Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
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Resize and convert manuscript images to KDP-compliant dimensions at 300 DPI for print-on-demand.
The English summary is being prepared. Showing the original description.
Review the instructions the agent will receive before you install.
Self-publishers and book production teams use this recipe to prepare manuscript images for KDP or IngramSpark. Constrain images to the printable area (1500x2400 pixels for a 6x9 inch page at 300 DPI), sharpen after downscale, and convert to JPEG at high quality — ready for interior pages.
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": "diagram-03.png",
"url": "https://storage.example.com/book/diagram-03.png"
},
"operations": [
{
"type": "resize",
"width_in_px": 1500,
"height_in_px": 2400,
"fit": "inside"
},
{
"type": "sharpen",
"sigma": 0.5
},
{
"type": "convert",
"format": "jpeg",
"quality": 95
}
]
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
const result = await client.transformImage({
file: {
type: "url",
name: "diagram-03.png",
url: "https://storage.example.com/book/diagram-03.png",
},
operations: [
{
type: "resize",
width_in_px: 1500,
height_in_px: 2400,
fit: "inside",
},
{
type: "sharpen",
sigma: 0.5,
},
{
type: "convert",
format: "jpeg",
quality: 95,
},
],
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
result = client.transform_image(
file={
"type": "url",
"name": "diagram-03.png",
"url": "https://storage.example.com/book/diagram-03.png",
},
operations=[
{
"type": "resize",
"width_in_px": 1500,
"height_in_px": 2400,
"fit": "inside",
},
{
"type": "sharpen",
"sigma": 0.5,
},
{
"type": "convert",
"format": "jpeg",
"quality": 95,
},
],
)
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
quality := 95
result, err := client.TransformImage(il.TransformImageRequest{
File: il.FileInput{Type: "url", Name: "diagram-03.png", Url: "https://storage.example.com/book/diagram-03.png"},
Operations: []il.TransformOperation{
il.NewResizeOperation(1500, 2400, "inside"),
il.NewSharpenOperation(0.5),
il.ConvertOperation{Type: "convert", Format: "jpeg", Quality: &quality},
},
})
if err != nil {
panic(err)
}
}
{
"name": "Resize Image for Print Publishing",
"nodes": [
{
"parameters": {
"content": "## Resize Image for Print Publishing\n\nSelf-publishers and book production teams use this recipe to prepare manuscript images for KDP or IngramSpark. Constrain images to the printable area (1500x2400 pixels for a 6x9 inch page at 300 DPI), sharpen after downscale, and convert to JPEG at high quality \u2014 ready for interior pages.\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": "474c9048-ca01-43e7-b05f-2692707102ea",
"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": "0ef17e6f-9466-40c3-9cdb-acadbf57e915",
"name": "Step 1 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "d0e1f2a3-b4c5-4d6e-7f8a-0b1c2d3e4f5a",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "imageTransformation",
"fileInputMode": "url",
"fileName": "diagram-03.png",
"fileUrl": "https://storage.example.com/book/diagram-03.png",
"operations": {
"operationValues": [
{
"operationType": "resize",
"widthInPx": 1500,
"heightInPx": 2400,
"fit": "inside"
},
{
"operationType": "sharpen",
"sigma": 0.5
},
{
"operationType": "convert",
"convertFormat": "jpeg",
"quality": 95
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "a3b4c5d6-e7f8-4a9b-0c1d-2e3f4a5b6c7d",
"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"
}
}
Resize the image at [file URL] for print publishing. Use the transform_image tool with a resize operation to [width]x[height] pixels (fit: inside), a sharpen operation, and a convert operation to JPEG at quality 95.
{
"success": true,
"data": {
"buffer": "iVBORw0KGgoAAAANSUhEUg...",
"mime_type": "image/jpeg"
}
}
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Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
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The English summary is being prepared. Showing the original description.