# Extract Object API

> Mengisolasi objek yang disebutkan dalam prompt teks dan mengembalikannya sebagai cutout RGBA transparan beserta mask-nya

Menemukan objek yang dijelaskan dalam `prompt` di dalam gambar dari `image_url` dan mengembalikannya pada latar transparan, bersama mask segmentasi. `autocrop` mempersempit kanvas ke objek. `remove_background` menyempurnakan tepi cutout dengan penghapusan latar, bukan hanya menggunakan mask segmentasi. Jika tidak ada yang cocok, seluruh gambar input dikembalikan.

- Model id: `bria/extract-object`
- Made by: Bria AI
- Category: Image Editing
- Output: image
- Price: $0.02 / image (cheapest run $0.02 (20 API credits))
- Run: `POST https://api.doitong.com/v1/run/bria/extract-object`
- Quote: `POST https://api.doitong.com/v1/quote/bria/extract-object`
- Docs page: https://doitong.com/id/developers/models/bria/extract-object

## Pricing

Price: **$0.02 / image**. Billed per generated image.

The full example input below costs $0.02 = 20 API credits (1 image × 20 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/extract-object` 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) | no | `https://bria-datasets.s3.amazonaws.com/object-extraction/tools_construction_flatlay.jpg` |  | Gambar sumber yang diberikan melalui URL publik, byte gambar mentah yang dienkode base64, atau URI data base64 seperti data:image/png;base64,... . |
| `prompt` |  | string | no | `yellow hammer` |  | Objek yang akan diproses, dideskripsikan dalam bahasa alami, seperti 'the red car'. |
| `autocrop` |  | boolean | no | `false` |  | Pangkas kanvas output agar sesuai dengan objek yang diekstrak. |
| `remove_background` |  | boolean | no | `false` |  | Sakelar penyempurnaan alfa cutout. Bawaan, False, melewati matting objek menonjol dan mengambil alfa langsung dari segmentasi SAM, sehingga pemrosesan lebih cepat serta membantu mempertahankan teks, logo, atau grafik yang mungkin dipangkas berlebihan oleh RMBG. Atur ke True untuk menyempurnakan alfa menggunakan penghapusan latar belakang RMBG. |

File parameters (`image`) 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
{}
```

A fuller example:

```json
{
  "prompt": "yellow hammer"
}
```

## 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/extract-object?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "yellow hammer"
  }'

# 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/extract-object?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "yellow hammer"
  }),
});
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 = {
    "prompt": "yellow hammer",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bria/extract-object", 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/extract-object",
      "input": {
        "prompt": "yellow hammer"
      },
      "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/extract-object",
  "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": 20,
    "usd": "0.02",
    "charged": 20,
    "refunded": 0
  },
  "input": {
    "prompt": "yellow hammer"
  },
  "output": {
    "image": {
      "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
    },
    "mask": {
      "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 |
|---|---|---|
| `image` | object {url, content_type, file_name, file_size, width, height} | Gambar sumber penuh jika prompt tidak menemukan objek yang cocok; jika tidak, hasil RGBA dengan objek yang diekstrak dikelilingi transparansi. |
| `mask` | object {url, content_type, file_name, file_size, width, height} | Mask ekstraksi yang fallback tanpa kecocokan bergantung pada input: gambar RGBA menyediakan kanal alfanya, sedangkan semua gambar lain menghasilkan mask putih sepenuhnya. |

## 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/extract-object
- 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/extract-object
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/bria/extract-object