Image to Image AI

If the task depends on shape, select an image with a clear silhouette and limited occlusion. If it depends on material, use a source where texture and reflections are visible. If composition matters, avoid a crop that hides the spatial relationship you want to preserve. A reference cannot reliably communicate information it does not clearly show.

Remove unrelated borders, screenshots, captions, and interface elements when they are not part of the desired output. A cleaner source reduces ambiguity. The upload control accepts JPEG, PNG, and WebP images, but a supported format does not make a low-resolution, heavily compressed, or obstructed source suitable for transformation.

When the task begins with a cut-out subject, use the AI Background Remover first if background isolation is the actual requirement. Then use the resulting asset as part of a separate creative transformation, rather than asking one prompt to perform two different jobs at once.

• Identity priority: face shape, hairstyle, distinctive garment, object silhouette, logo placement, or another cue that makes the subject recognizable.
• Composition priority: camera angle, subject position, foreground-background relationship, horizon, or negative space that should remain.
• Color and material priority: a limited palette, surface texture, finish, or lighting response that should survive the change.
• Flexibility statement: explain what may change freely. Giving the model a clear area of freedom can reduce accidental changes to the protected area.

For an environment change, name the place, time, weather, lighting source, and visual relationship to the subject. For a material change, identify the new surface and how it behaves under light. For a composition change, state the crop, viewpoint, subject position, and amount of surrounding context.

Useful wording often pairs a stable clause with a target clause: “Preserve the bicycle frame geometry and side view; replace the workshop with a clean outdoor service area in overcast daylight.” The two halves create a direct review checklist.

Avoid asking for several unrelated transformations in the first attempt. Changing identity, pose, camera, environment, material, season, and graphic treatment at once makes both preservation and diagnosis harder. Establish the most important change first, then build on a result that already holds the anchor.

• Subject reference: supplies the person, object, or silhouette that should remain recognizable.
• Composition reference: supplies camera angle, spatial arrangement, or framing without necessarily supplying the subject identity.
• Material or palette reference: supplies surface treatment, color relationships, or lighting character.
• Conflict check: remove a reference when it contradicts another image on viewpoint, identity, palette, or layout and the prompt does not establish which one has priority.

• The source identity drifts: shorten the change request, list the defining cues first, use a clearer reference, and avoid changing pose, camera, and environment simultaneously.
• The composition drifts: state the camera angle and subject placement explicitly, choose an output ratio compatible with the source layout, and remove requests that imply a different frame.
• The result barely changes: describe the destination with specific environment, lighting, material, palette, or crop language instead of saying “more different.”
• The wrong reference dominates: assign roles in the prompt, reduce the number of inputs, or select a model whose visible reference capacity fits the task without unnecessary images.
• Small details or text become unreliable: simplify the transformation, enlarge the key element in the frame, and verify critical lettering or precision details in an appropriate downstream editor.
• The task cannot submit: confirm that at least one reference and a prompt are present, complete any sign-in requirement, and read the interface’s credit or concurrency feedback before trying again.