My desire was to combine something like iNaturalist with BirdWeather for a bird tracker of audio and visual. BirdWeather does make it free which is great, but there's no great free API of iNaturalist quality for diverse bird tracking.

That being said, I am certain that if iNaturaist made their model public, tons of competitive apps would spring up and it'd be commercialized regardless of license immediately and would take people away from iNaturalist without giving iNaturalist anything in return.

Plus I know iNaturalist has issues with that they don't want autolabeled data uploaded as matched. They only want manually labeled data, which opening the API I'm sure would flood their server with ML labeled data. Which on the one hand, could be useful, but also a ton of noise.

I'm in favor of whatever option is most in line with keeping a long term success of a free, high quality plant/animal identifying app out there, and I don't know enough to take a definitive stance on that, and unfortunately those that do, probably have a vested interest in one of the outcomes.

https://www.nytimes.com/2022/08/01/business/dealbook/pornhub...

https://arstechnica.com/tech-policy/2022/08/california-court...

>This week, US District Judge Cormac Carney of the US District Court of the Central District of California decided that there's reason to believe that Visa knowingly processed payments that allowed MindGeek to monetize "a substantial amount of child porn." To decide, the court wants to know much more about Visa's involvement, calling for more evidence of legal harms caused during a jurisdictional discovery process extended through December 30, 2022.

According to Court Listener, the case is still ongoing - https://www.courtlistener.com/docket/59992265/serena-fleites...

                  Overall | Handwritten | Typed
  Google Vision:    98.80%  | 93.29%      | 99.37%
  Amazon Texttract: 98.80%  | 95.37%      | 99.15%
  surya:            97.41%  | 87.16%      | 98.48%
  azure:            96.09%  | 92.83%      | 96.46%
  trocr:            95.92%  | 79.04%      | 97.65%
  paddleocr:        92.96%  | 52.16%      | 97.23%
  tesseract:        92.38%  | 42.56%      | 97.59%
  nougat:           92.37%  | 89.25%      | 92.77%
  easy_ocr:         89.91%  | 35.13%      | 95.62%
  keras_ocr:        89.7%   | 41.34%      | 94.71%

Overall, of you want the best, if you're an enterprise, just use whatever AWS/GCP/Azure you're on, if you're an individual, pick between those. While some of the Open Source solutions do quite well, surya took 188 seconds to process 88 pages on my RTX 3080, while the cloud ones were a few seconds to upload the docs and download them all. But if you do want open source, seriously consider surya, tesseract, and nougat depending on your needs. Surya is the best overall, while nougat was pretty good at handwriting. Tesseract is just blazingly fast, from 121-200 seconds depending on using the tessdata-fast or best, but that's CPU based and it's trivially parallelizeable, and on my 5950X using all the cores, took only 10 seconds to run through all 88 pages.

But really, you need to generate some of your own sample test data/examples and run them through the models to see what's best. Given frankly how little this paper tested, I really should redo my study, add VLMs, and write a small blog/paper, been meaning to for years now.