# Sam 3 1 · Video RLE API

> Segmentazione video con SAM 3.1, maschere RLE, inizializzazione della maschera e maschere opzionali per oggetto e fotogramma

Segmenta video con SAM 3.1, inizializzato da un `prompt` testuale, da prompt puntuali o rettangolari oppure da un `mask_url` applicato a `frame_index`. `max_num_objects` consente di tracciare da 1 a 128 oggetti. Imposta `return_object_rles` per ottenere la maschera di ciascun oggetto tracciato per ogni fotogramma, con un ID stabile. `detection_threshold` va da 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/it/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 per la segmentazione. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL della maschera per l'applicazione iniziale. |
| `prompt` |  | string | no | `` |  | Prompt di segmentazione che supporta più oggetti tracciati tramite descrizioni separate da virgole, come 'person, cloth'. |
| `point_prompts` |  | array of object {x, y, label, object_id, frame_index} | no | `[]` |  | Elenco di prompt punto che specifica gli indici dei fotogrammi. |
| `point_prompts[].x` |  | integer \| null | no |  |  | Posizione del prompt lungo l'asse X. |
| `point_prompts[].y` |  | integer \| null | no |  |  | Posizione del prompt lungo l'asse Y. |
| `point_prompts[].label` |  | enum (integer) \| null | no |  | `0`, `1` | Etichetta primo piano/sfondo: 1 indica il primo piano; 0 indica lo sfondo. |
| `point_prompts[].object_id` |  | integer \| null | no |  |  | Identificatore facoltativo che raggruppa i prompt che perfezionano un singolo oggetto. Se viene fornito anche testo come prompt, questo identificatore determina quale oggetto rilevato viene perfezionato da quei punti. |
| `point_prompts[].frame_index` |  | integer \| null | no |  |  | Indice che identifica il fotogramma per l'interazione. |
| `box_prompts` |  | array of object {x_min, y_min, x_max, y_max, object_id, frame_index} | no | `[]` |  | Elenco di prompt riquadro, con un frame_index facoltativo per ogni voce. |
| `box_prompts[].x_min` |  | integer \| null | no |  |  | Coordinata x minima del riquadro. |
| `box_prompts[].y_min` |  | integer \| null | no |  |  | Coordinata y minima del riquadro. |
| `box_prompts[].x_max` |  | integer \| null | no |  |  | Coordinata X massima del riquadro. |
| `box_prompts[].y_max` |  | integer \| null | no |  |  | Coordinata Y massima del riquadro. |
| `box_prompts[].object_id` |  | integer \| null | no |  |  | Identificatore facoltativo che raggruppa i riquadri che perfezionano un singolo oggetto. |
| `box_prompts[].frame_index` |  | integer \| null | no |  |  | Indice che identifica il fotogramma per l'interazione. |
| `apply_mask` |  | boolean | no | `false` |  | Indica se applicare la mascheratura al video. |
| `boundingbox_zip` |  | boolean | no | `false` |  | Indica se restituire un archivio ZIP contenente le sovrapposizioni dei riquadri per ogni fotogramma. |
| `detection_threshold` |  | number | no | `0.5` | 0.01 – 1 | Soglia di confidenza del rilevamento, con valori predefiniti di 0.5 per gli oggetti esistenti e 0.7 per quelli nuovi. Nell'intervallo 0.0–1.0, valori inferiori sacrificano la precisione per ottenere più rilevamenti; prova 0.2–0.3 quando i prompt testuali non funzionano. |
| `frame_index` |  | integer | no | `0` |  | Indice del fotogramma per l'interazione iniziale quando si fornisce mask_url. |
| `max_num_objects` |  | integer | no | `16` | 1 – 128 | Limite massimo al numero di oggetti tracciati nel video. |
| `return_object_rles` |  | boolean | no | `false` |  | Indica se restituire anche una maschera separata per ogni oggetto tracciato in ogni fotogramma, usando un ID oggetto stabile per tutto il video. La risposta include comunque l'rle unificato. |

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 prodotto dalla segmentazione. |
| `boundingbox_frames_zip` | object {url, content_type, file_name, file_size} \| null | Archivio ZIP delle sovrapposizioni dei riquadri per ogni fotogramma. |

## 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