Master the Art of Stable Diffusion with Houdini and WebUI
Table of Contents
- Introduction
- Connecting Stable Fusion with Houdini
- The Lazy Way: Using Automatic 1111's Web UI
- Setting Up Houdini for Stable Diffusion
- Writing Image Data into a Volume
- The Main Program: Controlling the Web UI
- Extracting and Converting the Image
- Visualizing the Image in Houdini
- Bringing the Image into COPs
- Conclusion
Introduction
In this article, we will explore how to connect Stable Fusion with Houdini to Create dynamic and visually stunning effects. We will discuss different methods of integration and focus on the "lazy" approach using Automatic 1111's Web UI. By remotely controlling the Web UI, we can easily generate and import image data into Houdini for further manipulation. Get ready to unleash your creativity and take your visual effects to the next level.
Connecting Stable Fusion with Houdini
One of the exciting aspects of working with Stable Fusion is its architecture and the promise it holds for creative experimentation. To harness the power of Stable Fusion within Houdini, there are various approaches we can take. The intelligent method involves convincing Houdini to load the Hugging Face's Diffuse library and implementing a Stable Fusion workflow in a Python node. However, for those who prefer a more effortless process, we can use Automatic 1111's Web UI and its API to control Stable Fusion remotely from within Houdini. This lazy approach is now more feasible than ever, thanks to the amazing capabilities of the Web UI.
The Lazy Way: Using Automatic 1111's Web UI
To utilize Automatic 1111's Web UI for controlling Stable Fusion, we need to first install the Web UI user Package. With the Web UI user package installed, we can enable API access by adding a command line parameter to the Web UI user file. By accessing the Web UI's API features, we can remotely control Stable Fusion from inside Houdini with just a few lines of code. Additionally, we can use the Web UI to HAND over the data generated by Stable Fusion into Houdini for further manipulation.
Setting Up Houdini for Stable Diffusion
Before we dive into the integration process, we need to ensure that Houdini is properly configured to work with Stable Diffusion. To represent a 2D image in Houdini, we have two options: using a plane or a volume. In this case, we will utilize a 2D volume as it offers more flexibility. We can set up a vector volume within the volume SOP and specify the resolution, Dimensions, and Channel properties. Additionally, we will need to install and import several libraries and set up a function to write image data into the volume.
Writing Image Data into a Volume
To write image data into the volume, we will define a Python function called "image2volume" which takes an image and the volume channels as inputs. The function converts the image into a numpy array, flips it if necessary, splits it into red, green, and Blue channels, remaps the channel values, and writes them into the respective volume channels. This function allows us to efficiently write out the image data into the Houdini volume.
The Main Program: Controlling the Web UI
Now that we have set up Houdini and defined the necessary functions, we can focus on the main program. The main program involves specifying the parameters for the Web UI, connecting to the Web UI server, and triggering the image generation process. We will construct a payload containing the required parameters such as prompt, negative prompt, seed, steps, CFG Scale, width, Height, and sampler index. Using the requests library, we will send a post request to the Web UI server and receive the generated data as a response.
Extracting and Converting the Image
After receiving the response from the Web UI, we need to extract the image data and convert it into a format that can be processed by Houdini. By extracting the JSON format and decoding the image data using the base64 library, we can obtain the image in a byte STRING format. We will then use the PIL library to open the image and convert it into an object that Houdini can work with.
Visualizing the Image in Houdini
To Visualize the generated image within Houdini, we will utilize a volume visualization node. By configuring the node's parameters, such as density and diffuse field, we can render the image in the Houdini viewport. This visualization allows us to preview the image and make any necessary adjustments before further processing.
Bringing the Image into COPs
To further work with the image and Apply compositing techniques, we will bring the image into Houdini's Compositing Network (COPs). By adding a Sub Import node and connecting it to the COP Network, we can import the image and begin manipulating it using a wide range of COP nodes and tools. This integration between Stable Fusion, Houdini, and COPs unlocks countless creative possibilities for visual effects artists.
Conclusion
In this article, we covered the process of connecting Stable Fusion with Houdini through Automatic 1111's Web UI. We explored the lazy approach of using the Web UI to remotely control Stable Fusion and import the generated image data into Houdini. By leveraging the power of Houdini's Python scripting capabilities and the flexibility of Stable Fusion, artists can push the boundaries of visual effects and create stunning, dynamic imagery.