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FLUX SRPO [dev] is a 12B flow transformer for image-to-image generation producing high-quality images for personal and commercial use. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-image
Input

Idle

$0.025per run·~40 / $1

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README

FLUX SRPO — Image-to-Image

FLUX SRPO Image-to-Image is a powerful image transformation model that converts existing images into new styles based on text prompts. Upload an image, describe the transformation you want, and the model generates a stylized version while preserving the original composition.

Why It Stands Out

  • Image-to-image transformation: Convert images into new styles while preserving structure.
  • Prompt-guided generation: Describe the visual style you want to achieve.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better results.
  • Adjustable strength: Control how much the output differs from the original.
  • Multiple output formats: Export as JPEG or PNG based on your needs.
  • Fine-tuned control: Adjust guidance scale and inference steps for precise results.
  • Reproducibility: Use the seed parameter to recreate exact results.

Parameters

ParameterRequiredDescription
promptYesText description of the desired visual style.
imageNoSource image to transform (upload or public URL).
strengthNoTransformation intensity (0.0–1.0, default: 0.8).
num_inference_stepsNoQuality/speed trade-off (default: 28).
seedNoSet for reproducibility; -1 for random.
guidance_scaleNoPrompt adherence strength (default: 3.5).
output_formatNoOutput format: jpeg or png (default: jpeg).
enable_base64_outputNoReturn base64 string instead of URL (API only).
enable_sync_modeNoWait for result before returning response (API only).

How to Use

  1. Upload your source image — drag and drop a file or paste a public URL.
  2. Write a prompt describing the visual style you want. Use the Prompt Enhancer for AI-assisted optimization.
  3. Adjust strength — lower values preserve more of the original, higher values allow more transformation.
  4. Adjust parameters (optional) — fine-tune guidance scale and inference steps.
  5. Click Run and download your transformed image.

Best Use Cases

  • Style Transfer — Convert photos into paintings, illustrations, or artistic styles.
  • Visual Effects — Apply consistent visual treatments across multiple images.
  • Content Repurposing — Transform images into different aesthetic styles.
  • Design Exploration — Explore different visual directions from existing images.
  • Creative Projects — Experiment with unique visual transformations.

Pricing

OutputPrice
Per image$0.025

Pro Tips for Best Quality

  • Use lower strength (0.3–0.5) to preserve more of the original image structure.
  • Use higher strength (0.7–0.9) for more dramatic style transformations.
  • Be specific in your prompt about the style, mood, and visual treatment.
  • Use PNG format when you need higher quality or transparency support.
  • Fix the seed when iterating to compare different strength or prompt variations.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • Processing time varies based on current queue load.
  • Please ensure your content complies with usage guidelines.
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.

Flux Srpo Image To Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-srpo/image-to-image 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 Flux Srpo Image To Image 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",
    "strength": 0.8,
    "num_inference_steps": 28,
    "seed": -1,
    "guidance_scale": 3.5,
    "output_format": "jpeg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-srpo/image-to-image" \
  -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/wavespeed-ai/flux-srpo/image-to-image";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "strength": 0.8,
        "num_inference_steps": 28,
        "seed": -1,
        "guidance_scale": 3.5,
        "output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "strength": 0.8,
    "num_inference_steps": 28,
    "seed": -1,
    "guidance_scale": 3.5,
    "output_format": "jpeg"
}

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/wavespeed-ai/flux-srpo/image-to-image", 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)

Flux Srpo Image To Image API — Frequently asked questions

What is the Flux Srpo Image To Image API?

Flux Srpo Image To Image is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. FLUX SRPO [dev] is a 12B flow transformer for image-to-image generation producing high-quality images for personal and commercial use. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Flux Srpo Image To Image 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/wavespeed-ai/flux-srpo-image-to-image.

How much does Flux Srpo Image To Image cost per run?

Flux Srpo Image To Image starts at $0.025 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 Flux Srpo Image To Image accept?

Key inputs: `prompt`, `image`, `seed`, `guidance_scale`, `num_inference_steps`, `enable_base64_output`. 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/wavespeed-ai/flux-srpo-image-to-image.

How long does Flux Srpo Image To Image 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 Flux Srpo Image To Image outputs commercially?

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

Flux Srpo Image to Image | Fast Image Editing API on WaveSpeedAI