aiTransformer

          Being a culinary enthusiast, I aimed to create a portrait of a chef in a sophisticated kitchen through photography. I used aiTransformer Super Stylizer , which is based on Stable Diffusion, a powerful deep learning, text-to-image model. While Stable Diffusion is generally effective, it occasionally produces distorted or surreal images of human faces or limbs. The distortion happens because Stable diffusion is a generative model that produces realistic images by gradually adding noise to a starting image over a series of steps. This process can produce images with realistic textures and details, but it can also introduce distortions to the image.       For a new project,  I usually begin with a straightforward representation of the image I envision. This simplistic approach aids in establishing a solid foundation to build upon. If the outcome doesn't meet my expectations, I then introduce more detailed descriptions to the prompt. Usually, with a few attempts—sometimes soo

          In the Super Stylizer tool, we can stylize an image with images generated from a text prompt (using Stable Diffusion img2img). The resulting images might have the style  transferred   relatively well, but you have to use a proper style with appropriate style strength, and it's not easy to find a good match. For example, suppose you want to style a portrait of a person with  Renaissance art, using a weaker style strength (say 20%) you'll get results resembling the portrait but not much  Renaissance  style,  using  a stronger style strength (say 80%) you'll get results in somewhat  Renaissance  style  but very much deviating from the original portrait. In fact, in this case no matter what  style strength to use  you may never get a  realistic looking result, i.e. a portrait looks like a  Renaissance  painting.  the original portrait and results of  img2img  with   style strength 20%, 50% and 80% for the same seed  543955       ControlNet is a neural network struct