# Extract Object API

> Isolates an object named in a text prompt and returns it as a transparent RGBA cutout with its mask

Finds the object described in `prompt` within the image from `image_url` and returns it on a transparent background, together with the segmentation mask. `autocrop` tightens the canvas to the object. `remove_background` refines the cutout edge with background removal instead of using the segmentation mask alone. If nothing matches, the full input image is returned.

- 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/en-US/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` |  | Source image supplied through a public URL, raw base64-encoded image bytes, or a base64 data URI such as data:image/png;base64,... . |
| `prompt` |  | string | no | `yellow hammer` |  | Object to act on, described in natural language, such as 'the red car'. |
| `autocrop` |  | boolean | no | `false` |  | Crop the output canvas to fit the extracted object. |
| `remove_background` |  | boolean | no | `false` |  | Cutout alpha refinement switch. The default, False, skips salient-object matting and takes alpha directly from SAM segmentation, making processing faster and helping preserve text, logos, or graphics that RMBG might trim excessively. Set True to refine alpha using RMBG background removal. |

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} | Full source image if the prompt finds no matching object; otherwise, an RGBA result with the extracted object surrounded by transparency. |
| `mask` | object {url, content_type, file_name, file_size, width, height} | Extraction mask whose no-match fallback depends on the input: RGBA images supply their alpha channel, while all other images produce an entirely white mask. |

## 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