GREAT Outpainting with ControlNet!

In this introduction, the presenter explains how to expand images using Control Net with the in-painting model. He starts with an image of a fantasy island and shows how to load it into the Control Net interface, enabling in-painting preprocessing. The key step is setting the resize mode to 'resize and fill' rather than just 'resize,' to avoid stretching or cropping the image. The presenter begins by expanding the image vertically, adjusting parameters like the Euler A sampler to DPM++ 2M Keras, using 20 steps, and maintaining default settings for negative and digital oil painting styles. He highlights the importance of selecting the right resizing mode to avoid image distortion.

Here, the focus shifts to horizontal expansion, with the same settings applied. As the image expands, new details like clouds, water, and rocks appear. The presenter acknowledges that expanding from a small image (512x512) results in less detail. To improve, he suggests transferring the expanded image to the 'image-to-image' section, where more details can be added using styles like 'Fantasy Island' and adjusting denoising strength between 0.4 and 0.6. The difference between low and high denoising strength is demonstrated, with higher values introducing more changes and details to the image, such as altering the castle and bridge slightly.

This section provides a trick for improving sharpness and detail in the image by using an external tool like photop.com. By applying a filter called 'unsharp mask' with specific settings, the presenter sharpens the image slightly, which can then be used as input for the 'image-to-image' process. He shows how sharpening the image before re-rendering results in more contrast and clarity in fine details, particularly visible in terrain and water. The presenter compares the initial and improved versions side-by-side, emphasizing how these small changes can enhance the overall quality of the expanded image.

Shifting focus to human portraits, the presenter explains how the same workflow can be applied to generate and expand images of people. He demonstrates this with a series of generated female portraits, selecting one with a hat for expansion. Using Control Net and the same settings (resize and fill), he first expands vertically and then horizontally, noting that it's necessary to expand one direction at a time to avoid stretching. This method generates new parts of the image seamlessly, adding to the portrait while maintaining the original composition.

In this final instructional part, the presenter answers potential questions about expanding images in multiple directions at once. He explains why his preferred workflow involves expanding one axis at a time and encourages viewers to explore alternative methods, such as 'Poor Man's Outpainting.' He shows examples of two expanded portrait images, discussing minor imperfections in one but ultimately being satisfied with the results. He wraps up by suggesting that users be mindful of prompts when outpainting to ensure the best results and invites viewers to share better workflows in the comments.

In the conclusion, the presenter thanks viewers for watching and encourages them to like and subscribe to the channel if they found the tutorial helpful. He maintains a lighthearted tone, stating that viewers are free to do as they please. The video closes with a warm goodbye, leaving the audience with the option to apply these techniques in their own image-editing workflows.