Embed Product | Fast Image Editing API

Bria Embed Product

Bria Embed Product seamlessly embeds product images into background scenes with precise positioning control. Upload a background image and one or more product images with exact placement coordinates — the model intelligently blends products into the scene with natural lighting, shadows, and perspective.

Why Choose This?

Precise positioning Specify exact X, Y coordinates and dimensions for pixel-perfect product placement.
Multi-product support Embed multiple products into a single scene with individual positioning for each.
Intelligent blending Automatically adapts lighting, shadows, and perspective for realistic integration.
Simple workflow Define position and size — the model handles the compositing automatically.

Parameters

Parameter	Required	Description
image	Yes	Background image (URL or upload)
products	Yes	List of products to embed (click "+ Add Item" to add more)
→ image	Yes	Product image (URL or upload)
→ x	Yes	X coordinate for product placement (pixels)
→ y	Yes	Y coordinate for product placement (pixels)
→ width	Yes	Product width in the output (pixels)
→ height	Yes	Product height in the output (pixels)
seed	No	Random seed for reproducibility
enable_sync_mode	No	Wait for result in response (API only)
enable_base64_output	No	Return base64 instead of URL (API only)

How to Use

Upload background image — provide the scene where products will be placed.
Add products — for each product:

Upload the product image
Set X and Y coordinates for placement position
Set width and height for product size

Add more products (optional) — click "+ Add Item" to embed additional products.
Set seed (optional) — for reproducible results.
Run — submit and download your composite image.

Pricing

Output	Cost
Per image	$0.04

Best Use Cases

E-commerce — Place products in lifestyle scenes for catalog and marketing images.
Interior Design — Visualize furniture and decor in room settings.
Advertising — Create product placement visuals for campaigns.
Virtual Staging — Add products to empty spaces for real estate or retail.
Product Photography — Composite products into professional backgrounds without physical shoots.

Pro Tips

Use transparent PNG product images for best blending results.
Coordinate values (x, y) define the top-left corner of the product placement.
Match product size (width, height) to the perspective of the background scene.
For multiple products, consider their relative positions and overlap.
Use a consistent seed to iterate on placement while maintaining the same blending style.

Notes

Both image (background) and products are required fields.
Each product requires image, x, y, width, and height values.
Coordinates are in pixels relative to the background image.
Ensure uploaded image URLs are publicly accessible.

Related Models

FireRed Image Edit — Multi-image editing and composition.

Embed Product API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bria/embed-product 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 Embed Product below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/bria/embed-product" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "image": "https://example.com/your-input.jpg",
    "products": [
        {}
    ],
    "seed": 0,
    "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].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("bria/embed-product", {
        "image": "https://example.com/your-input.jpg",
        "products": [
                {}
        ],
        "seed": 0,
        "enable_sync_mode": false,
        "enable_base64_output": false
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "bria/embed-product",
    {
    "image": "https://example.com/your-input.jpg",
    "products": [
        {}
    ],
    "seed": 0,
    "enable_sync_mode": false,
    "enable_base64_output": false
}
)

print(output["outputs"][0])  # → URL of the generated output

Embed Product API — Frequently asked questions

What is the Embed Product API?

Embed Product is a Bria model for image editing, exposed as a REST API on WaveSpeedAI. Bria Embed Product seamlessly integrates product images into scene backgrounds with natural lighting and perspective matching. 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 Embed Product 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 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-embed-product.

How much does Embed Product cost per run?

Embed Product 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 Embed Product accept?

Key inputs: `image`, `seed`, `enable_base64_output`, `enable_sync_mode`, `products`. 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-embed-product.

How do I get started with the Embed Product API?

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.

Can I use Embed Product 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.

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