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Anyone know of open models useful (and good quality) for going the other way? I.e., Input is a 800x600 jpg and output is 4k version.
[0] https://huggingface.co/docs/diffusers/api/pipelines/stable_d...
Anyone know of open models useful (and good quality) for going the other way? I.e., Input is a 800x600 jpg and output is 4k version.
Make sure to test the models before you deploy. Nothing will be lossless doing superresolution but flows can get you lossless in compression.
How do we know we don't get hands with 16 fingers?
https://pub.towardsai.net/stable-diffusion-based-image-compr...
HN discussion: https://news.ycombinator.com/item?id=32907494
Anyone know of open models useful (and good quality) for going the other way? I.e., Input is a 800x600 jpg and output is 4k version.
Look for SuperResolution. These models will typically come as a GAN, Normalizing Flow (or Score, NODE), or more recently Diffusion (or SNODE) (or some combination!). The one you want will depend on your computational resources, how lossy you are willing to be, and your image domain (if you're unwilling to tune). Real time (>60fps) is typically going to be a GAN or flow. Make sure to test the models before you deploy.…
Earlier quoted context omitted.
Did JPEG2000 really flounder? If your concept of it being a consumer facing product as a direct replacement for JPEG, then I could see being unsuccessful in that respect. However, JPEG2000 has found its place in the professional side of things.
Yes, I do mean broad- rather than niche adoption. I myself used J2K to archive film scans. One problem is that without broad adoption, support even in niche cases is precarious; the ecosystem is smaller. That makes the codec not safe for archiving, only for distribution. The strongest use case I see for this is streaming video, where the demand for compression is highest.
Anyone know of open models useful (and good quality) for going the other way? I.e., Input is a 800x600 jpg and output is 4k version.
However, this weekend someone released an open-source version which has a similar output. (https://replicate.com/philipp1337x/clarity-upscaler)
I'd recommend trying it. It takes a few tries to get the correct input parameters, and I've noticed anything approaching 4× scale tends to add unwanted hallucinations.
For example, I had a picture of a bear I made with Midjourney. At a scale of 2×, it looked great. At a scale of 4×, it adds bear faces into the fur. It also tends to turn human faces into completely different people if they start too small.
When it works, though, it really works. The detail it adds can be incredibly realistic.
Example bear images:
1. The original from Midjourney: https://i.imgur.com/HNlofCw.jpeg
2. Upscaled 2×: https://i.imgur.com/wvcG6j3.jpeg
3. Upscaled 4×: https://i.imgur.com/Et9Gfgj.jpeg
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The same person also released a lower-level version with more parameters to tinker with. (https://replicate.com/philipp1337x/multidiffusion-upscaler)
Earlier quoted context omitted.
But that's like saying it's difficult to drive your Formula 1 car to work every day. It's not meant for that, so it's not the car's fault. It's a niche thing built to satisfy the requirements of a niche need. I would suggest this is "you're holding it wrong" type of situations that isn't laughable.
There was absolutely an initiative to make J2K a widespread standard
Anyone know of open models useful (and good quality) for going the other way? I.e., Input is a 800x600 jpg and output is 4k version.
