Upload a reference, say what should stay and what should change, and use Image to Image AI to create a controlled visual variation.
Image to Image AI addresses the main reasons people search for an AI image editor: product background replacement, photo-to-art style transfer, sketch-to-image rendering, and consistent character variations. The source supplies structure or identity while the instruction defines the transformation.
Use Image to Image AI as an AI product background changer while keeping the product silhouette, camera angle, label geometry, and important details recognizable. Turn a plain catalog shot into a botanical campaign, seasonal promotion, lifestyle setting, or premium studio variation. This helps ecommerce and brand teams turn one catalog asset into multiple campaign directions before arranging another shoot.
Transform a portrait, landscape, or object photo into editorial illustration, anime, watercolor, cinematic photography, 3D rendering, or another art direction. A restrained style transfer can preserve expression, hairstyle, pose, composition, and lighting while changing the medium. If no source image needs to be preserved, Text to Image AI is the cleaner blank-canvas workflow.
Use a drawing, wireframe, storyboard panel, room sketch, or packaging outline to anchor layout, proportions, perspective, and object placement. Then describe the materials, lighting, atmosphere, and rendering style required for the next stage. This sketch-to-image workflow is useful for interiors, architecture, product visualization, game art, and client presentations where the original composition should remain readable.
Generate a new season, location, outfit, expression, or campaign scene while asking Image to Image AI to retain the same facial features, hairstyle, proportions, illustration language, and signature accessories. Multiple references can provide separate identity, wardrobe, and style anchors. GPT Image 2 and Nano Banana 2 support multi-reference workflows for developing a recognizable character across new creative directions.
The reference upload is required, GPT Image 2 is selected automatically, and the first generation uses practical ratio and resolution defaults.
Start with a clear source image. Add more references only when each contributes a specific subject, product, material, scene, or style direction.
Name the composition, identity, geometry, or style cues to preserve, then describe the new background, object, material, lighting, or medium.
Review the credit estimate, create the result, compare it with the references, and simplify the prompt if too many details drifted.
It is useful whenever an existing picture already solves part of the brief and recreating its composition, subject, or product from words would waste time.
Create product backgrounds, seasonal visuals, color variations, lifestyle scenes, and advertising concepts from existing assets.
Explore character versions, portrait styles, comic scenes, thumbnails, covers, and visual storytelling directions.
Move sketches, mood boards, interior photos, packaging concepts, and material studies toward a more finished presentation.
Produce alternate art directions and market-specific campaign concepts without rebuilding every composition from scratch.
Use GPT Image 2 with up to 16 references or compare Nano Banana models with different cost, ratio, resolution, and reference limits inside one workspace.
Combine a main source with additional subject, material, product, or style references when one picture cannot communicate the whole brief.
Compare GPT Image 2 and Nano Banana options without moving assets and prompts between disconnected products.
Supported models include common social, portrait, landscape, square, panoramic, and up-to-4K output settings.
The generation cost appears before submission and responds to the current model and output settings.
Use text-to-image for a blank-canvas idea, image-to-video for motion, or a dedicated model page when you want to compare capabilities.
Create a new visual from words without a required image.
Animate the finished variation as a short video.
Review the default model and its reference capacity.
Compare broad ratios, multi-reference input, and 4K output.
Try a lower-cost route for drafts and quick iterations.
Use several assets to guide a new video shot.
Upload a clear reference, state what should stay, describe one meaningful change, and review the credit estimate before generating.
