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Create from a visual starting point
Image to image AI
Image to image AI starts with a picture and generates a new interpretation from your instructions. Use a source photograph for the broad composition, then describe the change you want. If you add references, explain whether each one supplies a color palette, material, or visual style so competing images do not muddy the brief.
Your original stays separate · Review the price before generating
Basic edits are free. AI images start at 10 credits with these settings. Review the price on the canvas before generating.
Before you start
Use image to image AI when a source picture communicates more than text alone. Upload the main image, define the desired transformation, and give any references distinct roles. Expect a generated interpretation rather than a pixel-perfect copy; check geometry, identity, text, and other details that matter.
Decide what the source must contribute
A source image can anchor the arrangement of a room, the pose of a person, or the shape of a rough concept. Before generating, choose which of those properties matters most. A brief that asks to preserve everything while changing the whole style contains a conflict the model must resolve.
For example, a room photograph can establish the camera angle while a separate image suggests a warmer palette. That is a different task from reproducing the second room. Write the role of the source in a sentence you could use to judge the result afterward.
For image to image AI, keep a short acceptance note: which property must survive and which may change. That note prevents a polished but unsuitable output from replacing the actual brief.
Give references separate jobs
Image to image AI becomes easier to direct when each reference contributes one clear thing. Call the first picture the composition source and the second the color reference. If a third image shows a surface finish, explain that it supplies material appearance rather than object placement.
Avoid assuming that the system knows which image is authoritative. Two photos with different poses or perspectives can pull the result in opposite directions. Reduce the set when the brief becomes difficult to explain. More references are useful only when their roles make the desired outcome less ambiguous.
| Reference role | Describe its contribution | Check for unwanted influence |
|---|---|---|
| Composition | Keep the camera angle and broad arrangement | Unrequested objects copied into the scene |
| Palette | Borrow warm neutrals and muted green accents | Subject shape changes along with color |
| Material | Use the appearance of matte ceramic | Reference object replaces the original subject |
| Illustration treatment | Use broad lines and limited shading | Important identifying details disappear |
Build an image to image AI request
Keep a short written brief before starting. It gives you a consistent comparison standard even when the generated version is visually appealing.
Upload the main source first
Choose the clearest image of the subject or arrangement you want to carry forward. JPG, PNG, WebP, and HEIC inputs are supported up to 20 MB.
Add only useful references
Explain which image controls composition and which contributes appearance. Remove references that introduce conflicting perspectives or details you do not want reproduced.
Name the intended change
Describe the output in concrete visual language. Specify light direction, palette, material appearance, or line treatment rather than asking for a better image.
Compare against the brief
Inspect the most important preserved property first. Then check small details, including labels, faces, edges, and object counts, before choosing the version to download.
A room concept shows why priority matters
Consider an illustrative room brief: retain the sofa position and camera angle, but reinterpret the upholstery as muted green fabric and soften the wall color. The source controls layout. The written request controls the two appearance changes. That division makes the result easier to inspect.
If the generated room gains another window or moves the sofa, it has missed an important constraint even if the colors work. Return to the source and simplify the change. This example describes a workflow, not a verified before-and-after result or a guarantee of architectural accuracy.
Know which details need exact evidence
Generated interpretation is useful for concept work, but exact text, packaging, and geometry deserve separate attention. A product label can acquire incorrect letters; a chair can gain a different number of supports. Compare those details directly with the source rather than relying on an overall impression.
When exact pixels must remain intact, consider whether a free crop, resize, or format conversion already solves your task. If you only need to alter one region, a focused inpainting workflow may give you a clearer brief. Use the broad reference workflow when reinterpretation is part of the intended result.
Review from structure down to surface
Start with the silhouette and arrangement. Check the number of objects, their relative sizes, and where they overlap. Only then judge material texture, color, and lighting. A pleasing surface treatment can distract from a structural change that makes the image unsuitable.
For people, compare identity and anatomy. For products, check shape and labels against actual merchandise. For spaces, inspect doors, windows, and perspective lines. These are different review tasks, which is why a general claim of preserved details would be misleading. The acceptance standard comes from what you intend to use the image for.
Use separate variations to answer separate questions
Begin each major experiment from the original source when you want a fair comparison. Editing an already changed result can carry forward accidental details, making it harder to know which version introduced an error.
Keep the reference roles consistent across a small set of variations. If one test changes color and another changes both color and perspective, they answer different questions. There is no dedicated batch production workflow here, and repeated prompts do not guarantee identical objects across a series. Save the brief with your chosen output if another person will review the concept.
Match the output to the next decision
A first concept often needs enough detail for evaluation rather than the largest possible file. The generation options cost 10 credits for 1K, 20 for 2K, or 30 for 4K per result. Every new variation uses credits; internal retries for the same job do not add another charge.
Export PNG, JPG, or WebP after checking the image. The original remains available for comparison, and free basic edits can adjust framing or dimensions afterward. A higher output setting increases the image size but does not guarantee faithful text or recovered source detail. Keep that distinction clear when handing the concept to a client or collaborator.
Example request
Use the first image for the main composition and the second image only for its muted color palette. Create a new interpretation while preserving the main subject and broad arrangement.
Adapt the subject and details to your image. This is a starting instruction, not a sample result.
Questions about this edit
How does image to image AI differ from text generation?
A source picture provides visual context such as composition or subject appearance. Text explains what to change. A text-only request starts without that visual anchor, while this workflow asks the model to interpret an existing image.
Does image to image AI copy my source exactly?
No. The result is a generated interpretation. You can ask to preserve specific properties, but geometry, text, identity, and small objects may change. Use a direct basic edit when you need a simple transformation without generated scene content.
How many references should I use?
Use the smallest set that explains your goal clearly within the editor's available controls. One useful reference can be better than several competing images. State what each contributes rather than assuming upload order alone communicates the intended relationship.
Can I use image to image AI for exact product photos?
It can help explore concepts, but compare every result with the actual item. Labels, proportions, textures, and construction details can drift. Do not present an inaccurate generated interpretation as a faithful photograph of merchandise.
Can image to image AI restore missing detail?
It may invent plausible detail, which is different from recovering the original information. This page does not provide a dedicated restoration or upscaling workflow. Keep the source when factual accuracy matters and evaluate added detail as synthetic.
Create from a source image
Bring your image and a clear request. Choose the output settings and review the task price before generating.