stability-sdk VS stylegan2-projecting-images

I use stable diffusion via stability.ai.

SDXL 0.9 is now available on the Clipdrop by Stability AI platform. Stability AI API and DreamStudio customers will be able to access the model this Monday, 26th June as well as other leading image generating tools like NightCafe.

And for your imaging purposes, you might explore things such as the new StableStudio that Stability AI has. Here's an article about StableStudio. Here are imaging things you can do in StableStudio via its API.

I know there are tons are programs out there but I've made some really cool stuff with this free one https://beta.dreamstudio.ai then rotoscoped it onto a green screen then animated it

Currently Midjourney is the best one, but you need to pay. For low to no cost you could use https://app.leonardo.ai/ or https://beta.dreamstudio.ai/

https://beta.dreamstudio.ai/ (belaj bildoj)

> Of course new SD models are also on the horizon…

SDXL is available at https://beta.dreamstudio.ai/ though they say they're going to release more variants.

I think ControlNet is a lot more interesting than just "better tuned models"; it means there's no line between creating something yourself and asking an AI to do it anymore.

(this is actually generated using the new sdxl beta model in https://beta.dreamstudio.ai )

A Colab notebook.

To play with the dataset, we first must create a Jupyter notebook, a powerful and popular tool among data engineers. I created mine on Google Colab.

Please head over to the Google Colab

But regardless of what you want to do, you'll probably use Python. In this context, a good way to work with Python is using Jupyter Notebooks. So you should start with installing Python and Jupyter and go from there. If you want to get started without installing anything, Google Colab gives you a remote Jupyter Notebook which runs in the browser for free.

访问 Google Colab 。

Remember school days when you'd share notes with classmates? Jupyter takes that spirit and amplifies it. Once you've crafted your Notebook, you can share it with peers, collaborators, and the world. Platforms like GitHub and Google's Colab natively render Jupyter Notebooks. It's like penning an open letter to the world but in a delightful mix of code, text, and visuals.

Open your web browser and navigate to Google Colab.

Using Google Colab you can develop Python codes, similar to Jupyter Notebooks. You will have an environment prepared with various Python libraries. In addition you have tips on small codes for development, some tutorials, gihub connection, cloud -saved notebooks and more.