# Bria Product Shot API

> 텍스트 설명 또는 참조 이미지에서 제품을 새로운 라이프스타일 장면에 배치하고 위치를 제어합니다

`image_url`의 제품을 `scene_description`으로 설명된 장면 또는 `ref_image_url`에 표시된 장면에 배치합니다. 둘 다 사용할 수는 없습니다. `placement_type`은 original, automatic, manual_placement, manual_padding 중 하나이며, `manual_placement_selection`에는 10개의 위치가 있습니다. `shot_size`는 약 1,000,000픽셀입니다. `num_results`는 1~4 범위이며 `fast` 모드를 사용할 수 있습니다.

- 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/ko/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 |  |  | 라이프스타일 장면에 배치할 상품 사진 URL입니다. 이미지는 jpeg, jpg, png, webp 형식이어야 하며 12 MB 이하여야 합니다. `image_file`도 제공하면 `image_url`이 우선합니다. |
| `scene_description` |  | string \| null | no |  |  | 제공된 상품 사진에 생성할 장면 또는 배경을 설명하는 특수 문자 없는 영어 전용 프롬프트입니다. |
| `ref_image_url` |  | string (image URL) | no | `` |  | 상품 사진의 새 배경 또는 장면 생성에 사용할 참조 이미지 URL입니다. jpeg, jpg, png, webp를 지원합니다. `scene_description` 또는 `ref_image_url` 중 정확히 하나를 제공해야 하며, 빈 URL은 ""로 작성합니다. `ref_image_file`도 제공하면 `ref_image_url`이 우선합니다. |
| `optimize_description` |  | boolean | no | `true` |  | 장면 설명 최적화의 활성화 여부입니다. |
| `num_results` |  | integer | no | `1` | 1 – 4 | 배치당 라이프스타일 상품 이미지 수(`num_results`)입니다. 총 개수는 `placement_type=manual_placement`일 때 필요한 배치 수 × `num_results`, `placement_type=automatic`일 때 `num_results` × 10입니다. |
| `fast` |  | boolean | no | `true` |  | 빠른 모델을 선택할지 제어합니다. |
| `placement_type` |  | enum (string) | no | `manual_placement` | `original`, `automatic`, `manual_placement`, `manual_padding` | 상품 배치 모드입니다. 수동 옵션은 두 가지입니다. 'manual_placement'는 'manual_placement_selection'으로 선택한 사전 정의 위치를 사용하고, 'manual_padding'은 상품 주변의 픽셀 패딩으로 이미지 위치와 크기를 조정합니다. 원본 위치를 유지하려면 'original'을, 권장 상품 위치 10곳에서 결과를 생성하려면 'automatic'을 선택합니다. |
| `original_quality` |  | boolean | no | `false` |  | `placement_type=original`에서만 사용하는 출력 크기 옵션입니다. false이면 가로세로 비율을 변경하지 않고 이미지를 1 메가픽셀(1MP)로 조정하며, true이면 입력 크기를 유지합니다. |
| `shot_size` |  | array of integer | no | `[1000,1000]` |  | 최종 상품 이미지의 대상 치수입니다. placement_type=automatic 또는 placement_type=manual_placement에서만 적용됩니다. 최상의 결과를 위해 전체 약 1,000,000픽셀을 목표로 하세요. |
| `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` | placement_type=manual_placement 선택 시 사용할 사전 설정 위치입니다. 목록에서 선택하며 여러 위치를 함께 요청할 수 있습니다. |
| `padding_values` |  | array of integer | no |  |  | `placement_type=manual_padding`에 사용할 픽셀 패딩이며 [left, right, top, bottom] 순서로 제공합니다. 값을 정하려면 먼저 product cutout API로 상품 컷아웃을 얻어 치수를 확인한 후, 원하는 패딩과 함께 이 API에 전달하세요. 최적의 결과를 위해 패딩 후 총 약 1,000,000픽셀을 목표로 하세요. |

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} | 모델이 생성한 이미지입니다. |

## 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