stable-diffusion-webui
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[Bug]: Can't use most of upscalers in latest sd-webui
Is there an existing issue for this?
- [X] I have searched the existing issues and checked the recent builds/commits
What happened?
Can't use most of upscalers. Lanczos, Nearest, R-ESRGAN 4x+, these 3 upscalers are working fine. The others just crash in different ways.
Steps to reproduce the problem
- R-ESRGAN_4
URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:997)>
-
R-ESRGAN 4x+ Anime6B
AttributeError: 'NoneType' object has no attribute 'local_data_path'
-
LSDR Stuck at ...
Loading model from /Users/silver/AI/stable-diffusion-webui/models/LDSR/model.ckpt
LatentDiffusionV1: Running in eps-prediction mode
DiffusionWrapperV1 has 113.62 M params.
Keeping EMAs of 308.
Applying cross attention optimization (InvokeAI).
Down sample rate is 1 from 4 / 4 (Not downsampling)
I have two option:
- terminate the terminal and restart sd-webui
- wait for system crash and reboot automatically
- ScuNET GAN
URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:997)>
- ScuNET PSNR
URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:997)>
- SwinIR_4x Python quit unexpectedly
SwinIR tiles: 0%| | 0/35 [00:00<?, ?it/s]loc("mps_multiply"("(mpsFileLoc): /AppleInternal/Library/BuildRoots/a0876c02-1788-11ed-b9c4-96898e02b808/Library/Caches/com.apple.xbs/Sources/MetalPerformanceShadersGraph/mpsgraph/MetalPerformanceShadersGraph/Core/Files/MPSGraphUtilities.mm":219:0)): error: input types 'tensor<1x36864x480xf16>' and 'tensor<1xf32>' are not broadcast compatible
LLVM ERROR: Failed to infer result type(s).
[1] 6059 abort ./webui.sh
/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/multiprocessing/resource_tracker.py:224: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
warnings.warn('resource_tracker: There appear to be %d '
What should have happened?
Less error maybe?
Commit where the problem happens
Try to use upscalers in Extras
What platforms do you use to access the UI ?
MacOS on M1 chip.
What browsers do you use to access the UI ?
Google Chrome
Command Line Arguments
No
List of extensions
No
Console logs
Additional information
No response
Interesting. Not tried all of them, but at least Linear and R-ESRGAN x4 + ANIME v6 produce blurry images for me. Sticking to img2img for now. Shame.
i presume you downloaded upscaler .pth models of upscalers and you put them into models/esrgan , models/real-esrgan folders? for me it works from extras tab of webui1111... r-esrgan and r-esrgan_anime are VERY GOOD! I haven't do the comparison with NERO AI upscaler which is the best, but R-ESRGAN and ANIME is doing similar or even better than NERO(which is best of commercial upscalers) R-ESRGAN and ANIME is much better than TOPAZ Gigapixel AI for example...
i presume you downloaded upscaler .pth models of upscalers and you put them into models/esrgan , models/real-esrgan folders? for me it works from extras tab of webui1111... r-esrgan and r-esrgan_anime are VERY GOOD! I haven't do the comparison with NERO AI upscaler which is the best, but R-ESRGAN and ANIME is doing similar or even better than NERO(which is best of commercial upscalers) R-ESRGAN and ANIME is much better than TOPAZ Gigapixel AI for example...
Do I need to download anything? On holiday rn, but I'll bookmark this comment so when I get back on Monday I can give it a shot. Just links to any repos so I can clone thanks:)
Also, is hires. fix supposed to take a very very long time? I find it take up to 177s/it for me. I am running on AMD, Win64 but I have been trying different ways to get PyTorch to recognise my GPU, but it does not want to. I have a ryzen 5 zen2 though so it's gets about 20s/it on standard txt2img. Completely different issue, but I wasn't sure if that was fast or not, and ofc I can't use Xformers to speed it up.
hi spaceman, well it is well known that stable diffusion was meant to be used on Nvidia rtx cards, thats why i picked second hand rtx 3090 with 24gb vram... if you want to seriously use SD think about 18 - 100+gb vram nvidia card... :D no kidding
Watch this video on how to fix certificates: https://www.youtube.com/watch?v=dEBN1M609zk
Use your version,Use this command:
/Applications/Python\ 3.9/Install\ Certificates.command