# Birefnet API

> Entfernt Hintergründe aus Videos mit sechs Modelloptionen, Matting sowie mp4-, webm-, mov- oder gif-Ausgabe

Wendet die BiRefNet-Segmentierung auf jedes Bild eines Videos aus `video_url` an. Die Modelle umfassen Light, Light 2K, Heavy, Matting, Portrait und Dynamic, mit Betriebsauflösungen bis 2304x2304 (nur beim Modell Dynamic). Die Ausgabe kann X264 mp4, VP9 webm, ProRes 4444 mov oder GIF sein, mit den Einstellungen `video_quality` und `video_write_mode`. Ein separates Maskenvideo kann angefordert werden.

- 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.com/v1/run/birefnet/v2/video`
- Quote: `POST https://api.doitong.com/v1/quote/birefnet/v2/video`
- Docs page: https://doitong.com/de/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.com/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)` | Auswahl des Modells zur Hintergrundentfernung: 'General Use (Light)' verweist auf BiRefNet, das ursprüngliche Modell des BiRefNet-Repositorys, und wird für die meisten Anwendungsfälle empfohlen. 'General Use (Light 2K)' verweist auf BiRefNet_lite-2K und verwendet dieses ursprüngliche, mit 2K-Bildern trainierte Modell. 'General Use (Heavy)' verweist auf BiRefNet_lite und bietet höhere Genauigkeit bei langsamerer Verarbeitung. 'Matting' verweist auf BiRefNet-matting und wurde speziell für Bild-Matting trainiert. 'Portrait' verweist auf BiRefNet-portrait und wurde speziell mit Porträtbildern trainiert. 'General Use (Dynamic)' verweist auf BiRefNet_dynamic und unterstützt variable Auflösungen von 256x256 bis 2304x2304. |
| `operating_resolution` |  | enum (string) | no | `1024x1024` | `1024x1024`, `2048x2048`, `2304x2304` | Arbeitsauflösung; '2304x2304' ist auf das Modell 'General Use (Dynamic)' beschränkt. Bei hochauflösenden Eingabebildern verbessern höhere Einstellungen die Ausgabequalität. |
| `output_mask` |  | boolean | no | `false` |  | Steuert, ob die Maske zur Hintergrundentfernung in der Ausgabe enthalten ist. |
| `refine_foreground` |  | boolean | no | `true` |  | Steuert die Vordergrundverfeinerung auf Grundlage der geschätzten Maske. |
| `video_url` | `video` | string (video URL) | yes |  |  | URL des Videos, dessen Hintergrund entfernt wird. |
| `video_output_type` |  | enum (string) | no | `X264 (.mp4)` | `X264 (.mp4)`, `VP9 (.webm)`, `PRORES4444 (.mov)`, `GIF (.gif)` | Ausgabetyp des resultierenden Videos. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Qualitätsstufe des resultierenden Videos. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Schreibmodus des resultierenden Videos. |

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.com/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.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/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.com/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.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/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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/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} | Video nach der Hintergrundentfernung. |
| `mask_video` | object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames} \| null | Bei der Hintergrundentfernung angewendete Maske. |

## 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.com/v1/models/birefnet/v2/video