CogVideo
stable-diffusion
CogVideo | stable-diffusion | |
---|---|---|
39 | 383 | |
3,512 | 65,739 | |
1.6% | 1.5% | |
2.4 | 0.0 | |
11 months ago | 5 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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CogVideo
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InstructPix2Pix Video: "Turn the wave into trash"
Additionally two open source demo models [CogVideo[(https://github.com/THUDM/CogVideo) by a groups of cs students a model by [Antonia Antonova](https://antonia.space/text-to-video-generation) and have presented their own innovative methods of generating video from text
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Effortpost: The Future Of Media Synthesis and AI Art
The second thing that will happen is the appearance of AI video and audio. Google has shown two programs for video generation, one which is fairly high quality and the other which can make long videos with several scenes. Meta has also demonstrated their own. We've already seen other projects like CogVideo, as well as many others that are currently being worked on. It's likely that these techniques will become so refined that over the next year or two, they'll have a similar boom to image generation programs. And eventually, they'll have a similar application in video editing, once coherence is adequate enough. Select a person's shirt, and it stays that for the remainder of the scene. Change an actor's hairstyle in real time, or add characters that didn't exist into a scene and let the computer figure out the desired level of realism. This'll revolutionize VFX to a degree where making an effects heavy will be less about wrangling complex toolsets and more about making aesthetic choices of style and placement.
- AI Content Generation, Part 1: Machine Learning Basics
- Can we please make a general update on all the "most important" news/repos available?
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Stable Diffusion Public Release – Stability.ai
Check out https://github.com/THUDM/CogVideo - progress is being made on coherent video generation.
Characters and dialogue are effectively solved, just look at GPT-3.
The entity behind StableDiffusion is also supporting generative music art, so let's see what is coming out of that: https://www.harmonai.org/
We are currently far away from generating a production quality movie with AI, but I don't think it's going to be nearly as long as a lifetime. In my opinion, we'll have high quality AI shorts within the decade.
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How far away are we from have AI like DALL-E 2 be able to create other media like 3d models or video?
CogVideo and a CogView web app.
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Does training transformers on large corpuses of music files have some hidden difficulty which makes it impossible?
A better comparison to AI music generation would be video generation, which has not improved much since i saw first examples some years ago. The last iteration is stuff like CogVideo and this is only able to generate 4 second videos with mid-strong artifacts.
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[R] CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers + Gradio Web Demo
github: https://github.com/THUDM/CogVideo
- CogVideo: Code and 94B Model for Text-to-Video Generation via Transformers
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CogVideo (text-to-video) model, code, and demo are available
GitHub repo.
stable-diffusion
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Top 7 Text-to-Image Generative AI Models
Stable Diffusion: It is based on a kind of diffusion model called a latent diffusion model, which is trained to remove noise from images in an iterative process. It is one of the first text-to-image models that can run on consumer hardware and has its code and model weights publicly available.
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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?
What are some alternatives?
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
dalle-playground - A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini)
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
diffusers-uncensored - Uncensored fork of diffusers
stable-diffusion-webui-feature-showcase - Feature showcase for stable-diffusion-webui
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
imagen-pytorch - Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
NUWA - A unified 3D Transformer Pipeline for visual synthesis
onnx - Open standard for machine learning interoperability