Hello trend,
This is Satya Mallick from LearnOpenCV.com.
Stable Diffusion models and their variations are great for generating novel images. But most of the time, we do not have much control over the generated images. Img2Img lets us control the style to an extent, but the pose and structure of objects may differ greatly in the final image. To mitigate this issue and get more control, you can use ControlNet.
Let's jump into this short video tutorial on ControlNet:
ControlNet is a new way of conditioning input images and prompts for image generation. It allows us to control the final image generation through various techniques like pose, edge detection, depth maps, and many more. If you prefer to read the article, you can jump directly into the article.
| ControlNet – Controlling Stable Diffusion |
The accompanying code for the blog post can be found here:
| Download Code |
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Cheers,
Satya
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