Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
The English summary is being prepared. Showing the original description.
Use AI detection to smart-crop individual portraits from a group photo.
The English summary is being prepared. Showing the original description.
Review the instructions the agent will receive before you install.
HR platforms and event organizers extract individual headshots from team or group photos using AI-powered face detection to crop around the most prominent subject. Upload a group photo, apply smart crop to center on the detected face, and convert to JPEG — ready for employee directories, badges, or social profiles.
Image Transformation (0.5 credits/request)
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.
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": "group-photo.jpg",
"url": "https://example.com/group-photo.jpg"
},
"operations": [
{
"type": "smart_crop",
"width_in_px": 400,
"height_in_px": 400
},
{
"type": "convert",
"format": "jpeg",
"quality": 90
}
]
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
const result = await client.transformImage({
file: {
type: "url",
name: "group-photo.jpg",
url: "https://example.com/group-photo.jpg",
},
operations: [
{
type: "smart_crop",
width_in_px: 400,
height_in_px: 400,
},
{
type: "convert",
format: "jpeg",
quality: 90,
},
],
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
result = client.transform_image(
file={
"type": "url",
"name": "group-photo.jpg",
"url": "https://example.com/group-photo.jpg",
},
operations=[
{
"type": "smart_crop",
"width_in_px": 400,
"height_in_px": 400,
},
{
"type": "convert",
"format": "jpeg",
"quality": 90,
},
],
)
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: "group-photo.jpg", Url: "https://example.com/group-photo.jpg"},
Operations: []il.TransformOperation{
il.NewSmartCropOperation(400, 400),
il.NewConvertOperation("jpeg"),
},
})
if err != nil {
panic(err)
}
}
{
"name": "Smart Crop Group Photo",
"nodes": [
{
"parameters": {
"content": "## Smart Crop Group Photo\n\nHR platforms and event organizers extract individual headshots from team or group photos using AI-powered face detection to crop around the most prominent subject. Upload a group photo, apply smart crop to center on the detected face, and convert to JPEG \u2014 ready for employee directories, badges, or social profiles.\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": "7d2e9c48-ab14-46c6-81df-28efb20a5e3d",
"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": "98571eef-7f02-4713-a429-42f8dc8997bd",
"name": "Step 1 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "f2a3b4c5-d6e7-4f8a-9b0c-2d3e4f5a6b7c",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "imageTransformation",
"fileInputMode": "url",
"fileName": "group-photo.jpg",
"fileUrl": "https://example.com/group-photo.jpg",
"operations": {
"operationValues": [
{
"operationType": "smart_crop",
"widthInPx": 400,
"heightInPx": 400
},
{
"operationType": "convert",
"convertFormat": "jpeg",
"quality": 90
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "c5d6e7f8-a9b0-4c1d-2e3f-4a5b6c7d8e9f",
"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 a portrait from the group photo at [file URL]. Use the transform_image tool with a smart_crop operation to [width]x[height] pixels and a convert operation to JPEG at quality [quality].
{
"success": true,
"data": {
"buffer": "/9j/4AAQSkZJRgABAQAAAQABAAD...",
"mime_type": "image/jpeg"
}
}
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
The English summary is being prepared. Showing the original description.
Compress an image to fit within a specific file size in bytes using quality-first compression.
The English summary is being prepared. Showing the original description.
Convert a contract PDF to clean markdown for clause extraction or LLM analysis.
The English summary is being prepared. Showing the original description.
Convert external documents — specs, contracts, reports — to markdown for knowledge base ingestion.
The English summary is being prepared. Showing the original description.
Convert a document to clean markdown suitable for chunking and embedding in a RAG pipeline.
The English summary is being prepared. Showing the original description.
Convert an image between PNG, JPEG, and WebP formats with quality control for web optimization.
The English summary is being prepared. Showing the original description.