Product Shots

From 3.1 credits

Turn one product photo into a full marketplace-ready shoot, white background, lifestyle, gradient studio, in-use, and outdoor variants.

Product Photo

Click to upload image

or drag and drop

Browse library

Aspect Ratio

Product Description(optional)

Still needed: Product Photo, Environments

Runs on

1 models

Google
- Nano Banana 2

How to use Product Shots

A compact decision guide for placing this pipeline in a workflow.

Best for

Amazon marketplace listings (white_background main)
Shopify and DTC catalogs
scale reference shots that reduce returns
premium ecom where texture sells the price point

Product Shots API

Call this pipeline from your own code. One request dispatches a run; the model is an input field, not a separate endpoint.

Get an API token

inputs: 4
required: 2
Pricing: from 3.1 credits

Language

TypeScript Python Go CLI

bun add @pipe2-ai/sdk

Run a pipeline

import { createClient } from "@pipe2-ai/sdk";

const client = createClient(process.env.PIPE2_TOKEN!);

const { run_pipeline } = await client.RunPipeline({
  pipeline_slug: "product-shots",
  input: {
    product_image: "https://example.com/product.png",
    environments: ["white_background","lifestyle","detail_closeup"],
  },
});

pip install pipe2

Run a pipeline

import asyncio
import os

from pipe2 import Pipe2Client

client = Pipe2Client(token=os.environ["PIPE2_TOKEN"])

run = asyncio.run(client.run_pipeline(
    pipeline_slug="product-shots",
    input={
        "product_image": "https://example.com/product.png",
        "environments": ["white_background","lifestyle","detail_closeup"],
    },
))

go get github.com/pipe2-ai/sdk-go

Run a pipeline

client := pipe2.NewClient(os.Getenv("PIPE2_TOKEN"))

input := json.RawMessage(`{
  "product_image": "https://example.com/product.png",
  "environments": ["white_background","lifestyle","detail_closeup"]
}`)

run, err := pipe2.RunPipeline(context.Background(), client, "product-shots", input)
if err != nil {
    log.Fatal(err)
}

brew install pipe2-ai/tap/pipe2

Run a pipeline

pipe2 pipelines run \
  --pipeline product-shots \
  --input-json '{"product_image": "https://example.com/product.png", "environments": ["white_background","lifestyle","detail_closeup"]}' \
  --wait

Per page

Input	Type	default	Description
`environments`required	array	default["white_background","lifestyle","detail_closeup"]	Array of 1-7 environments to generate. white_background is an Amazon-compliant main image (pure white, 85% product fill). lifestyle is an aspirational real-world scene. in_use shows hands holding or using the product. detail_closeup is a macro texture shot. scale_reference shows the product next to a hand or common object. gradient_studio is a premium ad-creative backdrop. outdoor is a natural environment for ad creative. A strong marketplace set combines white_background, lifestyle, scale_reference, detail_closeup, and in_use; use gradient_studio and outdoor for ads and brand imagery. You pay per environment selected.
`product_image`required	string	default—	URL of the source product photo. One shot is enough, the AI preserves product shape, color, and branding and only changes the background.
`aspect_ratio`	enum	default1:1	Output aspect ratio for the generated shots. 1:1 · 4:5 · 3:4 +4 `1:14:53:42:34:39:1616:9`
`product_description`	string	default—	Optional short description of the product. Helps the AI craft more accurate per-variant edit prompts.

Point any MCP client at pipe2 and your agent gets these tools. It finds this pipeline, reads the same schema above, then runs it.

list_pipelines
get_pipeline_schema
run_pipeline
get_pipeline_run_status
request_upload

https://mcp.pipe2.ai/mcp

{
  "mcpServers": {
    "pipe2ai": {
      "url": "https://mcp.pipe2.ai/mcp",
      "headers": { "Authorization": "Bearer YOUR_TOKEN" }
    }
  }
}

MCP setup

Full API reference CLI reference

Articles about this pipeline

Show all articles

Article
Best AI Image Generators: A Practical Model Comparison

Frequently Asked Questions

How many credits does this cost?

from 3.1 credits per variant. You pick exactly which of the seven environments to render and pay only for those, so a default three-shot set is roughly three times that.

Will the product look different in each variant?

No, the product's shape, material, color, and branding are preserved across all variants. Only the background/context changes.

What image quality should I expect?

Near-studio quality at roughly 2K, suitable for marketplace listings and paid ads.

Can I use this for Amazon listings?

Yes. The 'white background' environment produces Amazon main-image compliant shots (pure white, no props, product-only).

What if one variant fails?

The others still deliver. Failed variants are marked in the output with an error note and the credits are adjusted accordingly.