case.01
Listing photos
Use a prompt image editor to change a product detail, prop, or surface area without regenerating the entire listing image.
AI Image Inpainting
Inpainting session
Masked area
Repainted image
Drag to compare
node.02 / seo-content
An inpainting for real creative work.
Linocut AI turns a single inpaint image task into part of a complete creative workspace. Start with one direct action, inspect the result, then keep the output connected to image, video, audio, text, and workflow nodes.
- inpainting.01
Upload an image and use the inpainting brush to mark the exact area for a local AI edit, such as an object, surface, outfit, or background patch.
- inpainting.02
Write what should appear inside the selected area with prompt image editor language, such as replace the masked dog with a cat or change the shirt to denim.
- inpainting.03
AI fill uses the prompt and surrounding image context to regenerate the marked area while the unmasked image stays stable.
[ 02 / sequence ]
How inpainting works
01
Upload a source image
Add the image that contains a region you want to replace, redraw, or improve with masked photo repair.
02
Mask the region
Use AI image inpainting mask mode and brush size controls to select the exact area while keeping the rest of the image locked.
03
Generate the replacement
Describe the new detail, choose the output format, run the AI fill pass, and review the local edit.
[ 04 / capabilities ]
What the inpainting improves
feat.01
Source image
Start AI image inpainting from a product photo, portrait, concept image, or creator asset that needs one selected region changed.
feat.02
Mask selection
Turn on mask mode, adjust brush size, paint the target area, and clear the mask when the local AI edit selection needs another pass.
feat.03
Prompt instruction
Tell the prompt image editor what should appear inside the mask, from object replacement to texture repair or detail changes.
feat.04
Region generation
Generate only the masked region, export WEBP, PNG, or JPG, and keep the AI fill result ready for enhancement or upscaling.
[ 05 / workflows ]
Inpainting use cases
Use AI image inpainting to brush one region, describe the replacement, and generate a local AI edit without rebuilding the whole image.
case.02
Campaign stills
Use AI fill for targeted campaign variations while keeping the wider composition stable for faster creative tests.
case.03
Portfolio images
Apply masked photo repair to a selected object, outfit, or background patch inside presentation imagery without rebuilding the scene.
case.04
Creator posts
Inpaint image details for faster social variants, adding or replacing small elements while preserving the original frame.
[ 06 / template ]
Why inpainting works best as a controlled local edit
The value of masked photo repair is changing one selected region without losing the rest of the image. Linocut AI keeps the mask, prompt, and review state visible together.
Locked source context
rule.01Preserve the unmasked image while an inpaint image pass replaces a product detail, outfit, prop, surface, or background patch.
Prompted replacement detail
rule.02Describe the new element with enough prompt image editor context to match lighting, material, scale, and surrounding texture.
Local edit handoff
rule.03Use the local AI edit as a stronger source for enhancement, style transfer, upscaling, or final export.
speed
privacy
edge
api
pipeline / secure-core
[ 07 / faq ]
Inpainting FAQ
Yes. Mask the object you want to change, then describe the replacement in the prompt, such as replacing a dog with a cat. AI fill redraws the selected area from that instruction.
Upload an image, mark the area that should change, enter a prompt for what should appear there, and inpaint image content where only the marked region is rewritten.
The intended workflow is local. The prompt controls the masked region, while the unmasked part of the image should remain stable aside from natural edge blending.
Use the brush control in the right panel, adjust brush size, and paint only the region that needs masked photo repair. Clear the mask if the selection is too broad.
Describe the replacement clearly, including object, material, color, style, and lighting cues. Short prompts work when the prompt image editor can read enough surrounding context.
Yes. Masked photo repair can rebuild a selected patch, cover a gap, repair a surface, or fill missing detail when the mask and prompt describe the intended result.
The interface supports WEBP, PNG, and JPG output settings, so the local AI edit result can fit web previews, transparent workflows, or flattened delivery files.
Yes. Mask the background area, describe the new texture or scene detail, and keep the subject unmasked so the inpaint image change stays controlled.
Use a mask that covers the full area you want changed plus a small edge margin. Very tiny masks can limit blend quality, while overly large masks may change more content.
Yes. The inpainted result can continue into image enhancement, upscaling, background removal, style transfer, or export variants inside the image workflow.
[ 08 / adjacent-nodes ]
Continue the image workflow
[ 09 / next-step ]
Run inpainting in the workspace.
Start with one direct task, then keep editing, generating, writing, and shipping from the same Linocut AI canvas.