Inpainting
Inpainting is an AI image editing technique that regenerates only a selected region of an image, letting you remove, replace or repair part of a picture while the rest stays untouched and the new content blends in seamlessly.
You mark the area to change with a mask, usually by brushing over it, and optionally describe what should appear there. The model then generates new pixels for the masked region while reading the surrounding image for context, so lighting, perspective, texture and style continue naturally across the edit boundary.
The three everyday uses are removal, replacement and repair. Remove a photobomber or a logo and the model fills in plausible background. Replace a plain shirt with a leather jacket by masking it and prompting for the new garment. Repair a damaged or awkward area, like a distorted hand in a generated image, by masking it and regenerating just that part.
Mask technique makes the difference between an invisible edit and an obvious one. Mask slightly beyond the object you are removing so no residue remains, and give the model a little surrounding context inside the mask for complex fills. If a fill looks wrong, regenerating the same mask usually yields a different candidate to choose from.
Inpainting is the reason a flawed generation rarely needs to be thrown away. Instead of re-rolling the whole image and losing what you liked, you fix the one region that is wrong. Arteza's inpaint tool provides this masking workflow in the browser.
Frequently asked questions
What is the difference between inpainting and outpainting?
Inpainting regenerates a region inside the existing image, while outpainting generates new content beyond the original borders to extend the canvas. Both fill their target area using the surrounding image as context.
Can inpainting remove objects from photos?
Yes, object removal is the most common use. You mask the object, leave the prompt empty or describe the background, and the model fills the area with plausible surroundings.
Why does my inpainted region not match the rest of the image?
Usually the mask is too tight or the prompt fights the surrounding context. Feather or enlarge the mask, describe the fill in a way consistent with the scene's lighting and style, and regenerate a few candidates.