Bria Product Dimensions creates marketplace-ready product images from product photos and real-world measurements, adding dimension callouts, labels, optional titles, and product facts for e-commerce listings and catalog visuals. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
就緒

$0.04每次運行·~25 / $1

Bria Product Dimensions turns a single product photo and real-world measurements into a clean product dimension image. The model preserves the product, removes the background inside the pipeline, and renders dimension callouts with labels.
Product dimension images Create marketplace-ready dimension visuals from one product photo and measurement values.
No generative redraw The product is preserved while callout lines and labels are rendered around it.
Flexible callouts Add height, top width, and bottom width labels with metric or imperial units.
Style options
Choose default, childlike, or elegant callout styling.
Optional product facts Add a title, weight readout, or capacity readout when needed.
Standard PNG output Results are returned as PNG image URLs in the standard WaveSpeed prediction response.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Source product photo. JPEG, JPG, PNG, and WEBP are supported. |
| dimensions | Yes | Dimension callouts to render. Each item includes name, value, unit, and optional position. |
| style | Yes | Rendering style: default, childlike, or elegant. |
| units_display | No | Label display mode: single, dual_bullet, dual_slash, or dual_parens. Default: single. |
| background | No | Canvas background. Use white, cream, charcoal, or a hex color. Default: white. |
| title | No | Optional headline above the product. Maximum 80 characters. |
| title_position | No | Title placement: top_left, top_center, or top_right. Default: top_center. |
| weight_value | No | Optional product weight value. Use together with weight_unit. |
| weight_unit | No | Optional product weight unit: lb, oz, g, or kg. |
| weight_label | No | Optional weight label: Weight or Net Weight. |
| capacity_value | No | Optional product capacity value. Use together with capacity_unit. |
| capacity_unit | No | Optional product capacity unit: fl_oz, ml, l, qt, gal, or cups. |
| proportional_lines | No | Scale callout line length to the measurement value. Default: true. |
| Output | Price |
|---|---|
| Per image | $0.04 |
height, width_bottom, and width_top for the clearest callout layout.dual_parens when you want labels such as 10 in (25.4 cm).image, dimensions, and style are required.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bria/product-dimensions with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Product Dimensions below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"dimensions": [
{
"name": "height",
"value": 0,
"unit": "mm",
"position": "top"
}
],
"style": "default",
"units_display": "single",
"background": "white",
"title_position": "top_center",
"weight_unit": "lb",
"weight_label": "Weight",
"capacity_unit": "fl_oz",
"proportional_lines": true
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/bria/product-dimensions" \
-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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/bria/product-dimensions";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"dimensions": [
{
"name": "height",
"value": 0,
"unit": "mm",
"position": "top"
}
],
"style": "default",
"units_display": "single",
"background": "white",
"title_position": "top_center",
"weight_unit": "lb",
"weight_label": "Weight",
"capacity_unit": "fl_oz",
"proportional_lines": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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));
}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",
"dimensions": [
{
"name": "height",
"value": 0,
"unit": "mm",
"position": "top"
}
],
"style": "default",
"units_display": "single",
"background": "white",
"title_position": "top_center",
"weight_unit": "lb",
"weight_label": "Weight",
"capacity_unit": "fl_oz",
"proportional_lines": 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/product-dimensions", 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)Product Dimensions is a Bria model for image editing, exposed as a REST API on WaveSpeedAI. Bria Product Dimensions creates marketplace-ready product images from product photos and real-world measurements, adding dimension callouts, labels, optional titles, and product facts for e-commerce listings and catalog visuals. 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 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-product-dimensions.
Product Dimensions 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: `image`, `background`, `capacity_unit`, `capacity_value`, `dimensions`, `proportional_lines`. 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-product-dimensions.
Median end-to-end generation time on WaveSpeedAI is around 5 seconds per request, based on recent successful runs. Queue time varies 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.