Once the API is released, this will be easier to do in a programmatic fashion.
Note: Depending on how many times you do this... I could see there being a continuity problem with the extremes of the image (eg: the far left has no knowledge of the far right). An alternative could be to scale the image down and mask the borders then later scale it back up to the desired resolution.
This scale and mask strategy also works well for images where part of the scene has been clipped that you want to include (EG: Part of a character's body outside the original image dimensions). Scale the image down, then mask the border region, and provide that to the generation step.
https://apps.apple.com/us/app/waifu2x/id1286485858
I paid extra to get the higher quality model using the in-app purchase option. It crushes the phone's battery life, but runs in only ~10 seconds on an iPhone 13 Pro for a single 1000x1000 input image.
Considering waifu2x is the name of an algorithm I assumed it was just that algorithm. There's also no mention of other models on the demo page or the Github page as far as I can see.
The confusion originates from the fact that I was using a GUI project for Waifu2x called "Waifu2x Extension GUI" (https://github.com/AaronFeng753/Waifu2x-Extension-GUI) which other than Waifu2x also supports other algorithms like Real-ESRGAN, Real-CUGAN, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.
So as you said Cupscale is surely more advanced than Waifu2x (the single algorithm), but do you think it's also better than Waifu2x Extension GUI?
https://www.topazlabs.com/gigapixel-ai
No kidding.
On-demand stock photo generation probably is the next step, particularly when combined with other free media services (Unsplash immediately comes to mind). Simply choose a "look" or base image, add contextual details, and out pops a 1 of 1 stock photo at a fraction of the cost of standard licensing. It'll be very exciting seeing what new products/services will make use of the DALL-E API, how and where they integrate with other APIs, use cases, value adds like upscaling and formatting, etc.
Maybe it would be cheaper. I imagine it would one day. And maybe it would have a more liberal usage license.
At any rate, I look forward to this. And I look forward to the inevitable debates over which is better: AI generation or photographer.
And this is the first picture I got: https://labs.openai.com/s/lSWOnxbHBYQAtli9CYlZGqcZ
It got it a bit strong on the depth of field and I don’t like the angle but I could iterate a few times and get a good one.
For the first few days when it was announced I use to look deep even in real photos in search of generative artifacts. They are not so difficult to spot now, most of the times anyway.
Heck: If the cost to entry is prohibitively low they might do it at a loss and take over the site
It's very good at generating art style images. These kind of images are mostly amazing most of the times. But the Photorealistic images only work with cherry picking.
Me and you must have very different definitions of "cherry picking". For prompts that fall within it's scope (i.e not something unusually complex or obscure) I get usable results probably 90% of the time.
Can you give me some examples of prompts that you tried where you found good results difficult to obtain?
It did generate good dslr like face closeups, as good as Nvidia does, most of the times but not always. Sometimes there are weird artifacts and face does not make sense.
Dslr style blurry photos are mostly good. From the looks of images I follow, imagen is probably more believable. Don't know how much cherry picking goes on there. See this thread [1] for example. I failed to generate image like this (honey dress) in dalle2.
[1]: https://www.reddit.com/r/ImagenAI/comments/w3saku/creating_i...
Unless I'm missing something, these seem pretty darn good