Bria Guided Remove Background removes image backgrounds with optional text guidance to control what should be preserved, producing clean transparent cutouts while retaining the original foreground pixels for product images, e-commerce assets, portraits, and design workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle

$0.03per run·~33 / $1


Keep only the astronaut and the helmet she is holding.
Bria Guided Remove Background removes image backgrounds with optional text guidance for more controlled cutouts. Provide an image and, when needed, describe which subjects or objects should be kept or removed.
Use it for product cutouts, people, props, catalog assets, advertising composites, and other workflows that need transparent-background images with more control than standard automatic background removal.
Prompt-guided background removal
Use natural-language instructions to describe which subjects or objects should remain in the cutout.
Standard background removal
Leave prompt empty when you want automatic background removal without additional guidance.
Selective cutouts
Guide the model toward specific people, products, props, or other visual elements.
Existing alpha control
Preserve transparency already present in the source image or make retained regions fully opaque.
Multiple image input formats
Supports JPEG, JPG, PNG, and WEBP input images.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Source image provided as a publicly accessible URL. Supported formats: JPEG, JPG, PNG, and WEBP. |
| prompt | No | Optional instructions describing what should be kept or removed. Omit or leave blank for standard background removal. |
| preserve_alpha | No | Preserve existing transparency in the input image. |
prompt when you want to specify which subject, object, or group of elements should remain.preserve_alpha=true to retain existing transparency, or disable it to make retained regions fully opaque.outputs array.Pricing is fixed at $0.03 per image.
| Output | Cost |
|---|---|
| One background-removed image | $0.03 |
prompt and preserve_alpha do not add separate charges.
only the chair or the person with the plant.prompt empty when standard automatic background removal is sufficient.preserve_alpha=true when existing transparency in the source image should remain.preserve_alpha=false when the retained subject should be fully opaque.image is required.prompt is optional.prompt is omitted or left blank, the endpoint performs standard background removal.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bria/remove-background-guided with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Remove Background Guided below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"preserve_alpha": true
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/bria/remove-background-guided" \
-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="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(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' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/bria/remove-background-guided";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"preserve_alpha": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
await new Promise(resolve => setTimeout(resolve, 2000));
}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",
"preserve_alpha": True
}
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/remove-background-guided", 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 = 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", "deleted"}:
raise RuntimeError(result)
time.sleep(2)Remove Background Guided is a Bria model for image background removal, exposed as a REST API on WaveSpeedAI. Bria Guided Remove Background removes image backgrounds with optional text guidance to control what should be preserved, producing clean transparent cutouts while retaining the original foreground pixels for product images, e-commerce assets, portraits, and design workflows. 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/bria/bria-remove-background-guided.
Remove Background Guided starts at $0.03 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`, `preserve_alpha`. 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-remove-background-guided.
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.
Commercial usage rights depend on the model's license, set by its provider (Bria). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.