Text-to-image versus editing: evaluate new composition and source fidelity separately
Compare generation from text with editing existing images, and explain why references, strength settings and masks do not replace fidelity checks.
Choose an approach
Start with text-to-image for composition exploration and editing when an existing subject or layout must be retained. Editing does not guarantee unchanged unselected regions, and references do not promise exact copying. Mark invariants and allowed changes before choosing, then assess visual quality separately from fidelity.
Text and existing images provide different constraints
OpenAI distinguishes generation from editing; Diffusers describes input images and strength controls for image-to-image work. Support depends on the model. Text specifies a scene linguistically, while editing uses existing imagery but can still change details. Check outside mask boundaries too. For exact text or existing vector edits, conventional design tools provide a baseline; generation need not redraw everything.
Test whether required invariants survive the same request
Choose one image and a precise change, such as wall color only. Preserve editing inputs and masks; use the same desired description for generation while acknowledging different source information. Check proportions and marks before scene quality. Record model versions and settings across attempts instead of inferring consistency from one selected image. Typeset exact text afterward where necessary; an accidentally correct result does not establish deterministic editing.
Choose editing or regeneration from the cause of rework
For local defects, preserve the usable version and edit the affected region. If composition is wrong, explore again and continue editing from an approved version. Keep originals and change descriptions instead of overwriting the sole source. Count regeneration and inspection, not just first-image latency. This article checks mechanisms without calling image models or measuring success rates; verify required fidelity on your own assets.
Checked sources
These sources support the concepts and methods described here. Examples and test scope are labeled separately; check the version of the tools you use.