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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
For automating the creation of large batches of AI-generated artwork locally.
| Date | Stars |
|---|---|
| 2026-07-24 | 621 |
| 2026-07-25 | 621 |
| 2026-07-28 | 621 |
| 2026-07-30 | 621 |
| 2026-08-06 | 621 |
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# 2022-09-28 Update: Just a note that I've launched [Dream Factory](https://github.com/rbbrdckybk/dream-factory), a significant upgrade to this. It's got an (optional) GUI, true simultaneous multi-GPU support, an integrated gallery with full EXIF metadata support, and many other new [features](https://github.com/rbbrdckybk/dream-factory#features). I dropped VQGAN and Disco Diffusion support to focus on Stable Diffusion, so if you want VQGAN and/or Disco Diffusion you should stick with this for now. Otherwise I encourage everyone to migrate to Dream Factory! I'll continue to patch bug fixes on this repo but I likely won't be adding new features going foward. # AI Art Generator For automating the creation of large batches of AI-generated artwork locally. Put your GPU(s) to work cranking out AI-generated artwork 24/7 with the ability to automate large prompt queues combining user-selected subjects, styles/artists, and more! More info on which models are available after the sample pics. Some example images that I've created via this process (these are cherry-picked and sharpened): <img src="/samples/sample01.jpg" width="367" height="220" alt="sample image 1" title="sample image 1"> <img src="/samples/sample02.jpg" width="220" height="220" alt="sample image 2" title="sample image 2"> <img src="/samples/sample03.jpg" width="220" height="220" alt="sample image 3" title="sample image 3"> <img src="/samples/sample04.jpg" width="220" height="220" alt="sample image 4" title="sample image 4"> <img src="/samples/sample05.jpg" width="220" height="220" alt="sample image 5" title="sample image 5"> <img src="/samples/sample06.jpg" width="367" height="220" alt="sample image 6" title="sample image 6"> Note that I did not create or train the models used in this project, nor was I involved in the original coding. I've simply modified the original colab versions so they'll run locally and added some support for automation. Models currently supported, with links to their original implementations: * [Stable Diffusion](https://github.com/CompVis/stable-diffusion) * CLIP-guided Diffusion (via [Disco Diffusion](https://colab.research.google.com/github/alembics/disco-diffusion/blob/main/Disco_Diffusion.ipynb) adapted to run locally) * [VQGAN+CLIP](https://colab.research.google.com/github/justinjohn0306/VQGAN-CLIP/blob/main/VQGAN%2BCLIP(Updated).ipynb) # Requirements You'll need an Nvidia GPU, preferably with a decent amount of VRAM. 12GB of VRAM is sufficient for 512x512 output images depending on model and settings, and 8GB should be enough for 384x384 (8GB should be considered a reasonable minimum!). To generate 1024x1024 images, you'll need ~24GB of VRAM or more. Generating small images and then upscaling via [ESRGAN](https://github.com/xinntao/Real-ESRGAN) or some other package provides very good results as well. It should be possible to run on an AMD GPU, but you'll need to be on Linux to install the ROCm version of Pytorch. I don't have an AMD GPU to throw into a Linux machine so I haven't tested this myself. # Setup These instructions were tested on a Windows 10 desktop with an Nvidia 3080 Ti GPU (12GB VRAM), and also on an Ubuntu Server 20.04.3 system with an old Nvidia Tesla M40 GPU (24GB VRAM). **[1]** Install [Anaconda](https://www.anaconda.com/products/individual), open the root terminal, and create a new environment (and activate it): ``` conda create --name ai-art python=3.9 conda activate ai-art ``` **[2]** Install Pytorch: ``` conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch ``` Note that you can customize your Pytorch installation by using [the online tool located here](https://pytorch.org/get-started/locally/). **[3]** Install other required Python packages: ``` conda install -c anaconda git urllib3 pip install transformers keyboard pillow ftfy regex tqdm omegaconf pytorch-lightning IPython kornia imageio imageio-ffmpeg einops torch_optimizer ``` **[4]** Clone this repository and switch to it
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:950f24ff044a313a, topic:stable-diffusion, topic:image-generation, topic:generative-art