# BiRefNet V2 Background Removal API

> 2304 px تک کھلے پس منظر ہٹانے اور میٹنگ کی سہولت، اختیاری ماسک آؤٹ پٹ کے ساتھ۔

BiRefNet V2 متعدد ماڈل ویریئنٹس (light، heavy، matting، portrait، dynamic) اور 2304x2304 تک آپریٹنگ ریزولوشنز کے ذریعے موضوع کو پس منظر سے الگ کرتا ہے۔ کٹ آؤٹ اور اختیاری ماسک PNG، WebP یا GIF میں واپس کرتا ہے۔

- Model id: `birefnet/v2`
- Made by: BiRefNet
- Category: Background Removal
- Output: image
- Estimated price per run: $0.002 / run (cheapest run $0.002 (2 API credits))
- Run: `POST https://api.doitong.com/v1/run/birefnet/v2`
- Quote: `POST https://api.doitong.com/v1/quote/birefnet/v2`
- Docs page: https://doitong.com/ur/developers/models/birefnet/v2

## Pricing

Price: **$0.002 / run**. Estimated from the typical cost of one run. The quote is exactly what the run charges.

The full example input below costs $0.002 = 2 API credits (1 request × 2 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/birefnet/v2` 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 |
|---|---|---|---|---|---|---|
| `model` |  | enum (string) | no | `General Use (Light)` | `General Use (Light)`, `General Use (Light 2K)`, `General Use (Heavy)`, `Matting`, `Portrait`, `General Use (Dynamic)` | پس منظر ہٹانے والے ماڈل کا انتخاب: 'General Use (Light)'، BiRefNet سے مطابقت رکھتا ہے، BiRefNet ریپوزٹری کا اصل ماڈل ہے اور زیادہ تر استعمالات کے لیے تجویز کیا جاتا ہے۔ 'General Use (Light 2K)'، BiRefNet_lite-2K سے مطابقت رکھتا ہے اور 2K تصاویر پر تربیت یافتہ اصل ماڈل استعمال کرتا ہے۔ 'General Use (Heavy)'، BiRefNet_lite سے مطابقت رکھتا ہے اور سست پروسیسنگ کے عوض زیادہ درستگی فراہم کرتا ہے۔ 'Matting'، BiRefNet-matting سے مطابقت رکھتا ہے اور خاص طور پر امیج میٹنگ کے لیے تربیت یافتہ ہے۔ 'Portrait'، BiRefNet-portrait سے مطابقت رکھتا ہے اور خاص طور پر پورٹریٹ تصاویر پر تربیت یافتہ ہے۔ 'General Use (Dynamic)'، BiRefNet_dynamic سے مطابقت رکھتا ہے اور 256x256 سے 2304x2304 تک متغیر ریزولوشنز کی معاونت کرتا ہے۔ |
| `operating_resolution` |  | enum (string) | no | `1024x1024` | `1024x1024`, `2048x2048`, `2304x2304` | ورکنگ ریزولوشن؛ '2304x2304' صرف 'General Use (Dynamic)' ماڈل تک محدود ہے۔ ہائی ریزولوشن ان پٹ تصاویر کے لیے زیادہ سیٹنگز آؤٹ پٹ کی درستگی بہتر کرتی ہیں۔ |
| `output_mask` |  | boolean | no | `false` |  | کنٹرول کرتا ہے کہ پس منظر ہٹانے کا ماسک آؤٹ پٹ میں شامل ہو یا نہیں۔ |
| `refine_foreground` |  | boolean | no | `true` |  | تخمینی ماسک کی بنیاد پر پیش منظر کی اصلاح کو کنٹرول کرتا ہے۔ |
| `image_url` | `image` | string (image URL) | yes |  |  | اس تصویر کی شناخت کرنے والا URL جس کا پس منظر ہٹایا جائے گا۔ |
| `output_format` |  | enum (string) | no | `png` | `webp`, `png`, `gif` | حاصل ہونے والی تصویر کا فارمیٹ۔ |
| `mask_only` |  | boolean | no | `false` |  | صرف ماسک آؤٹ پٹ سوئچ: `True` پیش منظر کی اصلاح کو نظرانداز کرتا ہے اور تصویر کو بغیر تبدیلی کے رکھتے ہوئے صرف اس کا سیگمنٹیشن ماسک واپس کرتا ہے۔ |

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

A fuller example:

```json
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.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/birefnet/v2?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.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/birefnet/v2?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.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": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/birefnet/v2", 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": "birefnet/v2",
      "input": {
        "image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.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": "birefnet/v2",
  "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": 2,
    "usd": "0.002",
    "charged": 2,
    "refunded": 0
  },
  "input": {
    "image": "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
  },
  "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_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
    }
  },
  "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} | پس منظر ہٹانے کے بعد کی تصویر، یا `mask_only` کے `True` ہونے پر سیگمنٹیشن ماسک۔ |
| `mask_image` | object {url, content_type, file_name, file_size, width, height} \| null | پس منظر ہٹانے کے دوران لاگو کیا جانے والا ماسک۔ |

## Related models

- [Birefnet Background Removal](https://doitong.com/developers/models/birefnet.md) (`birefnet`): $0.002 / run
- [Bria RMBG 2.0](https://doitong.com/developers/models/bria/background/remove.md) (`bria/background/remove`): from $0.018 / request
- [Birefnet](https://doitong.com/developers/models/birefnet/v2/video.md) (`birefnet/v2/video`): $0.000575 / second of processing time
- [ben-v2-image](https://doitong.com/developers/models/ben/v2/image.md) (`ben/v2/image`): $0.102 / run
- [Ben-Video-Bg-Rm](https://doitong.com/developers/models/ben/v2/video.md) (`ben/v2/video`): $0.001 / megapixel of input video
- [Bria Guided Remove Background](https://doitong.com/developers/models/bria/guided-remove-background.md) (`bria/guided-remove-background`): $0.03 / image
- [Bria's VRMBG 3.0](https://doitong.com/developers/models/bria/video/background-removal/v3.md) (`bria/video/background-removal/v3`): $0.05 / second of input video
- [Feynobg Background Remover](https://doitong.com/developers/models/feynobg.md) (`feynobg`): $0.001 / request

## Links

- HTML page: https://doitong.com/developers/models/birefnet/v2
- 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=birefnet/v2
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/birefnet/v2