# Sam 3 · Video RLE API

> Video-Segmentéierung mat Mask-URL-Saat, Kontroll iwwer de Frame-Index an enger méi niddereger Detektiounsschwell

Segmentéiert Videoe mat SAM 3 iwwer en Text-`prompt`, Punkt- oder Box-Prompts oder eng initial Mask aus `mask_url`, déi bei `frame_index` ugewannt gëtt. `detection_threshold` geet vun 0.01 bis 1; méi niddreg Wäerter wéi 0.2 bis 0.3 kënne hëllefen, wann Text-Prompts feelen. Kann e ZIP mat Bounding-Boxe pro Frame iwwer `boundingbox_zip` zeréckginn.

- Model id: `sam-3/video-rle`
- Made by: Meta
- Category: Video to Video
- Output: video
- Price per 16 frames of your input video: $0.005 / 16 frames of input video (cheapest run $0.005 (5 API credits))
- Run: `POST https://api.doitong.ru/v1/run/sam-3/video-rle`
- Quote: `POST https://api.doitong.ru/v1/quote/sam-3/video-rle`
- Docs page: https://doitong.com/lb/developers/models/sam-3/video-rle

## Pricing

Price: **$0.005 / 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 $0.095 = 95 API credits (19 × 16 frames input video × $0.005).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.ru/v1/quote/sam-3/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 |  |  | Video-URL fir Segmentéierung. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | Mask-URL fir déi initial Uwendung. |
| `prompt` |  | string | no | `` |  | Segmentéierungs-Prompt, deen e puer verfollegt Objekter duerch komma-getrennte Beschreiwungen ënnerstëtzt, wéi 'person, cloth'. |
| `point_prompts` |  | array of object {x, y, label, object_id, frame_index} | no | `[]` |  | Lëscht vu Punkt-Prompts, déi Frame-Indexen uginn. |
| `point_prompts[].x` |  | integer \| null | no |  |  | Prompt-Positioun op der X-Achs. |
| `point_prompts[].y` |  | integer \| null | no |  |  | Prompt-Positioun op der Y-Achs. |
| `point_prompts[].label` |  | enum (integer) \| null | no |  | `0`, `1` | Label fir Virder- oder Hannergrond: 1 bedeit Virdergrond; 0 bedeit Hannergrond. |
| `point_prompts[].object_id` |  | integer \| null | no |  |  | Optionalen Identifikator, deen Prompts gruppéiert, déi een eenzegen Objet verfeineren. Wann och Text als Prompt geliwwert gëtt, bestëmmt dësen Identifikator, wéi en detektéierten Objet dës Punkten verfeineren. |
| `point_prompts[].frame_index` |  | integer \| null | no |  |  | Index, deen de Frame fir d'Interaktioun identifizéiert. |
| `box_prompts` |  | array of object {x_min, y_min, x_max, y_max, object_id, frame_index} | no | `[]` |  | Lëscht vu Box-Prompts mat engem optionalen frame_index fir all Element. |
| `box_prompts[].x_min` |  | integer \| null | no |  |  | Minimum-x-Koordinate vun der Këscht. |
| `box_prompts[].y_min` |  | integer \| null | no |  |  | Minimum-y-Koordinate vun der Këscht. |
| `box_prompts[].x_max` |  | integer \| null | no |  |  | Maximal X-Koordinat vun der Box. |
| `box_prompts[].y_max` |  | integer \| null | no |  |  | Maximal Y-Koordinat vun der Box. |
| `box_prompts[].object_id` |  | integer \| null | no |  |  | Optionalen Identifikator, deen Boxe gruppéiert, déi een eenzegen Objet verfeineren. |
| `box_prompts[].frame_index` |  | integer \| null | no |  |  | Index, deen de Frame fir d'Interaktioun identifizéiert. |
| `apply_mask` |  | boolean | no | `false` |  | Ob Maskéierung op de Video applizéiert soll ginn. |
| `boundingbox_zip` |  | boolean | no | `false` |  | Ob en ZIP-Archiv mat Bounding-Box-Overlays fir all Frame zeréckginn soll ginn. |
| `detection_threshold` |  | number | no | `0.5` | 0.01 – 1 | Grenzwäert fir d'Detektiouns-Confidence mat Standardwäerter vun 0.5 fir bestoend Objekter an 0.7 fir nei Objekter. Am Beräich 0.0–1.0 tausche méi kleng Wäerter Präzisioun géint méi Detektiounen; probéiert 0.2–0.3, wann Text-Prompts feelen. |
| `frame_index` |  | integer | no | `0` |  | Index vum Frame fir déi initial Interaktioun beim Iwwerginn vun mask_url. |

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.ru/v1/run/sam-3/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.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/sam-3/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.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/sam-3/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.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": "sam-3/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/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": 95,
    "usd": "0.095",
    "charged": 95,
    "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.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} | Video, deen duerch d'Segmentéierung produzéiert gouf. |
| `boundingbox_frames_zip` | object {url, content_type, file_name, file_size} \| null | ZIP-Archiv mat Bounding-Box-Overlays fir all Frame. |

## Related models

- [Sam 3 · Image RLE](https://doitong.com/developers/models/sam-3/image-rle.md) (`sam-3/image-rle`): $0.005 / run
- [Segment Anything Model 3](https://doitong.com/developers/models/sam-3/image.md) (`sam-3/image`): $0.005 / run
- [Sam 3 · Video](https://doitong.com/developers/models/sam-3/video.md) (`sam-3/video`): $0.005 / 16 frames of input video
- [Sam 3 · 3D Body](https://doitong.com/developers/models/sam-3/3d-body.md) (`sam-3/3d-body`): $0.02 / run
- [Sam 3 · 3D Objects](https://doitong.com/developers/models/sam-3/3d-objects.md) (`sam-3/3d-objects`): $0.02 / run
- [Sam 3 · 3D Align](https://doitong.com/developers/models/sam-3/3d-align.md) (`sam-3/3d-align`): $0.02 / run
- [Sam 3 · Image · Embed](https://doitong.com/developers/models/sam-3/image/embed.md) (`sam-3/image/embed`): $0.005 / 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

## Links

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