ohjauskuvia

Ohjauskuvia, often translated as "control images" or "guide images," are a concept primarily used in the field of digital image processing and computer graphics, particularly in the context of generative models like diffusion models. Their purpose is to guide the image generation process, allowing for more precise control over the output compared to unconditional generation. Instead of a model generating an image solely based on random noise and its learned distribution of images, ohjauskuvia provide additional information or constraints.

These control images can take various forms, depending on the specific application and the type of control desired. Common examples include edge maps, depth maps, segmentation masks, or even sketches. By incorporating these ohjauskuvia into the diffusion process, the model is conditioned to produce an image that adheres to the structural, semantic, or spatial information provided by the control image. For instance, an edge map might guide the generation of an image with sharp outlines matching the provided edges, while a depth map could influence the perceived three-dimensionality of the generated scene.

The integration of ohjauskuvia significantly enhances the controllability and interpretability of generative models. It enables users to steer the creative process, generating images that are not only aesthetically pleasing but also align with specific desired attributes. This has opened up new possibilities in areas like image editing, content creation, and scene reconstruction, where precise control over the generated output is paramount. The effectiveness of ohjauskuvia lies in their ability to provide a structured framework for the otherwise stochastic nature of generative processes.