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Fashion & AI

How to Stop AI from Scrambling Logos and Text on Clothing

Why AI garbles brand logos and slogans on t-shirts and hoodies, and four practical ways to keep them legible.

1 Nov 2026
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How to Stop AI from Scrambling Logos and Text on ClothingFashion & AI

Quick answer: AI scrambles logos because it draws letters as shapes, not text. To keep them legible: use the real garment photo as a reference, keep the logo large and facing the camera, choose poses with little fabric folding, and add the final logo in a separate edit step or layer it on afterwards for hero images.

Why letters break

Image models predict shapes. A wordmark on a folded chest is a hard shape to predict, so letters merge or get invented. Newer models are better at text, but folds and angles still cause errors.

Four ways to keep logos clean

  1. Reference: always attach a clear photo of the actual garment with the logo.
  2. Framing: front-facing, chest-up shots keep the logo flat and readable.
  3. Edit pass: generate the shot, then run a targeted edit that only fixes the logo area.
  4. Overlay: for hero campaign images, place the real logo artwork in design software and match light and folds.

Prompt to copy

Keep the garment exactly as in the reference, including the logo. The logo text must read exactly: "[BRAND]". Front-facing, chest-up framing, fabric smooth across the chest, soft even light. Do not change letters, spacing or colours of the logo.

Common mistakes

  • Expecting perfect small text in full-body shots.
  • Generating 50 variations instead of doing one clean edit.
  • Not proofreading every letter.

Where to do this in the Lab

Related

FAQ

Why does AI mess up text on shirts?

It draws letters as shapes, and folds make those shapes hard to predict.

Which shots keep logos readable?

Front-facing, chest-up shots with smooth fabric.

Can I fix only the logo?

Yes, a targeted edit on the logo area works better than regenerating.

Is it OK to add the logo manually?

Yes. For hero images it is the most reliable option.

Next step: learn the whole workflow in a recorded workshop (see all workshops) or save with a bundle.

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