iterationlayer Smart Crop Product Image
E-commerce platforms and marketplaces use this recipe to normalize supplier product photos to consistent square thumbnails. AI detects the product and crops around it — no manual positioning, no lost products at the edges.
APIs Used
Image Transformation (0.5 credits/request)
Prerequisites
You need an Iteration Layer API key. Get one at platform.iterationlayer.com during the 7-day trial.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
Implementation
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": "supplier-image.jpg",
"url": "https://cdn.example.com/supplier/product-001.jpg"
},
"operations": [
{
"type": "smart_crop",
"width_in_px": 1000,
"height_in_px": 1000
}
]
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
const result = await client.transformImage({
file: {
type: "url",
name: "supplier-image.jpg",
url: "https://cdn.example.com/supplier/product-001.jpg",
},
operations: [
{
type: "smart_crop",
width_in_px: 1000,
height_in_px: 1000,
},
],
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
result = client.transform_image(
file={
"type": "url",
"name": "supplier-image.jpg",
"url": "https://cdn.example.com/supplier/product-001.jpg",
},
operations=[
{
"type": "smart_crop",
"width_in_px": 1000,
"height_in_px": 1000,
},
],
)
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
result, err := client.TransformImage(il.TransformImageRequest{
File: il.FileInput{Type: "url", Name: "supplier-image.jpg", Url: "https://cdn.example.com/supplier/product-001.jpg"},
Operations: []il.TransformOperation{
il.NewSmartCropOperation(1000, 1000),
},
})
if err != nil {
panic(err)
}
}
{
"name": "Smart Crop Product Image",
"nodes": [
{
"parameters": {
"content": "## Smart Crop Product Image\n\nE-commerce platforms and marketplaces use this recipe to normalize supplier product photos to consistent square thumbnails. AI detects the product and crops around it \u2014 no manual positioning, no lost products at the edges.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes on self-hosted n8n, or add it directly on n8n Cloud with Verified Community Nodes enabled.",
"height": 280,
"width": 500,
"color": 2
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
200,
40
],
"id": "c1f1d6cd-3e16-4933-9557-caf1d498b9e5",
"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": "b548438b-de0a-4f2d-ab16-50b012f9669b",
"name": "Step 1 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "a3b4c5d6-e7f8-4a9b-0c1d-3e4f5a6b7c8d",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "imageTransformation",
"fileInputMode": "url",
"fileName": "supplier-image.jpg",
"fileUrl": "https://cdn.example.com/supplier/product-001.jpg",
"operations": {
"operationValues": [
{
"operationType": "smart_crop",
"widthInPx": 1000,
"heightInPx": 1000
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "d6e7f8a9-b0c1-4d2e-3f4a-5b6c7d8e9f0a",
"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"
}
}
Smart crop the product image at [file URL] to center on the product. Use the transform_image tool with a smart_crop operation to [width]x[height] pixels.
Response
{
"success": true,
"data": {
"buffer": "/9j/4AAQSkZJRgABAQEASABI...",
"mime_type": "image/jpeg"
}
}