Editing

Instruction-based image editing via natural-language prompts. Change scenes, swap objects, and adjust composition without masks.

POST /edit/image/v1, edit input_image according to prompt.

cURL

curl -X POST https://api.imagepipeline.io/edit/image/v1 \
  -H "X-API-Key: $IMAGEPIPELINE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "input_image": "https://.../photo.webp",
  "prompt": "change the jacket to navy blue and add soft rim lighting",
  "faster_inference": true
}'

JavaScript

const res = await fetch("https://api.imagepipeline.io/edit/image/v1", {
  method: "POST",
  headers: {
    "X-API-Key": process.env.IMAGEPIPELINE_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
  "input_image": "https://.../photo.webp",
  "prompt": "change the jacket to navy blue and add soft rim lighting",
  "faster_inference": true
}),
});
const { job_id } = await res.json();

Python

import requests

res = requests.post(
    "https://api.imagepipeline.io/edit/image/v1",
    headers={"X-API-Key": API_KEY},
    json={
        "input_image": "https://.../photo.webp",
        "prompt": "change the jacket to navy blue and add soft rim lighting",
        "faster_inference": True,
    },
)
job_id = res.json()["job_id"]

Java

HttpRequest req = HttpRequest.newBuilder()
    .uri(URI.create("https://api.imagepipeline.io/edit/image/v1"))
    .header("X-API-Key", System.getenv("IMAGEPIPELINE_API_KEY"))
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString("""
{
  "input_image": "https://.../photo.webp",
  "prompt": "change the jacket to navy blue and add soft rim lighting",
  "faster_inference": true
}
"""))
    .build();
HttpResponse<String> res = client.send(req, BodyHandlers.ofString());

input_image accepts a single URL string, or an array of URLs (for example a model image plus a product image to composite).

Field	Type	Default	Notes
prompt	string	,	Required. The natural-language edit instruction.
input_image	string | string[]	,	Image(s) to edit. A single URL, or an array of URLs.
mode	string	,	Processing mode. Use anime to convert a photo to an illustration.
faster_inference	boolean	true	Use the Lightning LoRA distillation for speed.
refine_strength	number	,	Z-Image Turbo refinement pass after editing (0.0 to 1.0).
num_inference_steps	integer	model	Diffusion steps (1 to 100). Higher = better, slower.
guidance_scale	number	model	Classifier-free guidance (0.0 to 20.0). 0 disables it.
cfg_norm_strength	number	,	CFG normalization strength (0.0 to 1.0).
tone_correction	number	,	Post-edit tonal correction strength (0.0 to 1.0).
product_saturation	number	,	Saturation multiplier applied to the product image (image 2).
has_text	boolean	,	Whether the image contains visible text, logos, or labels.
has_product	boolean	,	Whether the image contains a physical product as the subject.
seed	integer	-1	-1 randomizes; set a value for reproducibility.
palette	string[]	,	Brand colours as hex codes, e.g. ["#FF5733"].
output_format	string	webp	webp, jpeg, or png.
profile_id	string	,	Apply an identity profile.
callback_url	string	,	Receive a webhook on completion.
server_id	string	,	Enterprise: pin to a dedicated pod.

Response — poll GET …/status/{job_id} until status is completed:

{
  "job_id": "job_7c1a9e44",
  "status": "completed",
  "result_url": "https://cdn.imagepipeline.io/o/7c1a9e44.webp",
  "processing_time_seconds": 30.2,
  "balance_remaining_usd": 187.52
}

Returns a job_id; poll GET /edit/image/v1/status/{job_id} or use a webhook.