AI product photos for small e-commerce shops
A clean listing photo without a studio, a light box or a photographer.
SamImageGenerator ·
A small shop rarely has a studio, and the difference between a photo that sells and one that does not is usually the background, the light and the clutter — not the camera. All three are fixable from a phone photo, which makes a generator a practical tool rather than a novelty here.
Photograph the product, generate the rest
The product itself must be a real photograph. Shape, colour, texture and finish are what the buyer is paying for, and a generated version of them is a misrepresentation. Everything around the product — the backdrop, the surface, the room, the seasonal scene in the banner — is fair to generate or replace.
| Asset | Route |
|---|---|
| Marketplace listing image | Phone photo, background replaced with plain white |
| Lifestyle shot | Same photo, moved into a described scene |
| Category or campaign banner | Generated from text, product placed on top |
| Social variants | Regenerated at 1:1 and 9:16 |
The clean-up routine
Mark the background and write "plain white seamless backdrop, soft even light, subtle contact shadow under the product". Then mark distractions — reflections, a cable, a sticker — and write "remove". Finish with colour: "correct the white balance, keep the product colour accurate". Three passes, three credits, and the photo belongs in a shop.
The contact shadow is the detail people skip and the one that separates a real photo from a cut-out. Without it the product floats, and every marketplace listing that floats looks like a placeholder.
Scaling past a handful of products
At twenty products this is a pleasant afternoon; at two thousand it is a script. The API takes the same photo and the same instruction and returns the finished image, so a catalogue runs through the routine unattended. The step-by-step version for a single photo is in product photo cleanup.