SDXL Inpainting

byStability AI & fal.ai

Swap objects, reimagine backdrops, and refine photographic compositions with seamless lighting and texture integration

SDXL Inpainting

How SDXL Inpainting works

Modify isolated regions without disturbing the surrounding composition, photographic grain, or native resolution.

Upload source canvas

Upload source canvas

Provide a clear native-resolution image in JPEG, PNG, or WebP format as your base canvas.

Brush target mask

Brush target mask

Paint a soft-feathered mask slightly beyond the target object to capture ambient shadows and edge transitions.

Prompt new elements

Prompt new elements

Describe the replacement object or environment adjustment while configuring denoising strength and guidance.

What SDXL Inpainting is good at

High-resolution spatial awareness, realistic light matching, and accelerated inference designed for targeted visual edits.

Seamless Shadow and Light Matching

Seamless Shadow and Light Matching

Calculates surrounding light vectors, ambient occlusion, and color temperatures to cast natural shadows across newly synthesized elements.

Dual-Prompt Spatial Coherence

Dual-Prompt Spatial Coherence

Dual-text encoder conditioning ensures complex material descriptions translate accurately into the masked bounding area without bleeding.

Native 1024px High-Fidelity Synthesis

Native 1024px High-Fidelity Synthesis

Generates crisp high-frequency textures natively at 1024x1024 resolution, avoiding blurriness and pixelation along boundary edges.

Granular Denoising Strength Control

Granular Denoising Strength Control

Adjust the strength parameter from subtle cosmetic touch-ups to total thematic replacement while keeping unmasked content pixel-intact.

Made with SDXL Inpainting

A gallery of selective object swaps, wardrobe alterations, and backdrop transformations rendered directly inside masked bounds.

Product wardrobe replacement with sharp cast shadows

Product wardrobe replacement with sharp cast shadows

Wardrobe alteration within cinematic environment

Wardrobe alteration within cinematic environment

Conceptual prop synthesis against dark void

Conceptual prop synthesis against dark void

Furniture replacement in staged interior

Furniture replacement in staged interior

Prop and tabletop detail enhancement

Prop and tabletop detail enhancement

What people build with SDXL Inpainting

Commercial designers, retouchers, and art directors refining photographic assets and staging new concepts in seconds.

Fashion Stylists & Lookbook Directors

01

Swap garment silhouettes, test colorways, and switch textiles across entire seasonal lookbooks without organizing costly reshoots.

E-Commerce Merchants & Catalog Producers

02

Clean up unwanted background elements, stage products into contextual lifestyle scenes, and update packaging variants at scale.

Brand Art Directors & Concept Artists

03

Rapidly iterate on hero props, background moods, and marketing assets during pitch and client review cycles.

Architects & Interior Visualizers

04

Populate empty architectural renderings with bespoke furniture, lighting fixtures, and decorative art pieces tailored to client briefs.

Filmmakers & VFX Compositors

05

Paint out visual blemishes, replace modern set dressing with period-accurate props, and alter background skies in cinematic key frames.

Frequently Asked Questions

SDXL inpainting is best suited for replacing specific objects, swapping clothing and wardrobe pieces, changing background scenery, and fixing visual flaws within native 1024x1024 images. Because it leverages the high-resolution SDXL architecture, it preserves the lighting direction, photographic grain, and color palette of surrounding unmasked pixels to ensure natural blending.

Use a high-contrast binary mask where white defines the region to regenerate and black preserves existing pixels, with slightly feathered edges along the boundary. Inpainting an area slightly larger than the target object allows the model to properly blend contact shadows and ambient light reflections into the surrounding image.

The model struggles with rendering crisp, high-resolution text, preserving minute micro-textures at very low strength settings, and executing detailed edits on tiny regions under 512 pixels without prior upscaling. For best results, use clean high-resolution inputs and focus on photographic or illustrative subjects.

The image strength parameter controls how much of the original image data is modified, where higher values replace the masked pixels entirely based on the prompt while lower values retain more underlying structural information. Guidance scale dictates how strictly the model adheres to your text prompt, with a default setting of 7.5 providing a balanced alignment.

Try SDXL Inpainting on Fuser

Swap objects, reimagine backdrops, and refine photographic compositions with seamless lighting and texture integration