Article by Warren Woodhouse
When you ask to remove an item (like a red arrow or another object or item), the system identifies the specific object's boundaries, colours and coordinates to create a pixel accurate mask over the region to be erased.
The model analyses the pixels surrounding the masked area to understand the underlying visual structure, such as the direction of the wood grain on the tree trunk, the thickness of sketch lines on the architectural drawing or the lighting and shading of the background.
Rather than just stretching adjacent pixels or applying a simple blur, a generative diffusion model predicts what should exist behind the object. Drawing from patterns learned during training, it synthesises new textures and features that match the style of the original image.
The generated area is blended seamlessly with the original image, matching noise, grain, tone and line thickness so no harsh seams or artefacts remain.
No comments:
Post a Comment