> For the complete documentation index, see [llms.txt](https://docs.sizebay.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sizebay.com/virtual-try-on/product-page-identification.md). # Product Page Identification Sizebay's Virtual Try-On does not maintain an internal product database. Instead, the VTR dynamically reads and interprets elements directly from your store's product page to generate each simulation in real time. This means no manual product registration is required — as long as the right elements are present and readable on the page, the VTR will work automatically. **Page Elements** The following elements are captured from the product page and used to generate accurate simulations: * **Product Image** — The primary image used to render the garment on the shopper's photo. For best results, make sure the product has a front-facing photo with good resolution and consistent positioning within the image carousel. Images that are cropped, angled, or vary in position across products may affect the quality of the simulation. * **Product Title** — Used to identify and contextualize the garment. * **Product Description** — Provides additional context about the product's fit, fabric, and style. * **Product Category** — Helps the VTR apply the correct simulation model for each garment type. * **Product Gender** — Ensures the simulation is rendered with the appropriate body reference. * **Product Age Group** — Used to apply the correct fit and body proportions (e.g., adult vs. children's sizing). The presence and accuracy of these elements directly impact the fidelity of the generated simulations. Incomplete or missing information may result in lower-quality or incorrect outputs. **Element Detection** Sizebay automatically inspects your product pages and captures these elements without any manual input from your team. However, if our system encounters difficulty identifying one or more elements — due to non-standard page structures, custom themes, or dynamic content loading — our team will reach out to request clarification or additional configuration from your side. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.sizebay.com/virtual-try-on/product-page-identification.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.