ESRGAN
stable-diffusion
ESRGAN | stable-diffusion | |
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21 | 382 | |
5,707 | 65,504 | |
- | 1.1% | |
0.0 | 0.0 | |
over 1 year ago | 21 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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ESRGAN
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Upscayl - Free and Open Source AI Image Upscaler for Linux, Mac and Windows
This seems to be based on ESRGAN which is supposed to be higher quality than waifu2x.
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How can I change the parameters of ESRGAN
I downloaded https://github.com/xinntao/ESRGAN , I run it using command line, no gui.
- Finetuning a x2 Real-ESRGAN model?
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The Golden Gator re-imagined by AI (Read comment before watching on stream)
Nerd info: Uses 3 different algorithms together: https://github.com/CompVis/stable-diffusion For generating source https://github.com/TencentARC/GFPGAN For repairing faces, mouths, eyes https://github.com/xinntao/ESRGAN For upscaling Paint.Net for manual retouching, cleanup and adjustments.
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[D] Has anyone tried GAN "tricks" on VAEs?
Code for https://arxiv.org/abs/1809.00219 found: https://github.com/xinntao/ESRGAN
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How to convert a low resolution, pixelated image into a high resolution picture 馃挮
Even if it's not a simple black and white image, you can get damn impressive results when upscaling images with GAN-based algorithms, like ESRGAN, together with a suitable pretrained model. Both are free of charge. The software can be tricky to use compared to Photoshop, though.
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Ambriel Motion Graphics Experiment
I use ESRGAN: https://github.com/xinntao/ESRGAN
- Some architectural stuff I鈥檝e been working on.
- children playing in the rain at night illuminated by lanterns, reflective puddles, fine detail, by Leonid Afremov
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Paper: "A-ESRGAN: Training Real-World Blind Super-Resolution with Attention U-Net Discriminators", Wei et al 2021. "Main idea: Introduce attention U-net into the field of blind real world image super resolution. We aims to provide a super resolution method with sharper result and less distortion."
There are two Generator architectures that are in the code, however these are actually just sitting there unused, likely from work that did not pan out because if you look at their inference code it's not used at all. Instead they directly import the plain old vanilla RRDB architecture from BasicSR yet again another Xinntao repository. Seeing the theme here.
stable-diffusion
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Go is bigger than crab!
Which is a 1-click install of Stable Diffusion with an alternative web interface. You can choose a different approach but this one is pretty simple and I am new to this stuff.
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Why & How to check Invisible Watermark
an invisible watermarking of the outputs, to help viewers identify the images as machine-generated.
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How to create an Image generating AI?
It sounds like you just want to set up Stable Diffusion to run locally. I don't think your computer's specs will be able to do it. You need a graphics card with a decent amount of VRAM. Stable diffusion is in Python as is almost every AI open source project I've seen. If you can get your hands on a system with an Nvidia RTX card with as much VRAM as possible, you're in business. I have an RTX 3060 with 12 gigs of VRAM and I can run stable diffusion and a whole variety of open source LLMs as well as other projects like face swap, Roop, tortoise TTS, sadtalker, etc...
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Two video cards...one dedicated to Stable Diffusion...the other for everything else on my PC?
Use specific GPU on multi GPU systems 路 Issue #87 路 CompVis/stable-diffusion 路 GitHub
- Automatic1111 - Multiple GPUs
- Ist Google inzwischen einfach unbrauchbar?
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Why are people so against compensation for artists?
I dealt with this in one of my posts. At least SD 1.1 till 1.5 are all trained on a batch size of 2048. The version pretty much everyone uses (1.5) is first pretrained at a resolution of 256x256 for 237K steps on laion2B-en, at the end of those training steps it will have seen roughly 500M images in laion2B-en. After that it is pre-trained for 194K steps on laion-high-resolution at a resolution of 512x512, which is a subset of 170M images from laion5B. Finally it is trained for 1.110K steps on LAION aesthetic v2 5+. This is easily verified by taking a glance at the model card of SD 1.5. Though that one doesn't specify for part of the training exactly which aesthetic set was used for part of the training, for that you have to look at the CompVis github repo. Thus at the end of it all both the most recent images and the majority of images will have come from LAION aesthetic v2 5+ (seeing every image approx 4 times). Realistically a lot of the weights obtained from pretraining on 2B will have been lost, and only provided a good starting point for the weights.
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Is SDXL really open-source?
stable diffusion 路 CompVis/stable-diffusion@2ff270f 路 GitHub
- I want to ask the AI to draw me as a Pokemon anime character then draw six of Pokemon of my choice next to me. What are my best free, 15$ or under and 30$ or under choices?
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how can i create my own ai image model
Here for example --> https://github.com/CompVis/stable-diffusion
What are some alternatives?
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
realsr-ncnn-vulkan - RealSR super resolution implemented with ncnn library
Waifu2x-Extension-GUI - Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.
diffusers-uncensored - Uncensored fork of diffusers
video2x - A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR. Started in Hack the Valley II, 2018.
diffusers - 馃 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
waifu2x-ncnn-vulkan - waifu2x converter ncnn version, runs fast on intel / amd / nvidia / apple-silicon GPU with vulkan
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
onnx - Open standard for machine learning interoperability