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Pruna AI P-Image Edit is a fast AI image editing model that edits and transforms images based on text instructions and reference images. Ready-to-use REST inference API for photo retouching, creative edits, product image updates, background changes, marketing assets, and AI image editing workflows with simple integration, no coldstarts, and affordable pricing.

image-to-image
Input

Idle

Change the figure 1 man's suit to the clothes in figure 2.

$0.01per run·~100 / $1

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ExamplesView all

Change the figure 1 man's suit to the clothes in figure 2.

Change the figure 1 man's suit to the clothes in figure 2.

Related Models

README

Pruna AI P-Image Edit

Pruna AI P-Image Edit transforms one or more reference images using natural-language editing instructions. It is designed for image modification workflows such as outfit changes, style transfer, object replacement, visual refinement, and other prompt-guided image edits.

Why Choose This?

  • Prompt-driven image editing Edit images by describing exactly what you want to change in natural language.

  • Multi-image reference support Upload one or more images to guide the edit, making it easier to preserve identity, style, or visual consistency.

  • Flexible aspect ratio control Choose the output aspect ratio that best fits your use case.

  • Multiple output formats Export the edited image in a supported format such as png.

  • Seed support for reproducibility Use seed to get more consistent results across repeated edits.

  • Simple fixed pricing Each edit run uses a straightforward per-image price.

Parameters

ParameterRequiredDescription
promptYesText instruction describing the desired edit.
imagesYesOne or more reference images used for the edit.
aspect_ratioNoOutput aspect ratio for the edited image.
output_formatNoOutput image format, such as png.
seedNoRandom seed for reproducibility. Use the same seed to get more consistent results.

How to Use

  1. Upload your reference images — provide one or more images you want to use for the edit.
  2. Write your prompt — describe what should change and what should stay consistent.
  3. Choose aspect ratio (optional) — select the output ratio that matches your target use case.
  4. Choose output format (optional) — select the format that best fits your workflow.
  5. Set a seed (optional) — use a fixed seed for more reproducible results.
  6. Submit — run the model and download the edited image.

Example Prompt

Change the figure 1 man's suit to the clothes in figure 2.

Pricing

Just $0.01 per image.

Best Use Cases

  • Outfit and apparel changes — Replace clothing or accessories while preserving the subject.
  • Style transfer — Apply the look or styling of one image to another.
  • Visual refinement — Improve or adjust details using prompt-based instructions.
  • Character consistency edits — Modify appearance while keeping identity and composition stable.
  • Creative image adaptation — Rework an existing image into a new variation for marketing, design, or social content.
  • Reference-guided editing — Use multiple images when you need stronger control over the desired result.

Pro Tips

  • Be specific about what should change and what should remain unchanged.
  • If using multiple images, make sure each image clearly supports the edit you want.
  • Mention identity, clothing, background, or composition explicitly when consistency matters.
  • Use the same seed when you want to iterate on an edit with more consistent outputs.
  • Keep prompts short and direct for simple edits, and add more detail only when necessary.

Notes

  • Both prompt and images are required.
  • images can include one or more reference images.
  • seed helps with reproducibility but may not guarantee identical results in every case.
  • Pricing is fixed at $0.01 per image.

Related Models

  • Pruna AI P-Image Text-to-Image — Generate new images directly from natural-language prompts.
  • Other Pruna AI image generation and image editing models may be useful when you need different quality, speed, or workflow trade-offs.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

P Image Edit API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/pruna-ai/p-image/edit with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for P Image Edit below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "images": [
        "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
    ],
    "aspect_ratio": "match_input_image",
    "output_format": "png",
    "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/pruna-ai/p-image/edit" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/pruna-ai/p-image/edit";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "images": [
                "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
        ],
        "aspect_ratio": "match_input_image",
        "output_format": "png",
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "images": [
        "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
    ],
    "aspect_ratio": "match_input_image",
    "output_format": "png",
    "seed": -1
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/pruna-ai/p-image/edit", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

P Image Edit API — Frequently asked questions

What is the P Image Edit API?

P Image Edit is a Pruna Ai model for image editing, exposed as a REST API on WaveSpeedAI. Pruna AI P-Image Edit is a fast AI image editing model that edits and transforms images based on text instructions and reference images. Ready-to-use REST inference API for photo retouching, creative edits, product image updates, background changes, marketing assets, and AI image editing workflows with simple integration, no coldstarts, and affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the P Image Edit API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/pruna-ai/pruna-ai-p-image-edit.

How much does P Image Edit cost per run?

P Image Edit starts at $0.010 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does P Image Edit accept?

Key inputs: `prompt`, `images`, `aspect_ratio`, `seed`, `enable_base64_output`, `enable_sync_mode`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/pruna-ai/pruna-ai-p-image-edit.

How long does P Image Edit take to generate?

Median end-to-end generation time on WaveSpeedAI is around 5 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use P Image Edit outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Pruna Ai). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

P Image Edit | Fast Image Editing API on WaveSpeedAI