# Sam 3 1 · Video RLE API

> Segmentación de vídeo con SAM 3.1 y máscaras RLE, inicialización de máscaras y máscaras opcionales por objeto y fotograma

Segmenta vídeos con SAM 3.1, inicializados mediante un `prompt` de texto, prompts de puntos o cuadros, o un `mask_url` aplicado en `frame_index`. `max_num_objects` permite rastrear de 1 a 128 objetos. Establece `return_object_rles` para obtener la máscara propia de cada objeto rastreado en cada fotograma con un ID estable. `detection_threshold` varía de 0.01 a 1.

- Model id: `sam-3-1/video-rle`
- Made by: Meta
- Category: Video to Video
- Output: video
- Price per 16 frames of your input video: $0.01 / 16 frames of input video (cheapest run $0.01 (10 API credits))
- Run: `POST https://api.doitong.com/v1/run/sam-3-1/video-rle`
- Quote: `POST https://api.doitong.com/v1/quote/sam-3-1/video-rle`
- Docs page: https://doitong.com/es/developers/models/sam-3-1/video-rle

## Pricing

Price: **$0.01 / 16 frames of input video**. Price per 16 frames of your input video: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $0.19 = 190 API credits (19 × 16 frames input video × $0.01).

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/sam-3-1/video-rle` 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 |
|---|---|---|---|---|---|---|
| `video_url` | `video` | string (video URL) | yes |  |  | URL del video para la segmentación. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL de la máscara para la aplicación inicial. |
| `prompt` |  | string | no | `` |  | Prompt de segmentación compatible con varios objetos rastreados mediante descripciones separadas por comas, como 'person, cloth'. |
| `point_prompts` |  | array of object {x, y, label, object_id, frame_index} | no | `[]` |  | Lista de prompts de puntos que especifica los índices de los fotogramas. |
| `point_prompts[].x` |  | integer \| null | no |  |  | Posición del prompt en el eje X. |
| `point_prompts[].y` |  | integer \| null | no |  |  | Posición del prompt en el eje Y. |
| `point_prompts[].label` |  | enum (integer) \| null | no |  | `0`, `1` | Etiqueta de primer plano/fondo: 1 indica primer plano; 0 indica fondo. |
| `point_prompts[].object_id` |  | integer \| null | no |  |  | Identificador opcional que agrupa prompts que refinan un único objeto. Si también se proporciona texto como prompt, este identificador determina qué objeto detectado refinan esos puntos. |
| `point_prompts[].frame_index` |  | integer \| null | no |  |  | Índice que identifica el fotograma para la interacción. |
| `box_prompts` |  | array of object {x_min, y_min, x_max, y_max, object_id, frame_index} | no | `[]` |  | Lista de prompts de cuadros, con un frame_index opcional para cada entrada. |
| `box_prompts[].x_min` |  | integer \| null | no |  |  | Coordenada x mínima del cuadro. |
| `box_prompts[].y_min` |  | integer \| null | no |  |  | Coordenada y mínima del cuadro. |
| `box_prompts[].x_max` |  | integer \| null | no |  |  | Coordenada X máxima del recuadro. |
| `box_prompts[].y_max` |  | integer \| null | no |  |  | Coordenada Y máxima del recuadro. |
| `box_prompts[].object_id` |  | integer \| null | no |  |  | Identificador opcional que agrupa recuadros que refinan un único objeto. |
| `box_prompts[].frame_index` |  | integer \| null | no |  |  | Índice que identifica el fotograma para la interacción. |
| `apply_mask` |  | boolean | no | `false` |  | Indica si se debe aplicar el enmascaramiento al video. |
| `boundingbox_zip` |  | boolean | no | `false` |  | Indica si se debe devolver un archivo ZIP que contenga superposiciones de cuadros delimitadores para cada fotograma. |
| `detection_threshold` |  | number | no | `0.5` | 0.01 – 1 | Umbral de confianza de detección, con valores predeterminados de 0.5 para objetos existentes y 0.7 para objetos nuevos. Dentro del rango 0.0–1.0, los valores más pequeños reducen la precisión a cambio de más detecciones; prueba con 0.2–0.3 cuando fallen los prompts de texto. |
| `frame_index` |  | integer | no | `0` |  | Índice del fotograma para la interacción inicial al proporcionar mask_url. |
| `max_num_objects` |  | integer | no | `16` | 1 – 128 | Límite superior del número de objetos que se rastrean en el video. |
| `return_object_rles` |  | boolean | no | `false` |  | Indica si también se debe devolver una máscara independiente por cada objeto rastreado en cada fotograma, usando un ID de objeto estable durante todo el video. La respuesta sigue incluyendo el rle combinado. |

File parameters (`video`, `mask`) 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/sam-3-1/video-rle?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/sam-3-1/video-rle?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/sam-3-1/video-rle", 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": "sam-3-1/video-rle",
      "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": "sam-3-1/video-rle",
  "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": 190,
    "usd": "0.19",
    "charged": 190,
    "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
    },
    "boundingbox_frames_zip": {
      "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
    }
  },
  "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} | Video producido mediante segmentación. |
| `boundingbox_frames_zip` | object {url, content_type, file_name, file_size} \| null | Archivo ZIP con superposiciones de cuadros delimitadores para cada fotograma. |

## Related models

- [Sam 3 1 · Image](https://doitong.com/developers/models/sam-3-1/image.md) (`sam-3-1/image`): $0.01 / run
- [Sam 3 1 · Image RLE](https://doitong.com/developers/models/sam-3-1/image-rle.md) (`sam-3-1/image-rle`): $0.01 / run
- [Sam 3 1 · Video](https://doitong.com/developers/models/sam-3-1/video.md) (`sam-3-1/video`): $0.01 / 16 frames of input video
- [Sam 3 · Video](https://doitong.com/developers/models/sam-3/video.md) (`sam-3/video`): $0.005 / 16 frames of input video
- [Sam 3 · Video RLE](https://doitong.com/developers/models/sam-3/video-rle.md) (`sam-3/video-rle`): $0.005 / 16 frames of input video
- [Segment Anything Model 2 · Video](https://doitong.com/developers/models/sam2/video.md) (`sam2/video`): $0.001111 / second of processing time
- [AMT Interpolation](https://doitong.com/developers/models/amt-interpolation.md) (`amt-interpolation`): $0.000575 / second of processing time
- [AnimateDiff Turbo · Video to Video](https://doitong.com/developers/models/fast-animatediff/turbo/video-to-video.md) (`fast-animatediff/turbo/video-to-video`): $0.00125 / second of processing time

## Links

- HTML page: https://doitong.com/developers/models/sam-3-1/video-rle
- 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=sam-3-1/video-rle
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/sam-3-1/video-rle