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Fibo Image Blend

bria /

Bria Image Blend merges objects, applies textures, or rearranges items within an image using natural language. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

image-to-image
Eingabe

Bereit

Place the art on the shirt, keep the art exactly the same

$0.04pro Durchlauf·~25 / $1

Weiter:

BeispieleAlle anzeigen

Place the art on the shirt, keep the art exactly the same

Place the art on the shirt, keep the art exactly the same

Ähnliche Modelle

README

Bria Fibo Image Blend

Bria Fibo Image Blend is an AI-powered image blending model that seamlessly combines multiple elements within an image based on text instructions. Upload your composite image and describe how you want elements blended — the model intelligently merges them for natural, cohesive results.

Why Choose This?

  • Text-guided blending Use natural language to describe exactly how elements should be combined.

  • Seamless integration AI understands context to blend elements naturally without visible seams.

  • Preserve original elements Keep specific parts unchanged while blending others.

  • Prompt Enhancer Built-in tool to automatically improve your blending instructions.

  • Creative flexibility Perfect for product mockups, composites, and creative projects.

Parameters

ParameterRequiredDescription
imageYesSource image with elements to blend (URL or upload)
promptYesText instruction describing how to blend the elements

How to Use

  1. Upload your image — provide an image with the elements you want to blend.
  2. Write your prompt — describe how the elements should be combined.
  3. Run — submit and download your blended image.

Pricing

OutputCost
Per image$0.04

Best Use Cases

  • Product Mockups — Place artwork or designs onto clothing, products, or surfaces.
  • Composite Creation — Merge multiple image elements into a cohesive scene.
  • Design Visualization — Preview how designs look on real-world objects.
  • Marketing Materials — Create product shots with custom graphics or branding.
  • Creative Projects — Experiment with artistic image combinations.

Pro Tips

  • Be specific about what to keep unchanged (e.g., "keep the art exactly the same").
  • Use the Prompt Enhancer to refine your blending instructions.
  • For product mockups, clearly specify where the design should be placed.
  • Upload high-quality images for best blending results.
  • Describe the desired relationship between elements for more precise control.

Notes

  • Both image and prompt are required fields.
  • Ensure uploaded image URLs are publicly accessible.
  • Works best when elements to be blended are clearly visible in the source image.

Related Models

Hinweis:Diese Website nutzt KI-Modelle von Drittanbietern.

Fibo Image Blend API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bria/fibo/image-blend 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 Fibo Image Blend 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",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/bria/fibo/image-blend" \
  -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/bria/fibo/image-blend";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}

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/bria/fibo/image-blend", 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)

Fibo Image Blend API — Frequently asked questions

What is the Fibo Image Blend API?

Fibo Image Blend is a Bria model for image editing, exposed as a REST API on WaveSpeedAI. Bria Image Blend merges objects, applies textures, or rearranges items within an image using natural language. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Fibo Image Blend 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/bria/bria-fibo-image-blend.

How much does Fibo Image Blend cost per run?

Fibo Image Blend starts at $0.040 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 Fibo Image Blend accept?

Key inputs: `prompt`, `image`. 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/bria/bria-fibo-image-blend.

How long does Fibo Image Blend take to generate?

Median end-to-end generation time on WaveSpeedAI is around 21 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 Fibo Image Blend outputs commercially?

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

Fibo Image Blend | Fast Image Editing API | WaveSpeedAI