How to fix garbled text in AI-generated product images

If the words on an AI-generated product photo come out misspelled, doubled or melted into gibberish, the cause is almost always the same: the model redrew the label instead of reusing your photo. This page explains why that happens, how to shoot and prompt so it happens less, and what to do with an image you have already generated that still has broken text.

Key takeaways

• General image generators redraw everything in frame, label included. They re-letter every word from what they can make out, so even clean artwork comes back wrong.
• Small, dense type fails first. A single bold word survives far more often than a six-line ingredient panel.
• Masking is a hint, not a lock. Edits can extend past the selection; always compare the whole image to the source.
• Three fixes, in rising reliability: regenerate and pick, retype the line in place with a text editor that keeps the font, or composite the approved artwork back in.
• The prevention is a workflow choice: use tools that composite your product pixels and generate only the surroundings, so the label is never redrawn.

Why AI garbles the text in product images

A text-to-image or image-to-image model does not paste your photo into a new scene. It generates a new image guided by your upload, and everything in frame, your label included, is reconstructed from scratch. The model has to guess at letterforms it can only partly read, and it is trained to produce plausible-looking text, not your exact text. That is the whole mechanism behind garbled labels.

Why small and dense type fails more. The smaller or more crowded the lettering, the less visual information per character the model has to work from. A bold product name on a clean panel survives generation often; six lines of 6-point ingredients almost never do. If your product has a logo and fine print, expect the fine print to break first.

Why this matters on a listing. A changed size code, dosage, price or slogan misrepresents the product. Amazon's image rules require images to represent the product accurately, and TikTok Shop's AI-image policy says generated images must not change the product's features or attributes; a garbled label fails both before a buyer even complains.

Before you generate: shoot and prompt so text survives

Photograph the label flat-on, in focus and large in frame. Avoid glare, motion blur, folds across the artwork and heavy compression; they strip the detail the model needs to read the words. If the source is soft, reshoot or get the approved artwork file. No prompt fixes an unreadable source.

Transcribe the text in the prompt. Put the exact wording in quotation marks, line by line, and say the label and logo must stay unchanged: Keep the label text exactly as shown: "COLD BREW · 12 FL OZ". Do not alter, redraw or re-letter the logo or label. This improves the odds on short text; it does not rescue dense or small print, because the redraw behaviour is still in play.

Change one thing per generation and compare against the source before the next request. An error you keep editing on top of becomes the starting point for the next error.

Or avoid the redraw altogether. Tools built for product photos work the other way round: the product is cut out and locked, and only the scene, the model or the shadow is generated. PicBarn's AI product photography and virtual try-on tools never regenerate the product pixels, so the label is the label you photographed. That is the prevention; the fixes below are for images made elsewhere.

Fixing an image that already has garbled text

1. Regenerate and compare. Text errors are random from run to run. For short, simple copy (a product name, a size, a single price) a batch of two to four runs often contains a clean one. Lowest effort; useless for dense panels the model cannot parse at all.

2. Retype the line in place. For a headline, a callout, a date or a short label line, use an editor that detects the text and renders the replacement in the original font, colour and texture. PicBarn's edit text in photo tool does this: Analyze numbers every line, you type the correct words for the broken one, and the engine repaints only that line (2 credits per image, 5 free credits on sign-up). A compare slider shows nothing else moved. This is the fix for garbled AI signs, posters and packaging mock-ups where the design is right and the letters are wrong.

3. Rebuild from the approved artwork. For text physically printed on the product where accuracy is non-negotiable (ingredient panels, legal lines, dosage, certification marks, logos), composite the real artwork or a close-up of the real label over the generated image in a layer-based editor, transform it to the package's perspective, mask and blend. Slower, but the only method that guarantees the wording because no model spells anything.

Masking does not lock the rest of the image

Selecting or masking an area in a general editor does not guarantee the rest stays put; edits can extend beyond the selection. Treat the mask as a hint and compare the full export against the source, not only the region you meant to change. (A text editor that repaints a single detected line is the narrow exception, and the compare slider exists precisely so you can check.)

A decision rule under time pressure

• Short generic copy on a clean background: regenerate a batch, pick the best.
• Headline or callout not printed on the physical product: retype in place; do not fight the generator with more prompts.
• Text printed on the product (labels, logos, legal copy): rebuild from approved artwork; re-prompting does not change the redraw behaviour that caused it.

The more exact the wording must be, and the more it is printed on the product, the less you should rely on re-prompting.

Verify before publishing

Read every word and number on the final export, including spacing and line breaks, and compare against the real product or the approved artwork. For Amazon A+ panels and infographics, check each panel individually; PicBarn's Amazon infographic images tool renders exact text (1 credit per image), and the words still need a human read before upload. Keep the main image a real photo of the product on white on every marketplace.

FAQ

Why does AI generate garbled text in product images? Because the model redraws the whole product from a reference rather than copying it, and re-letters the words from what it can read. Small or dense text gives it the least to work with.

How do I fix garbled text in an image I already made? Short text: regenerate and pick. Headlines and callouts: retype the line in place with a font-matching text editor. Printed labels and legal text: composite the real artwork back in.

How do I prevent garbled letters in the first place? Shoot the label flat and sharp, transcribe the wording in the prompt, change one thing per run, or use a tool that composites your product pixels instead of redrawing them.

Does masking protect the label? Not reliably in a general editor. Compare the whole image after every edit.

What should I check before publishing a corrected image? Every word and number against the real product, plus the marketplace rules: accurate representation on Amazon, no changed attributes under TikTok Shop's AI-image policy.

Sources

• Amazon Seller Central, Product image requirements: images must accurately represent the product.
• TikTok Shop Seller University, AI-generated content requirements for product listing images: generated images must not change product features or attributes.