Seedream 5.0 Pro yayında | Görsel Üretici'de deneyin →

Bria Product Dimensions API

bria /

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.

image-to-image
Giriş

Boşta

$0.04çalıştırma başına·~25 / $1

Sonraki:

ÖrneklerTümünü görüntüle

İlgili Modeller

README

Bria Product Dimensions

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.

Why Choose This?

  • 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.

Parameters

ParameterRequiredDescription
imageYesSource product photo. JPEG, JPG, PNG, and WEBP are supported.
dimensionsYesDimension callouts to render. Each item includes name, value, unit, and optional position.
styleYesRendering style: default, childlike, or elegant.
units_displayNoLabel display mode: single, dual_bullet, dual_slash, or dual_parens. Default: single.
backgroundNoCanvas background. Use white, cream, charcoal, or a hex color. Default: white.
titleNoOptional headline above the product. Maximum 80 characters.
title_positionNoTitle placement: top_left, top_center, or top_right. Default: top_center.
weight_valueNoOptional product weight value. Use together with weight_unit.
weight_unitNoOptional product weight unit: lb, oz, g, or kg.
weight_labelNoOptional weight label: Weight or Net Weight.
capacity_valueNoOptional product capacity value. Use together with capacity_unit.
capacity_unitNoOptional product capacity unit: fl_oz, ml, l, qt, gal, or cups.
proportional_linesNoScale callout line length to the measurement value. Default: true.

How to Use

  1. Upload product photo - Provide a clear product image.
  2. Add dimensions - Enter at least one measurement such as height or bottom width.
  3. Choose style - Select the callout visual style.
  4. Adjust optional display settings - Add a title, background, weight, or capacity if needed.
  5. Submit - Generate the dimension image and retrieve the output URL.

Pricing

OutputPrice
Per image$0.04

Best Use Cases

  • Ecommerce product pages - Generate clear dimension images for listings.
  • Marketplace assets - Create product visuals for catalogs and online stores.
  • Packaging and product content - Show height, width, weight, or capacity in a polished visual.
  • Product marketing - Create clean comparison or specification images.
  • SKU workflows - Standardize product dimension visuals across many items.

Pro Tips

  • Use a clean product photo with the full product visible.
  • Use height, width_bottom, and width_top for the clearest callout layout.
  • Use dual_parens when you want labels such as 10 in (25.4 cm).
  • Keep titles short so they do not crowd the product.
  • Use a simple background color for marketplace-style assets.
  • Ensure the input image URL is publicly accessible.

Notes

  • image, dimensions, and style are required.
  • Output format is fixed to PNG.
  • The backend output size defaults to 2200 pixels.
  • Synchronous mode, webhook callbacks, and moderation switches are handled by backend defaults.
Not:Bu web sitesi, üçüncü taraflarca sağlanan yapay zeka modellerini kullanmaktadır.

Product Dimensions API — Quick start

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.

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",
    "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
done
Node.js example
const 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));
}
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",
    "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 API — Frequently asked questions

What is the Product Dimensions API?

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.

How do I call the Product Dimensions 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-product-dimensions.

How much does Product Dimensions cost per run?

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.

What inputs does Product Dimensions accept?

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.

How long does Product Dimensions take to generate?

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.

Can I use Product Dimensions 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.

Bria Product Dimensions API | WaveSpeedAI