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Are the images deleted after x days? Do you keep to train again? What rights (if any) are you claiming once I use it?
Finally all the CSI and detective shows are believable again: ENHANCE!!!
Not as good yet (at least in this case): * original: https://upcdn.io/12a1z2u/image/uploads/2024/07/18/4kU68cBDKF... * "10K" enhanced: https://replicate.delivery/czjl/gFpKKIlEKKZrL1lfqxXlpQrOBbe9...
Also:
12000 pixels is a 110 x 110 image.
12000 x 12000 would be 144 megapixels.
Not as good yet (at least in this case): * original: https://upcdn.io/12a1z2u/image/uploads/2024/07/18/4kU68cBDKF... * "10K" enhanced: https://replicate.delivery/czjl/gFpKKIlEKKZrL1lfqxXlpQrOBbe9...
The original contains artifacts that tend to arise after compression, as the other poster notes (posterization and such). I wonder if you'll get better results if you make the original go through a gaussian to smooth those artifacts, and then feed it to the enhancer.
Earlier quoted context omitted.
These enhance effects typically use guesswork. That would be useful to gain hints, but not to know for sure what the original looked like.
Unless the rest of the image offers details that the human observer would ignore but the AI would pick up. E.g. low res photo from 1828 of a US president - enhance to John Quincy Adams. Surprisingly there's a daguerreotype of John Quincy Adams from 1843[1], the AI could use that; perhaps "enhance" the time backwards a bit, to make him 15 years younger. [1]: https://en.m.wikipedia.org/wiki/File:John_Quincy_Adams_-_cop…
Earlier quoted context omitted.
The original contains artifacts that tend to arise after compression, as the other poster notes (posterization and such). I wonder if you'll get better results if you make the original go through a gaussian to smooth those artifacts, and then feed it to the enhancer.
Wouldn't that effectively just be losing input resolution?
But that's what's needed here. The current image contains a lot of compression artifacts, which are extraneous information, and that's what the upscaler seems to want to enhance. Wipe that information out and you're left with the rough structure, which is what we actually want enhanced.
Earlier quoted context omitted.
The original contains artifacts that tend to arise after compression, as the other poster notes (posterization and such). I wonder if you'll get better results if you make the original go through a gaussian to smooth those artifacts, and then feed it to the enhancer.
Wouldn't that effectively just be losing input resolution?
Really interested in this, but it needs additional login options. Not a Google user myself but would like to check this out.