ControlNet Stable Diffusion – Create Realistic Images in Seconds

ControlNet Stable Diffusion model that allows you to manage the composition and pose of generated images by replicating them from a reference image.

Seasoned Stable Diffusion users understand how difficult it is to generate the exact composition you desire. The photographs are somewhat random. You can only play the number game: Create a vast number of images and choose your favorite.

This post will teach you how to build realistic images using ControlNet stable diffusion.

What is ControlNet Stable Diffusion?

ControlNet Stable Diffusion gives you unparalleled fine-grained control over the images you generate. ControlNet adds an additional level of control by allowing users to input extra information into the model, such as text prompts or visuals. The supplied data may alter the structure, appearance, and content of the resultant image. This model is based on Stable Diffusion, a diffusion model used to create high-quality photographs.

Create Images with ControlNet Stable Diffusion

  • ControlNet Stable Diffusion has several advantages over other AI image generating algorithms. It gives users unprecedented control over the resulting image. This is due to the fact that ControlNet employs a number of strategies to understand the relationship between the input data and the intended output image.
  • ControlNet is extremely stable. This means that it is less likely to produce unclear or distorted images.
  • ControlNet is extremely fast, which means you can generate graphics very quickly.
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Controlnet Stable Diffusion
ControlNet Stable Diffusion – Create Realistic Images in Seconds 1

There are a variety of models in ControlNet, including Canny Edge, Hough, HED, Scribble, Interactive Scribbles, Fake Scribble, Human Pose, Segmentation, Depth, and Normal Maps. Let’s try one by one with unique images and prompts.

To create images in this models, you just have to upload an image that you want to recreate and add a prompt below the uploaded image.

Canny Edge ControlNet Model

When using the Canny Edge ControlNet model, only the pose of the dog remains the same in the final outputs, while the environment, weather, Color, and time keep changing.

Prompt: “cute dog”

Controlnet Stable Diffusion
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Other ControlNet models also create images in the same way. Let’s see the example with prompts.

M-LSD Lines ControlNet Stable Diffusion Model

This M-LSD Lines Model uses simple M-LSD straight line detection to create images.

Prompt: “Building”

Controlnet Stable Diffusion
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HED Boundary ControlNet Model

This model uses the soft HED Boundary, it will preserve many details in input images to create amazing images.

Prompt: “oil painting of handsome old man, masterpiece”

Controlnet Stable Diffusion
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Scribbles Maps ControlNet Model

In this model, you have to draw a scribble of a hot air balloon and upload it as an input image to get stunning output images.

Prompt: “Hot air balloon”

Controlnet Stable Diffusion
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Interactive Scribbles ControlNet Stable Diffusion Model

With the Interactive Scribbles model, you can use the “Open Drawing Canvas” option to draw your own creation and upload it as an input image. And you can adjust the canvas width and height.

Prompt: “dog in a room”

Controlnet Stable Diffusion
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Fake Scribbles ControlNet Model

When using this fake scribble, you can just upload the input image instead of drawing scribbles. This script uses the exact same scribble-based model but uses a simple algorithm to synthesize scribbles from input images.

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Prompt: “bag”

Controlnet Stable Diffusion
ControlNet Stable Diffusion – Create Realistic Images in Seconds 7

Human Pose ControlNet Model

This Human Pose ControlNet model directly manipulates the pose skeleton. You need to input an image, and then it will detect the pose for you.

Prompt: “Chef in the kitchen”

Controlnet Stable Diffusion
ControlNet Stable Diffusion – Create Realistic Images in Seconds 8

Semantic Segmentation ControlNet Model

With the semantic segmentation model, you can directly draw the segmentations. You need to input an image, and then a model called Uniformer will detect the segmentations for you.

Prompt: “River”

Controlnet Stable Diffusion
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Depth Control ControlNet Model

ControlNet receive the full 512×512 depth map, rather than 64×64 depth. Depth ControlNet model use 64×64 depth maps. This means that the ControlNet will preserve more details in the depth map.

Prompt: “Stormtrooper’s lecture”

Controlnet Stable Diffusion
ControlNet Stable Diffusion – Create Realistic Images in Seconds 10

Normal Map ControlNet Model

This model uses a normal map to find how many areas are in the background with an identity normal to the viewer. Tune the “normal background threshold” to get a feeling.

Prompt: “Cute toy”

Controlnet Stable Diffusion
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Non-Prompt Mode

You can get some really interesting results by adjusting the parameters, as seen below: Also read Stable Diffusion web UI: A Comprehensive Guide

Controlnet Stable Diffusion
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Conclusion

Overall, ControlNet is a strong tool that allows Stable Diffusion users to have complete control over the appearance and composition of their generated images. ControlNet is an excellent option if you want to generate realistic and detailed images with Stable Diffusion.