# Bria Product Shot API

> Places a product in a new lifestyle scene from a text description or reference image, with placement controls

Puts the product from `image_url` into a scene described by `scene_description` or shown in `ref_image_url`, but not both. `placement_type` can be original, automatic, manual_placement or manual_padding, with ten `manual_placement_selection` positions and a `shot_size` of about 1,000,000 pixels. `num_results` ranges from 1 to 4, and a `fast` mode is available.

- Model id: `bria/product-shot`
- Made by: Bria AI
- Category: Image Editing
- Output: image
- Price: $0.04 / image (cheapest run $0.04 (40 API credits))
- Run: `POST https://api.doitong.com/v1/run/bria/product-shot`
- Quote: `POST https://api.doitong.com/v1/quote/bria/product-shot`
- Docs page: https://doitong.com/developers/models/bria/product-shot

## Pricing

Price: **$0.04 / image**. Billed per generated image (`num_results`, default 1).

The full example input below costs $0.04 = 40 API credits (1 image × 40 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/bria/product-shot` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | Product photo URL for placement in a lifestyle scene; the image must be jpeg, jpg, png, webp and no larger than 12 MB. If an `image_file` is also supplied, `image_url` takes priority. |
| `scene_description` |  | string \| null | no |  |  | English-only prompt without special characters, describing the scene or background to create for the supplied product photo. |
| `ref_image_url` |  | string (image URL) | no | `` |  | Reference image URL for generating a product shot's new background or scene, with jpeg, jpg, png, and webp supported. Supply exactly one of `scene_description` or `ref_image_url`; an empty URL is written as "". When `ref_image_file` is also supplied, `ref_image_url` takes precedence. |
| `optimize_description` |  | boolean | no | `true` |  | Whether scene-description optimization is enabled. |
| `num_results` |  | integer | no | `1` | 1 – 4 | Lifestyle product image count per placement (`num_results`). The total is the number of required placements × `num_results` for `placement_type=manual_placement`, or `num_results` × 10 for `placement_type=automatic`. |
| `fast` |  | boolean | no | `true` |  | Controls whether the fast model is selected. |
| `placement_type` |  | enum (string) | no | `manual_placement` | `original`, `automatic`, `manual_placement`, `manual_padding` | Product positioning mode, with two manual options: 'manual_placement' uses predefined positions selected through 'manual_placement_selection', while 'manual_padding' adjusts image position and size through pixel padding around the product. To retain the source position, select 'original'; to generate results across 10 recommended product positions, select 'automatic'. |
| `original_quality` |  | boolean | no | `false` |  | Output sizing option used only with `placement_type=original`: false scales the image to 1 megapixel (1MP) without altering its aspect ratio, while true keeps the input dimensions. |
| `shot_size` |  | array of integer | no | `[1000,1000]` |  | Target dimensions for the final product image, applicable only with placement_type=automatic or placement_type=manual_placement. For best results, aim for approximately 1,000,000 pixels overall. |
| `manual_placement_selection` |  | enum (string) | no | `bottom_center` | `upper_left`, `upper_right`, `bottom_left`, `bottom_right`, `right_center`, `left_center`, `upper_center`, `bottom_center`, `center_vertical`, `center_horizontal` | Preset positions to use when placement_type=manual_placement is selected. Choose from the list; multiple positions may be requested together. |
| `padding_values` |  | array of integer | no |  |  | Pixel padding for `placement_type=manual_padding`, supplied as [left, right, top, bottom]. To choose these values, first obtain a product cutout using the product cutout API and inspect its dimensions, then pass that cutout to this API with the desired padding. Aim for around 1,000,000 total pixels after padding for optimal results. |

File parameters (`image`, `ref_image_url`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/bria/product-shot?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bria/product-shot?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bria/product-shot", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.com/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "bria/product-shot",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "bria/product-shot",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 40,
    "usd": "0.04",
    "charged": 40,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200,
        "width": 1024,
        "height": 768
      }
    ]
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Images produced by the model. |

## Related models

- [Bria Text-to-Image Base](https://doitong.com/developers/models/bria/text-to-image/base.md) (`bria/text-to-image/base`): $0.04 / image
- [Bria Text-to-Image Fast](https://doitong.com/developers/models/bria/text-to-image/fast.md) (`bria/text-to-image/fast`): $0.028 / image
- [Bria Text-to-Image HD](https://doitong.com/developers/models/bria/text-to-image/hd.md) (`bria/text-to-image/hd`): $0.04 / image
- [Bria](https://doitong.com/developers/models/bria/reimagine.md) (`bria/reimagine`): $0.04 / image
- [Bria Background Replace](https://doitong.com/developers/models/bria/background/replace.md) (`bria/background/replace`): $0.04 / image
- [Bria Eraser](https://doitong.com/developers/models/bria/eraser.md) (`bria/eraser`): $0.04 / request
- [Bria Expand Image](https://doitong.com/developers/models/bria/expand.md) (`bria/expand`): $0.04 / request
- [Bria GenFill](https://doitong.com/developers/models/bria/genfill.md) (`bria/genfill`): $0.04 / image

## Links

- HTML page: https://doitong.com/developers/models/bria/product-shot
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=bria/product-shot
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/bria/product-shot