do that.
Plants of Texas is a collection project that picks up a bunch of my stuff. Between that and a few other projects I manually add stuff to, if I don’t get an ID it’s usually because I didn’t include anything diagnostic in my pics.


That’s a shame. I can think of at least 2 on iNat who seem to do a lot of IDing.


I tried to ask but they didn’t want to talk about it. :woman_shrugging: