Bria Generate Background

Bria Generate Background

Playground

Try it on WaveSpeedAI!

Swap image backgrounds using text or reference images; realistic results. Trained on licensed data for risk-free commercial use. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Bria Background Generation replaces or generates realistic backgrounds from a text prompt or a reference image while preserving the foreground subject. It’s trained exclusively on licensed data for safe, low-risk commercial use across ads, e-commerce, social, portraits, and product photos.


✨ Highlights

  • Dual input: drive backgrounds by prompt or match style/composition with a reference image.
  • Subject preservation: clean edges and minimal color bleed around people and products.
  • Style range: photorealistic, illustration, anime—swap backgrounds without touching the subject.
  • Production-ready: predictable results that slot into real design pipelines.
  • Licensed training data: built for compliant commercial deployment.

🧩 Parameters

  • image* (required) Foreground/subject image (URL or upload). Missing image will fail.

  • prompt* (required) Background description only (scene, lighting, style, materials, mood). Example: “Epic anime city at night, neon signs, volumetric fog, blue-purple rim light.”


🚀 How to Use

  1. Provide image (required) — a clear, unobstructed subject works best.
  2. Write prompt (required) — describe the background only: environment, lighting, style.
  3. Click Run (e.g., $0.04) and download the generated image.
  4. Keep the same image and tweak the prompt to iterate styles while preserving composition.

💰 Pricing

  • Per job $0.04

🧠 Prompting Tips (background-focused)

  • Separate roles: keep the subject in the image; keep the background in the prompt.
  • Lead with light: phrases like golden hour, studio softbox, neon backlight, volumetric fog quickly lift realism.
  • Style anchors: add photorealistic, cinematic, anime, watercolor, or minimalist to control look.
  • Materials & space: e.g., concrete rooftop, wet asphalt, marble lobby, skylight, depth of field.
  • Consistent campaigns: reuse the same image and a prompt template; adjust color/weather for quick variants.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "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/generate-background" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(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' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  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

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-Text description of the new scene or background
imagestringYes-The URL of the image to erase.
enable_sync_modebooleanNofalse-If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models.
enable_base64_outputbooleanNofalse-If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
© 2026 WaveSpeedAI. All rights reserved.