Strictly retain the identity of what matters โ switch backgrounds, swap apparel textures, or regenerate scenes with photorealistic coherence and seamless boundary blending.
Use the client-side interactive sandbox or switch to the native ModelScope cloud engine below.
Drag the interactive slider horizontally to compare original inputs against photorealistic AI inpainting outputs.
Traditional inpainting damages edges and distorts face structures. ReplaceAnything solves this via multi-scale identity injection.
The target area is locked with pixel-level mathematical precision. Human faces, delicate jewelry, or trademark brand shapes will not shift by even a single millimeter.
The diffusion model automatically detects incident light directions, cast reflections, and color ambient bounce, harmonizing foreground and synthesized background.
Eliminate costly product photoshoot crews. Take one photo with a smartphone, swap into 50 global commercial backdrops, and ready your listings for Amazon or Shopify.
Copy-paste these golden prompt templates to achieve studio-grade outputs on your first try.
Conventional inpainting models often suffer from identity driftโwhen you ask to change a background, the model subtly alters the person's face, hair, or product silhouette. ReplaceAnything employs a dual-stream architecture with an identity-locking mechanism, guaranteeing 100% boundary fidelity for the masked region.
Yes, this web version and the underlying ModelScope space are open to the public for testing, research, and non-commercial exploration.
Yes. Outputs you synthesize with your own source products belong entirely to you. Many Amazon and Shopify sellers use this workflow to create lifestyle product scenes without renting physical studio space.
The core engine operates natively up to 1024x1024 / 2048x2048 with an integrated neural super-resolution upscaler to output crystal-clear 4K commercial graphics.