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.
Idle

$0.04per run·~25 / $1

grassy park with flowers, bright natural sunlight, detailed grass and flowers, smooth integration with dog, realistic photo style.

Forest park with a lake and trees, soft natural lighting, reflections of blue sky and greenery on the water surface, realistic photo style.

cozy indoor living room, soft furniture textures, warm natural light, seamless integration with cat, realistic photo style

tropical jungle, vibrant foliage, dappled sunlight, detailed leaves, realistic integration, high-resolution photo style.

snowy mountain landscape, clear sky, detailed snow textures, soft shadows, seamless integration with subject, realistic photo style.

Bright energy blasts illuminate the smoky, vibrant sky. Distant mountains or futuristic city structures are in the background, all rendered in an epic anime art style.

urban city street at dusk, detailed buildings, warm street lights, soft shadows, realistic integration, high-resolution photo style.

tropical beach at sunset, soft waves, golden sand, warm natural light, seamless integration with subject, realistic photo style.
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.
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.”
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bria/generate-background with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Generate Background below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/bria/generate-background" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"enable_sync_mode": false,
"enable_base64_output": false
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("bria/generate-background", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"enable_sync_mode": false,
"enable_base64_output": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"bria/generate-background",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"enable_sync_mode": false,
"enable_base64_output": false
}
)
print(output["outputs"][0]) # → URL of the generated outputGenerate Background is a Bria model for image editing, exposed as a REST API 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. You can call it programmatically or try it from the playground above.
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 prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/bria/bria-generate-background.
Generate Background 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.
Key inputs: `prompt`, `image`, `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/bria/bria-generate-background.
Average end-to-end generation time on WaveSpeedAI is around 17 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
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.