Flux ArtCross-border product-image localization should separate text extraction, terminology approval, base-image editing, target-language layout, and release review. Start with representative images on the GPT Image 2 model page, but have people verify numbers, currencies, model numbers, capacities, and regulatory text. One-click translation is not the same as release-ready content.
Layout drift is usually several problems at once
When the source is a flat image rather than editable text layers, localization must handle OCR, translation, removal of old text, background repair, and layout reconstruction. Thai, Vietnamese, Indonesian, and English differ in length and line breaking. Forcing translated copy into the original box can shrink type, break hierarchy, or squeeze price information.
| Risk level | Typical content | Release rule |
|---|---|---|
| Blocking | Model number, capacity, quantity, currency, price, date, regulatory or warning text | Match approved product records item by item or do not publish |
| High | Core claims, scope of use, guarantee language | Confirm against a termbase and review in the local language |
| General | Decorative copy and mood lines | Wording may adapt without changing product facts |
| Layout | Type size, line count, alignment, whitespace, and safe areas | Recompose for the target language instead of copying source line breaks |
Build one master, then derive each marketplace language
- Create a source-copy table. Give every string a field name, source text, target language, character limit, risk level, and review status.
- Extract text from the image and reconcile it with the source-copy table. OCR helps discover text; it is not the sole authority for product facts.
- Produce a clean image without promotional copy. Lock the product, logo, original packaging text, dimension marks, and graphics that must remain.
- Create separate Shopee and Lazada language versions. Preserve reading hierarchy and safe areas first, then adjust type size and line breaks.
- A native-language reviewer or someone familiar with the local marketplace checks terminology, numbers, currencies, and tone. Scale by SKU only after approval.
The correct role for GPT Image 2
OpenAI describes GPT Image 2 as an image model for fast, high-quality image generation and editing, with flexible image sizes and high-fidelity image inputs. This page therefore uses it for base-image and local edits; it does not claim that the model replaces translation review or marketplace compliance decisions. Source checked August 20, 2026.
Flux Art provides a unified workspace, model switching, asset management, and OpenAPI. Model capabilities come from their respective providers. Flux Art does not verify product specifications, translation accuracy, or current Shopee and Lazada policies for the team. Check live model availability, plans, credits, and API fields in the website and console on the publication date.
Six checks required before batching
- Every SKU, marketplace, and language maps correctly; no file from another product or country is written back.
- Model number, capacity, quantity, price, currency, and date match approved product records.
- Logos, original packaging text, and certification marks were not rewritten without evidence.
- Target-language line breaks, type size, alignment, and safe areas remain readable without forcing the source line count.
- The base image, source copy, translation, review record, and final asset are traceable.
- A responsible owner checks current marketplace rules and local law on the release date; this article does not replace official policy.
Related pages and verified sources
For the complete translation, QA, and video coordination process, continue with the cross-border image translation and shoppable-video workflow.
OpenAI: GPT Image 2 model page (checked August 20, 2026)
OpenAI: Introducing ChatGPT Images 2.0 (checked August 20, 2026)