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Fibo Reseason

bria /

Bria Reseason changes the season or weather atmosphere of an image. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

image-to-image
อินพุต

ว่าง

$0.04ต่อครั้ง·~25 / $1

ต่อไป:

ตัวอย่างดูทั้งหมด

โมเดลที่เกี่ยวข้อง

README

Bria Fibo Reseason

Bria Fibo Reseason is an AI-powered image transformation model that changes the season of any outdoor scene. Upload a landscape or outdoor photo and select a target season — the model intelligently transforms foliage, lighting, and atmosphere to match your chosen time of year.

Why Choose This?

  • Four season options Transform images to spring, summer, autumn, or winter.

  • Intelligent scene understanding AI recognizes trees, foliage, sky, and ground to apply realistic seasonal changes.

  • Natural transformations Adjusts colors, lighting, and atmosphere for believable results.

  • Simple workflow Just upload an image and select a season — instant transformation.

  • Versatile applications Perfect for real estate, marketing, and creative projects.

Parameters

ParameterRequiredDescription
imageYesOutdoor/landscape image to transform (URL or upload)
seasonYesTarget season: spring, summer, autumn, winter

Season Options

SeasonDescription
springFresh green foliage, blooming flowers, bright atmosphere
summerLush green leaves, warm lighting, vibrant colors
autumnGolden and red foliage, warm tones, falling leaves
winterSnow coverage, bare trees, cold blue tones

How to Use

  1. Upload your image — provide an outdoor or landscape photo.
  2. Select season — choose the target season you want.
  3. Run — submit and download your transformed image.

Pricing

OutputCost
Per image$0.04

Best Use Cases

  • Real Estate Marketing — Show properties in their best seasonal light.
  • Travel & Tourism — Display destinations across different seasons.
  • Creative Projects — Explore seasonal variations of landscapes.
  • Marketing Campaigns — Create season-specific promotional materials.
  • Film & Video — Pre-visualize scenes in different seasons.

Pro Tips

  • Works best with outdoor scenes featuring trees, landscapes, or natural elements.
  • Winter transformation adds snow — ideal for creating holiday-themed content.
  • Autumn transformation creates warm, golden tones perfect for cozy aesthetics.
  • Use high-quality source images for more realistic seasonal transformations.
  • Combine with Bria Fibo Relight to also adjust the lighting for maximum impact.

Notes

  • Both image and season are required fields.
  • Works best on outdoor scenes with visible vegetation or landscapes.
  • Indoor scenes or close-up portraits may not transform as expected.
  • Ensure uploaded image URLs are publicly accessible.

Related Models

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Fibo Reseason API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bria/fibo/reseason 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 Reseason below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "season": "spring"
}
JSON
)

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

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/reseason", 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 Reseason API — Frequently asked questions

What is the Fibo Reseason API?

Fibo Reseason is a Bria model for image editing, exposed as a REST API on WaveSpeedAI. Bria Reseason changes the season or weather atmosphere of an image. 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 Reseason 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-reseason.

How much does Fibo Reseason cost per run?

Fibo Reseason 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 Reseason accept?

Key inputs: `image`, `season`. 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-reseason.

How do I get started with the Fibo Reseason API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use Fibo Reseason 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 Reseason | Fast Image Editing API | WaveSpeedAI