stable-diffusion
Real-ESRGAN
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stable-diffusion | Real-ESRGAN | |
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382 | 131 | |
65,243 | 25,886 | |
1.7% | - | |
0.0 | 0.0 | |
5 days ago | 6 days ago | |
Jupyter Notebook | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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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 · Issue #87 · CompVis/stable-diffusion · 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 · CompVis/stable-diffusion@2ff270f · 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
Real-ESRGAN
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AI-Powered Nvidia RTX Video HDR Transforms Standard Video into HDR Video
It's not exactly what you're after, as it's anime specific and you need to process the video yourself (eg disassemble to frames, run the upscaler, then assemble back to a movie file), but Real-ESRGAN is really good:
https://github.com/xinntao/Real-ESRGAN/
It's pretty brilliant for cleaning up very old, low resolution anime.
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Photorealistic Video Generation with Diffusion Models
Just a note you can run upscaling on your home desktop with Real-ESRGAN:
- What software to use for upscaling anime edits
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What neural net for SISR?
Maybe Real-ESRGAN is a good fit? Even tho it's a couple of years old
- Cant make concurrent calls to Model
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Outis my beloved
I'm glad you noticed! I upscaled the icon from the wiki using Real-ESRGAN's 4xplus anime model, then photoshopped out the text. Worked far better than waifu2x.
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ComicMerge (Beta testing version - SafeTensors)
A: Try using High-res Fix and R-ESRGAN 4x+ Anime6B as upscaler
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Is there any way to upscale local files permanently using Nvidia's RT VSR?
Maybe try this one https://github.com/xinntao/Real-ESRGAN it may work even better.
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YOASOBI Idol [3840 x 2160]
Screenshotted from the official music video, upscaled to 4k using a state of the art ML model.
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Compilation of (almost) all end of chapter panels
Do you happen to remember which chapter has that "scene"? You could also try to enhance it yourself, I did it using Real-ESRGAN, which is really easy to use.
What are some alternatives?
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
ESRGAN - ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.
diffusers-uncensored - Uncensored fork of diffusers
SwinIR - SwinIR: Image Restoration Using Swin Transformer (official repository)
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
BSRGAN - Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (ICCV, 2021) (PyTorch) - We released the training code!
onnx - Open standard for machine learning interoperability
waifu2x - Image Super-Resolution for Anime-Style Art
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
Real-ESRGAN-colab - A Real-ESRGAN model trained on a custom dataset