Please, do not encourage use of AI suggestions without at least some knowledge of the object. Cleaning the resulting mess is one of the reasons which discourage qualified IDers, because it is very tedious to get into the lengthy discussions as to why the ID is not correct. The argument being – but i…

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 https://www.inaturalist.org/pages/help#cv-taxa

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!

[image] cmcheatle: 100 photos, not 100 observations, of which 50 need to be research grade. Is only the first photo of an observation used in the training? I thought I remembered reading that somewhere.

[image] bbinsecte: Is it conceivable that these suggestions could be marked as systematically incorrect, in order to reduce the probability of their appearance in the automatically generated list? @bbinsecte , see https://forum.inaturalist.org/t/computer-vision-clean-up-wiki/7281 . This is not…

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.

Don't use computer vision

General

janetwright June 25, 2020, 1:23pm 126

@bbinsecte, see https://forum.inaturalist.org/t/computer-vision-clean-up-wiki/7281. This is not an automatic clean-up, but it helps to direct attention to identifications that are systematically incorrect.

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Don't use computer vision

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