AI t-shirt product photography for print-on-demand & merch

Amazon expects a minimum of 1000 px on the longest edge, on a pure white background, with the product filling around 85% of the frame. Myntra is the outlier: it wants 1080 x 1440 in a 3:4 portrait frame rather than a square. That difference matters, because centre-cropping a portrait shot down to a square usually removes the model's head and feet, so generate each ratio rather than re-cropping one master file.

Because the garment edge and the backdrop are the same value, so the silhouette disappears and marketplace reviewers see a shapeless blob. White and pale tees need deliberate edge separation, usually a soft drop shadow or gentle side lighting that keeps the shoulder and sleeve lines readable while the background still reads as pure white. It is the single hardest case in t-shirt photography and the most common reason a plain white listing image looks cheap.

Placement, scale and colour are preserved from the source artwork. The thing to check on any on-model output is drape distortion: as fabric falls across the chest, a print can stretch or skew at the edges. Review the graphic's straight lines and any text in the artwork before you publish, since that is where distortion shows first.

Flat-lay is fastest and fine as a secondary angle. Ghost mannequin shows the garment holding its shape without a person, which suits catalogue grids. On-model is what sells fit, and Myntra requires a model shot for apparel listings outright. Most listings want a clean primary plus two or three of the others.

Yes. Reuse the same model, pose, and scene so your storefront stays visually consistent across dozens of variants.

Yes. It is built for high-SKU catalogs where shooting every design individually is not practical.