Editing Images

The image editing endpoint lets you modify existing images by providing a text prompt describing the desired changes. You can optionally include a mask to constrain edits to specific regions.

POST https://api.routeway.ai/v1/images/edits

Basic Image Editing

Provide an image and a prompt describing how to modify it.

Python
Node.js
cURL

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.routeway.ai/v1",
    api_key=os.getenv("ROUTEWAY_API_KEY"),
)

response = client.images.edit(
    model="gpt-image-1",
    image=open("input.png", "rb"),
    prompt="Add a rainbow in the sky",
)

print(response.data[0].url)

import fs from "fs";
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.routeway.ai/v1",
  apiKey: process.env.ROUTEWAY_API_KEY,
});

const response = await client.images.edit({
  model: "gpt-image-1",
  image: fs.createReadStream("input.png"),
  prompt: "Add a rainbow in the sky",
});

console.log(response.data[0].url);

curl -X POST https://api.routeway.ai/v1/images/edits \
  -H "Authorization: Bearer $ROUTEWAY_API_KEY" \
  -F model="gpt-image-1" \
  -F image="@input.png" \
  -F prompt="Add a rainbow in the sky"

Inpainting with Masks

Use a mask to specify which region of the image should be edited. The mask is a same-size image where transparent areas indicate where edits should be applied.

Python
Node.js
cURL

response = client.images.edit(
    model="gpt-image-1",
    image=open("room.png", "rb"),
    mask=open("mask.png", "rb"),
    prompt="A modern red sofa",
    size="1024x1024",
)

print(response.data[0].url)

const response = await client.images.edit({
  model: "gpt-image-1",
  image: fs.createReadStream("room.png"),
  mask: fs.createReadStream("mask.png"),
  prompt: "A modern red sofa",
  size: "1024x1024",
});

console.log(response.data[0].url);

curl -X POST https://api.routeway.ai/v1/images/edits \
  -H "Authorization: Bearer $ROUTEWAY_API_KEY" \
  -F model="gpt-image-1" \
  -F image="@room.png" \
  -F mask="@mask.png" \
  -F prompt="A modern red sofa" \
  -F size="1024x1024"

The mask must be a PNG with an alpha channel. Transparent pixels mark the area to edit; opaque pixels are preserved.

Supported Formats

Format	Supported
PNG	✅
JPEG	✅
WebP	✅
GIF (first frame)	✅

Images must be square and no larger than 4MB. Non-square images may be automatically cropped or rejected depending on the model.

Size Constraints

The size parameter controls the output dimensions of the edited image.

Size	Notes
`1024x1024`	Default. Works with all models.
`512x512`	Smaller output, faster processing.
`256x256`	Minimum supported size.

For best results, provide an input image that matches the requested output size. Mismatched sizes may result in distortion or quality loss.

Editing with Multiple Outputs

Generate several variations of an edit by setting n.

Python
Node.js
cURL

response = client.images.edit(
    model="gpt-image-1",
    image=open("photo.png", "rb"),
    prompt="Replace the background with a snowy mountain landscape",
    n=3,
)

for i, image in enumerate(response.data):
    print(f"Variation {i + 1}: {image.url}")

const response = await client.images.edit({
  model: "gpt-image-1",
  image: fs.createReadStream("photo.png"),
  prompt: "Replace the background with a snowy mountain landscape",
  n: 3,
});

response.data.forEach((image, i) => {
  console.log(`Variation ${i + 1}: ${image.url}`);
});

curl -X POST https://api.routeway.ai/v1/images/edits \
  -H "Authorization: Bearer $ROUTEWAY_API_KEY" \
  -F model="gpt-image-1" \
  -F image="@photo.png" \
  -F prompt="Replace the background with a snowy mountain landscape" \
  -F n=3

Saving Edited Images

Python
Node.js
cURL

import base64

response = client.images.edit(
    model="gpt-image-1",
    image=open("input.png", "rb"),
    prompt="Make it look like a pencil sketch",
    response_format="b64_json",
)

image_data = base64.b64decode(response.data[0].b64_json)

with open("edited.png", "wb") as f:
    f.write(image_data)

print("Edited image saved to edited.png")

const response = await client.images.edit({
  model: "gpt-image-1",
  image: fs.createReadStream("input.png"),
  prompt: "Make it look like a pencil sketch",
  response_format: "b64_json",
});

const imageBuffer = Buffer.from(response.data[0].b64_json, "base64");
fs.writeFileSync("edited.png", imageBuffer);

console.log("Edited image saved to edited.png");

curl -X POST https://api.routeway.ai/v1/images/edits \
  -H "Authorization: Bearer $ROUTEWAY_API_KEY" \
  -F model="gpt-image-1" \
  -F image="@input.png" \
  -F prompt="Make it look like a pencil sketch" \
  -F response_format="b64_json" \
  | jq -r '.data[0].b64_json' | base64 -d > edited.png

Best Practices

Use masks for precise edits

Without a mask, the model decides what to change. For predictable results, provide a mask that clearly marks the target region.

Keep prompts focused on the edit

Describe only what should change, not the entire image. “A blue vase with flowers” works better than re-describing the whole scene.

Match input and output sizes

Provide images at the same resolution you request in size to avoid quality degradation from rescaling.

Get Started

Platform Details

Help & Resources

Core Concepts

Account Management

Guides

Basic Image Editing

Inpainting with Masks

Supported Formats

Size Constraints

Editing with Multiple Outputs

Saving Edited Images

Best Practices

​Basic Image Editing

​Inpainting with Masks

​Supported Formats

​Size Constraints

​Editing with Multiple Outputs

​Saving Edited Images

​Best Practices

Basic Image Editing

Inpainting with Masks

Supported Formats

Size Constraints

Editing with Multiple Outputs

Saving Edited Images

Best Practices