Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
iterationlayer/skills42026年6月9日 更新
無料GitHub で公開
image-resize-watermark-convert
Resize an image, add a branded text watermark, and convert to WebP in a two-step pipeline.
含まれるファイル（1）
- SKILL.md13.1 KB
SKILL.md（原文）
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Resize, Watermark, and Convert Image
E-commerce teams and content platforms use this recipe to process product images for web. Resize to standard dimensions, add brand watermark, and convert to WebP — in two API calls with no image processing infrastructure.
APIs Used
Image Transformation (0.5 credits/request), Image Generation (1 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
# Step 1: Resize and sharpen the image
# The base64 buffer from this response is used as the image layer file in step 2
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-hero.jpg",
"url": "https://cdn.example.com/products/product-hero.jpg"
},
"operations": [
{
"type": "resize",
"width_in_px": 1200,
"height_in_px": 1200,
"fit": "cover",
"position": "smart_crop"
},
{
"type": "sharpen",
"sigma": 0.5
},
{ "type": "convert", "format": "png" }
]
}'
# Step 2: Compose the resized image with a watermark overlay and output as WebP
# Replace the base64 value below with the buffer returned by step 1
curl -X POST https://api.iterationlayer.com/image-generation/v1/generate \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"dimensions": {
"width_in_px": 1200,
"height_in_px": 1200
},
"output_format": "webp",
"layers": [
{
"index": 0,
"type": "solid-color",
"hex_color": "#FFFFFF"
},
{
"index": 1,
"type": "image",
"file": {
"type": "base64",
"name": "product-resized.png",
"base64": "<buffer from step 1>"
},
"position": {
"x_in_px": 0,
"y_in_px": 0
},
"dimensions": {
"width_in_px": 1200,
"height_in_px": 1200
}
},
{
"index": 2,
"type": "text",
"text": "© Riviera Home Goods",
"font_name": "Inter",
"font_size_in_px": 16,
"font_weight": "regular",
"text_color": "#FFFFFF",
"text_align": "right",
"vertical_align": "center",
"position": {
"x_in_px": 900,
"y_in_px": 1160
},
"dimensions": {
"width_in_px": 280,
"height_in_px": 24
},
"opacity": 60
}
]
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
// Step 1: Resize and sharpen the image
const transformed = await client.transformImage({
file: {
type: "url",
name: "product-hero.jpg",
url: "https://cdn.example.com/products/product-hero.jpg",
},
operations: [
{
type: "resize",
width_in_px: 1200,
height_in_px: 1200,
fit: "cover",
position: "smart_crop",
},
{
type: "sharpen",
sigma: 0.5,
},
{ type: "convert", format: "png" },
],
});
// Step 2: Compose the resized image with a watermark overlay and output as WebP
const result = await client.generateImage({
dimensions: { width_in_px: 1200, height_in_px: 1200 },
output_format: "webp",
layers: [
{ index: 0, type: "solid-color", hex_color: "#FFFFFF" },
{
index: 1,
type: "image",
file: {
type: "base64",
name: "product-resized.png",
base64: transformed.buffer,
},
position: { x_in_px: 0, y_in_px: 0 },
dimensions: { width_in_px: 1200, height_in_px: 1200 },
},
{
index: 2,
type: "text",
text: "\u00a9 Riviera Home Goods",
font_name: "Inter",
font_size_in_px: 16,
font_weight: "regular",
text_color: "#FFFFFF",
text_align: "right",
vertical_align: "center",
position: { x_in_px: 900, y_in_px: 1160 },
dimensions: { width_in_px: 280, height_in_px: 24 },
opacity: 60,
},
],
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
# Step 1: Resize and sharpen the image
transformed = client.transform_image(
file={
"type": "url",
"name": "product-hero.jpg",
"url": "https://cdn.example.com/products/product-hero.jpg",
},
operations=[
{
"type": "resize",
"width_in_px": 1200,
"height_in_px": 1200,
"fit": "cover",
"position": "smart_crop",
},
{
"type": "sharpen",
"sigma": 0.5,
},
{"type": "convert", "format": "png"},
],
)
# Step 2: Compose the resized image with a watermark overlay and output as WebP
result = client.generate_image(
dimensions={"width_in_px": 1200, "height_in_px": 1200},
output_format="webp",
layers=[
{"index": 0, "type": "solid-color", "hex_color": "#FFFFFF"},
{
"index": 1,
"type": "image",
"file": {"type": "base64", "name": "product-resized.png", "base64": transformed["buffer"]},
"position": {"x_in_px": 0, "y_in_px": 0},
"dimensions": {"width_in_px": 1200, "height_in_px": 1200},
},
{
"index": 2,
"type": "text",
"text": "\u00a9 Riviera Home Goods",
"font_name": "Inter",
"font_size_in_px": 16,
"font_weight": "regular",
"text_color": "#FFFFFF",
"text_align": "right",
"vertical_align": "center",
"position": {"x_in_px": 900, "y_in_px": 1160},
"dimensions": {"width_in_px": 280, "height_in_px": 24},
"opacity": 60,
},
],
)
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
// Step 1: Resize and sharpen the image
transformed, err := client.TransformImage(il.TransformImageRequest{
File: il.FileInput{Type: "url", Name: "product-hero.jpg", Url: "https://cdn.example.com/products/product-hero.jpg"},
Operations: []il.TransformOperation{
il.NewResizeOperation(1200, 1200, "cover"),
il.NewSharpenOperation(0.5),
il.NewConvertOperation("png"),
},
})
if err != nil {
panic(err)
}
// Step 2: Compose the resized image with a watermark overlay and output as WebP
_, err = client.GenerateImage(il.GenerateImageRequest{
Dimensions: il.Dimensions{WidthInPx: 1200, HeightInPx: 1200},
OutputFormat: "webp",
Layers: []il.Layer{
il.NewSolidColorBackgroundLayer(0, "#FFFFFF"),
il.NewImageLayer(1, il.NewFileFromBase64("product-resized.png", transformed.Buffer),
il.Position{XInPx: 0, YInPx: 0},
il.Dimensions{WidthInPx: 1200, HeightInPx: 1200},
),
il.NewTextLayer(2, "\u00a9 Riviera Home Goods", "Inter", 16, "#FFFFFF",
il.Position{XInPx: 900, YInPx: 1160},
il.Dimensions{WidthInPx: 280, HeightInPx: 24},
),
},
})
if err != nil {
panic(err)
}
}
{
"name": "Resize, Watermark, and Convert Image",
"nodes": [
{
"parameters": {
"content": "## Resize, Watermark, and Convert Image\n\nE-commerce teams and content platforms use this recipe to process product images for web. Resize to standard dimensions, add brand watermark, and convert to WebP \u2014 in two API calls with no image processing infrastructure.\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_in_px": 280,
"width_in_px": 500,
"color": 2
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
200,
40
],
"id": "ff8fd426-80e9-4d97-b534-b997ec1f6eab",
"name": "Overview"
},
{
"parameters": {
"content": "### Step 1: Resize and Sharpen\nResource: **Image Transformation**\n\nConfigure the Image Transformation parameters below, then connect your credentials.",
"height_in_px": 160,
"width_in_px": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
475,
100
],
"id": "4a44d3f6-06b1-4418-ba71-6def1ca74e97",
"name": "Step 1 Note"
},
{
"parameters": {
"content": "### Step 2: Add Watermark and Convert\nResource: **Image Generation**\n\nConfigure the Image Generation parameters below, then connect your credentials.",
"height_in_px": 160,
"width_in_px": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
725,
100
],
"id": "03b33364-4198-42e9-ba9d-61f82588fcce",
"name": "Step 2 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "e6f7a8b9-c0d1-2345-6e90-234567890123",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "imageTransformation",
"fileInputMode": "url",
"fileName": "product-hero.jpg",
"fileUrl": "https://cdn.example.com/products/product-hero.jpg",
"operations": {
"operationValues": [
{
"operationType": "resize",
"widthInPx": 1200,
"heightInPx": 1200,
"resizeMode": "cover"
},
{
"operationType": "sharpen",
"sigma": 0.5
},
{
"operationType": "convert",
"convertFormat": "png"
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "f7a8b9c0-d1e2-3456-7f01-345678901234",
"name": "Resize and Sharpen",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
},
{
"parameters": {
"resource": "imageGeneration",
"widthInPx": 1200,
"heightInPx": 1200,
"outputFormat": "webp",
"layersJson": "[\n {\n \"index\": 0,\n \"type\": \"solid-color\",\n \"hex_color\": \"#FFFFFF\"\n },\n {\n \"index\": 1,\n \"type\": \"image\",\n \"file\": {\n \"type\": \"base64\",\n \"name\": \"product-resized.png\",\n \"base64\": \"<buffer from step 1>\"\n },\n \"position\": { \"x\": 0, \"y\": 0 },\n \"dimensions\": { \"width\": 1200, \"height\": 1200 }\n },\n {\n \"index\": 2,\n \"type\": \"text\",\n \"text\": \"\\u00a9 Riviera Home Goods\",\n \"font_name\": \"Inter\",\n \"font_size_in_px\": 16,\n \"font_weight\": \"regular\",\n \"text_color\": \"#FFFFFF\",\n \"text_align\": \"right\",\n \"vertical_align\": \"center\",\n \"position\": { \"x\": 900, \"y\": 1160 },\n \"dimensions\": { \"width\": 280, \"height\": 24 },\n \"opacity\": 60\n }\n]",
"fontsJson": "[]"
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
750,
300
],
"id": "a8b9c0d1-e2f3-4567-8a12-456789012345",
"name": "Add Watermark and Convert",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Resize and Sharpen",
"type": "main",
"index": 0
}
]
]
},
"Resize and Sharpen": {
"main": [
[
{
"node": "Add Watermark and Convert",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
Resize, watermark, and convert the image at [file URL]. First, use the transform_image tool with a resize operation to [width]x[height] pixels (fit: cover, position: smart_crop), a sharpen operation, and a convert to PNG. Then use the generate_image tool to compose the resized image with a text watermark layer showing "[watermark text]" and output as WebP.
Response
{
"success": true,
"data": {
"buffer": "UklGRlYAAABXRUJQVlA4IEoA...",
"mime_type": "image/webp"
}
}
Links
レビュー
まだレビューはありません。使ってみた感想をお寄せください。
同じリポジトリのスキル
概要と使いどころ
Compress an image to fit within a specific file size in bytes using quality-first compression.
日本語の概要は準備中です。原文の説明を表示しています。
iterationlayer/skills42026年6月9日 更新
Convert a contract PDF to clean markdown for clause extraction or LLM analysis.
日本語の概要は準備中です。原文の説明を表示しています。
iterationlayer/skills42026年6月9日 更新
Convert external documents — specs, contracts, reports — to markdown for knowledge base ingestion.
日本語の概要は準備中です。原文の説明を表示しています。
iterationlayer/skills42026年6月9日 更新
Convert a document to clean markdown suitable for chunking and embedding in a RAG pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
iterationlayer/skills42026年6月9日 更新
Convert an image between PNG, JPEG, and WebP formats with quality control for web optimization.
日本語の概要は準備中です。原文の説明を表示しています。
iterationlayer/skills42026年6月9日 更新