41–50 of 62 posts
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If you want to provide good upscaling results you need to use a latent scaler but these are compute intensive so the easier way is to just blow it through a gan like here.
What are some examples of latent scaler upsamplers?
upscale wiki is really the place to explore everything image scaling:
Your automatic italian localization is incredibly bad. Examples: "Stiamo usando un fork dell'immaginazione per alimentare la nostra intelligenza artificiale, e il nostro progetto è sviluppato con Django per il sito web." -> "We are using a fork of imagination for feeding our artificial intelligence, and our project is developed with Django for the website". "Migliora le tue foto, cartoni animati, immagini e più facil…
It wasn so much that the output ChatGPT / Google created was wrong, but that it used wrong type of language for the context. For example speaking using very basic/common words no real person would use in a business document. MS translation service was really good in this regard, only making mistakes on genders of people in the translated text (too small context window?).
I guess it's fine if it's free or cheap. But why would I pay anywhere from $29-232 per month for what is basically a glorified web UI wrapping open source models? I can get the same or superior functionality for free from FOSS running on my local machine, including mobile devices. https://www.upscayl.org/ https://superimage.io/
Why would you? No idea. But there's obviously a huge market for slapping an easy-to-use interface + hosting onto something available for free.
Your automatic italian localization is incredibly bad. Examples: "Stiamo usando un fork dell'immaginazione per alimentare la nostra intelligenza artificiale, e il nostro progetto è sviluppato con Django per il sito web." -> "We are using a fork of imagination for feeding our artificial intelligence, and our project is developed with Django for the website". "Migliora le tue foto, cartoni animati, immagini e più facil…
Not the Op, but I have recently been working on applying "state of the art" AI for translations into languages other than English and I was pretty disappointed with rather mediocre results from Chatgpt, normal gpt and Google translate API. As it is, just running fairseq M2M100 locally (even just on a cpu) gave me significantly better results for English->Polish translation. And I was properly amazed by the quality of…
I haven't tested it yet, but I suggest that you have a "per image" price for those who use it sporadically. I could be a potential user, but not for 24/m for the 50 images I can do per month.
I haven't tested it yet, but I suggest that you have a "per image" price for those who use it sporadically. I could be a potential user, but not for 24/m for the 50 images I can do per month.
That's a great idea for pricing logic, I'll put it live, I might even be able to create bundles, something like 10-image packs, and you just keep adding more and more if you need.
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So? They both use bootstrap and they're made by the same people with the same contact information and company name and everything.
Is it the same people though? The Github link is different.
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So? They both use bootstrap and they're made by the same people with the same contact information and company name and everything.
Is it the same people though? The Github link is different.
Do you not see the "VPS.org LLC" and "Contact us" links on the bottom that I see?
Gigapixel AI works fantastic ( https://www.topazlabs.com/gigapixel-ai ) and has a perpetual license.