# Sam 3 · Video RLE API

> Videosegmentering med såing fra maske-URL, kontroll av bildeindeks og lavere grense for deteksjonsterskelen

Segmenterer video med SAM 3 ved hjelp av en tekstlig `prompt`, punkt- eller boksmarkører, eller en innledende maske fra `mask_url` brukt på `frame_index`. `detection_threshold` går fra 0.01 til 1, og lavere verdier som 0.2 til 0.3 kan hjelpe når tekstmarkører ikke fungerer. Kan returnere en zip med avgrensningsbokser per bilde via `boundingbox_zip`.

- 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.com/v1/run/sam-3/video-rle`
- Quote: `POST https://api.doitong.com/v1/quote/sam-3/video-rle`
- Docs page: https://doitong.com/no/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.com/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 for segmentering. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | Maske-URL for den innledende applikasjonen. |
| `prompt` |  | string | no | `` |  | Segmenteringsprompt som støtter flere sporede objekter gjennom kommaseparerte beskrivelser, for eksempel 'person, cloth'. |
| `point_prompts` |  | array of object {x, y, label, object_id, frame_index} | no | `[]` |  | Punktpromptliste som angir bildeindekser. |
| `point_prompts[].x` |  | integer \| null | no |  |  | Promptens posisjon langs X-aksen. |
| `point_prompts[].y` |  | integer \| null | no |  |  | Promptens posisjon langs Y-aksen. |
| `point_prompts[].label` |  | enum (integer) \| null | no |  | `0`, `1` | Forgrunns-/bakgrunnsetikett: 1 angir forgrunn; 0 angir bakgrunn. |
| `point_prompts[].object_id` |  | integer \| null | no |  |  | Valgfri identifikator som grupperer prompter som forbedrer ett enkelt objekt. Hvis tekst også oppgis som en prompt, bestemmer denne identifikatoren hvilket registrerte objekt punktene forbedrer. |
| `point_prompts[].frame_index` |  | integer \| null | no |  |  | Indeks som identifiserer bildet for interaksjon. |
| `box_prompts` |  | array of object {x_min, y_min, x_max, y_max, object_id, frame_index} | no | `[]` |  | Bokspromptliste, med en valgfri frame_index for hver oppføring. |
| `box_prompts[].x_min` |  | integer \| null | no |  |  | Minste x-koordinat for boksen. |
| `box_prompts[].y_min` |  | integer \| null | no |  |  | Minste y-koordinat for boksen. |
| `box_prompts[].x_max` |  | integer \| null | no |  |  | Maksimal X-koordinat for boksen. |
| `box_prompts[].y_max` |  | integer \| null | no |  |  | Maksimal Y-koordinat for boksen. |
| `box_prompts[].object_id` |  | integer \| null | no |  |  | Valgfri identifikator som grupperer bokser som forbedrer ett enkelt objekt. |
| `box_prompts[].frame_index` |  | integer \| null | no |  |  | Indeks som identifiserer bildet for interaksjon. |
| `apply_mask` |  | boolean | no | `false` |  | Om maskering skal brukes på videoen. |
| `boundingbox_zip` |  | boolean | no | `false` |  | Om det skal returneres et ZIP-arkiv med overlegg av avgrensningsbokser for hvert bilde. |
| `detection_threshold` |  | number | no | `0.5` | 0.01 – 1 | Grenseverdi for deteksjonskonfidens med standardverdier på 0.5 for eksisterende objekter og 0.7 for nye. Innenfor området 0.0–1.0 gir lavere verdier lavere presisjon, men flere deteksjoner; prøv 0.2–0.3 når tekstprompter mislykkes. |
| `frame_index` |  | integer | no | `0` |  | Indeks for bildet ved innledende interaksjon når mask_url oppgis. |

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/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/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/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/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.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 produsert av segmenteringen. |
| `boundingbox_frames_zip` | object {url, content_type, file_name, file_size} \| null | ZIP-arkiv med overlegg av avgrensningsbokser for hvert bilde. |

## 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.com/v1/models/sam-3/video-rle