Iteration Layer

Optimize Product Image for Amazon

Prepare a product photo to meet Amazon's main image requirements: pure white background, square format, 2000×2000px, JPEG.

No credit card required — start with free trial credits

Who this is for

E-commerce sellers and agencies use this recipe to prepare product photos that pass Amazon's main image requirements. One API call removes the background, fills it white, resizes to the required square format, and outputs a JPEG — no manual editing, no Photoshop.

Request
curl -X POST https://api.iterationlayer.com/image-transformation/v1/transform \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "file": {
      "type": "url",
      "name": "product.jpg",
      "url": "https://example.com/products/raw/jacket-001.jpg"
    },
    "operations": [
      {
        "type": "remove_background",
        "background_hex_color": "#FFFFFF"
      },
      {
        "type": "resize",
        "width_in_px": 2000,
        "height_in_px": 2000,
        "fit": "contain"
      },
      {
        "type": "convert",
        "format": "jpeg",
        "quality": 90
      }
    ]
  }'
Response
{
  "success": true,
  "data": {
    "buffer": "/9j/4AAQSkZJRgABAQ...",
    "mime_type": "image/jpeg"
  }
}
Request
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });

const result = await client.transform({
  file: {
    type: "url",
    name: "product.jpg",
    url: "https://example.com/products/raw/jacket-001.jpg",
  },
  operations: [
    {
      type: "remove_background",
      background_hex_color: "#FFFFFF",
    },
    {
      type: "resize",
      width_in_px: 2000,
      height_in_px: 2000,
      fit: "contain",
    },
    {
      type: "convert",
      format: "jpeg",
      quality: 90,
    },
  ],
});
Response
{
  "success": true,
  "data": {
    "buffer": "/9j/4AAQSkZJRgABAQ...",
    "mime_type": "image/jpeg"
  }
}
Request
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")

result = client.transform(
    file={
        "type": "url",
        "name": "product.jpg",
        "url": "https://example.com/products/raw/jacket-001.jpg",
    },
    operations=[
        {
            "type": "remove_background",
            "background_hex_color": "#FFFFFF",
        },
        {
            "type": "resize",
            "width_in_px": 2000,
            "height_in_px": 2000,
            "fit": "contain",
        },
        {
            "type": "convert",
            "format": "jpeg",
            "quality": 90,
        },
    ],
)
Response
{
  "success": true,
  "data": {
    "buffer": "/9j/4AAQSkZJRgABAQ...",
    "mime_type": "image/jpeg"
  }
}
Request
package main

import il "github.com/iterationlayer/sdk-go"

func main() {
    client := il.NewClient("YOUR_API_KEY")

    quality := 90
    result, err := client.Transform(il.TransformRequest{
        File: il.NewFileFromURL("product.jpg", "https://example.com/products/raw/jacket-001.jpg"),
        Operations: []il.TransformOperation{
            il.RemoveBackgroundOperation{Type: "remove_background", BackgroundHexColor: "#FFFFFF"},
            il.NewResizeOperation(2000, 2000, "contain"),
            il.ConvertOperation{Type: "convert", Format: "jpeg", Quality: &quality},
        },
    })
    if err != nil {
        panic(err)
    }
    _ = result
}
Response
{
  "success": true,
  "data": {
    "buffer": "/9j/4AAQSkZJRgABAQ...",
    "mime_type": "image/jpeg"
  }
}
Template
{
  "name": "Optimize Product Image for Amazon",
  "nodes": [
    {
      "parameters": {
        "content": "## Optimize Product Image for Amazon\n\nE-commerce sellers and agencies use this recipe to prepare product photos that pass Amazon's main image requirements. One API call removes the background, fills it white, resizes to the required square format, and outputs a JPEG \u2014 no manual editing, no Photoshop.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes before importing. Self-hosted n8n only.",
        "height": 280,
        "width": 500,
        "color": 2
      },
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        200,
        40
      ],
      "id": "cc02028c-4051-4ba5-8c25-38fe96c4303c",
      "name": "Overview"
    },
    {
      "parameters": {
        "content": "### Step 1: Transform Image\nResource: **Image Transformation**\n\nConfigure the Image Transformation parameters below, then connect your credentials.",
        "height": 160,
        "width": 300,
        "color": 6
      },
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        475,
        100
      ],
      "id": "a3156e35-e86c-4589-bd75-791e9e13e956",
      "name": "Step 1 Note"
    },
    {
      "parameters": {},
      "type": "n8n-nodes-base.manualTrigger",
      "typeVersion": 1,
      "position": [
        250,
        300
      ],
      "id": "d4e5f6a7-b8c9-4d0e-1f2a-4b5c6d7e8f9a",
      "name": "Manual Trigger"
    },
    {
      "parameters": {
        "resource": "imageTransformation",
        "fileInputMode": "url",
        "fileName": "product.jpg",
        "fileUrl": "https://example.com/products/raw/jacket-001.jpg",
        "operations": {
          "operationValues": [
            {
              "operationType": "remove_background",
              "hexColor": "#FFFFFF"
            },
            {
              "operationType": "resize",
              "widthInPx": 2000,
              "heightInPx": 2000,
              "fit": "contain"
            },
            {
              "operationType": "convert",
              "convertFormat": "jpeg",
              "quality": 90
            }
          ]
        }
      },
      "type": "n8n-nodes-iterationlayer.iterationLayer",
      "typeVersion": 1,
      "position": [
        500,
        300
      ],
      "id": "a7b8c9d0-e1f2-4a3b-4c5d-6e7f8a9b0c1d",
      "name": "Transform Image",
      "credentials": {
        "iterationLayerApi": {
          "id": "1",
          "name": "Iteration Layer API"
        }
      }
    }
  ],
  "connections": {
    "Manual Trigger": {
      "main": [
        [
          {
            "node": "Transform Image",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  }
}
Prompt
Optimize the product image at [file URL] for Amazon. Use the transform_image tool with a remove_background operation (background color #FFFFFF), a resize operation to 2000x2000 pixels (fit: contain), and a convert operation to JPEG at quality 90.

Related Recipes

Build your first workflow in minutes

Chain our APIs together and ship a complete pipeline before lunch. Free trial credits included — no credit card required.