# Birefnet API

> چھ ماڈل اختیارات، matting، اور mp4، webm، mov یا gif آؤٹ پٹ کے ساتھ ویڈیو سے پس منظر ہٹاتا ہے

`video_url` سے ویڈیو کے ہر فریم پر BiRefNet سیگمینٹیشن لاگو کرتا ہے۔ ماڈلز میں Light، Light 2K، Heavy، Matting، Portrait اور Dynamic شامل ہیں، جن کے آپریٹنگ ریزولوشنز 2304x2304 تک ہیں (صرف Dynamic ماڈل کے لیے)۔ آؤٹ پٹ X264 mp4، VP9 webm، ProRes 4444 mov یا GIF ہو سکتا ہے، جس میں `video_quality` اور `video_write_mode` ترتیبات شامل ہیں۔ الگ ماسک ویڈیو بھی طلب کی جا سکتی ہے۔

- Model id: `birefnet/v2/video`
- Made by: BiRefNet
- Category: Background Removal
- Output: video
- Charged by usage (up to $2.07 per run, typical $0.007; the rest of the hold is refunded): $0.000575 / second of processing time (cheapest run $0.007 (7 API credits))
- Run: `POST https://api.doitong.ru/v1/run/birefnet/v2/video`
- Quote: `POST https://api.doitong.ru/v1/quote/birefnet/v2/video`
- Docs page: https://doitong.com/ur/developers/models/birefnet/v2/video

## Pricing

Price: **$0.000575 / second of processing time**. Charged by actual usage at $0.000575 / second of processing time: up to $2.07 per run (the quote gives the maximum for your input), the rest is refunded automatically after the run. A typical run costs $0.007.

The full example input below holds up to $2.07 = 2070 API credits (up to 3600 s of processing time × $0.000575) when it starts; a typical run costs $0.007 (7 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). This model is charged by usage: `POST https://api.doitong.ru/v1/quote/birefnet/v2/video` with the same JSON body returns the most the run can cost for that input (`credits`, debited when the run starts); after the run you pay the usage the model reports and the rest is refunded automatically. An input whose maximum would exceed the per-run limit is refused with 422. 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۔ |
| `video_url` | `video` | string (video URL) | yes |  |  | اس ویڈیو کی شناخت کرنے والا URL جس کا پس منظر ہٹایا جائے گا۔ |
| `video_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | حاصل ہونے والی ویڈیو کی آؤٹ پٹ قسم۔ |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | حاصل ہونے والی ویڈیو کا معیار۔ |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | حاصل ہونے والی ویڈیو کا رائٹ موڈ۔ |

File parameters (`video`) 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
{
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

A fuller example:

```json
{
  "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

## 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.ru/v1/run/birefnet/v2/video?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }'

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

### JavaScript

```javascript
const API = "https://api.doitong.ru/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/video?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }),
});
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.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/birefnet/v2/video", 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.ru/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/video",
      "input": {
        "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
      },
      "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/video",
  "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": 2070,
    "usd": "2.07",
    "charged": 2070,
    "refunded": 0
  },
  "input": {
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "fps": 1.0,
      "duration": 5,
      "num_frames": 1
    },
    "mask_video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "fps": 1.0,
      "duration": 5,
      "num_frames": 1
    }
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames} | پس منظر ہٹانے کے بعد کی ویڈیو۔ |
| `mask_video` | object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames} \| null | پس منظر ہٹانے کے دوران لاگو کیا جانے والا ماسک۔ |

## Related models

- [BiRefNet V2 Background Removal](https://doitong.com/developers/models/birefnet/v2.md) (`birefnet/v2`): $0.002 / run
- [Bria RMBG 2.0](https://doitong.com/developers/models/bria/background/remove.md) (`bria/background/remove`): from $0.018 / request
- [Birefnet Background Removal](https://doitong.com/developers/models/birefnet.md) (`birefnet`): $0.002 / run
- [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/video
- 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/video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/birefnet/v2/video