# Sam 3 · Video RLE API

> Video segmentēšana ar maskas URL sēšanu, kadra indeksa vadību un zemāku noteikšanas sliekšņa minimumu

Segmentē video ar SAM 3, izmantojot teksta `prompt`, punkta vai kastes uzvednes vai sākotnējo masku no `mask_url`, kas lietota pie `frame_index`. `detection_threshold` ir no 0.01 līdz 1, un zemākas vērtības, piemēram, 0.2 līdz 0.3, var palīdzēt, ja teksta uzvednes nedarbojas. Var atgriezt katra kadra ierobežkastes zip arhīvu ar `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/lv/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 segmentēšanai. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | Maskas URL sākotnējai lietošanai. |
| `prompt` |  | string | no | `` |  | Segmentēšanas uzvedne, kas atbalsta vairākus izsekojamos objektus, izmantojot ar komatiem atdalītus aprakstus, piemēram, 'person, cloth'. |
| `point_prompts` |  | array of object {x, y, label, object_id, frame_index} | no | `[]` |  | Punktu uzvedņu saraksts, kas norāda kadru indeksus. |
| `point_prompts[].x` |  | integer \| null | no |  |  | Uzvednes pozīcija gar X asi. |
| `point_prompts[].y` |  | integer \| null | no |  |  | Uzvednes pozīcija gar Y asi. |
| `point_prompts[].label` |  | enum (integer) \| null | no |  | `0`, `1` | Priekšplāna/fona etiķete: 1 norāda priekšplānu, 0 — fonu. |
| `point_prompts[].object_id` |  | integer \| null | no |  |  | Neobligāts identifikators, kas grupē vienu objektu precizējošās uzvednes. Ja kā uzvedne tiek norādīts arī teksts, šis identifikators nosaka, kuru atklāto objektu šie punkti precizē. |
| `point_prompts[].frame_index` |  | integer \| null | no |  |  | Mijiedarbības kadru identificējošais indekss. |
| `box_prompts` |  | array of object {x_min, y_min, x_max, y_max, object_id, frame_index} | no | `[]` |  | Rāmju uzvedņu saraksts ar neobligātu frame_index katram ierakstam. |
| `box_prompts[].x_min` |  | integer \| null | no |  |  | Taisnstūra minimālā x koordināta. |
| `box_prompts[].y_min` |  | integer \| null | no |  |  | Taisnstūra minimālā y koordināta. |
| `box_prompts[].x_max` |  | integer \| null | no |  |  | Kastes maksimālā X koordināta. |
| `box_prompts[].y_max` |  | integer \| null | no |  |  | Kastes maksimālā Y koordināta. |
| `box_prompts[].object_id` |  | integer \| null | no |  |  | Neobligāts identifikators, kas grupē vienu objektu precizējošās kastes. |
| `box_prompts[].frame_index` |  | integer \| null | no |  |  | Mijiedarbības kadru identificējošais indekss. |
| `apply_mask` |  | boolean | no | `false` |  | Vai videoklipam lietot maskēšanu. |
| `boundingbox_zip` |  | boolean | no | `false` |  | Vai atgriezt ZIP arhīvu ar katra kadra ierobežojošo rāmju pārklājumiem. |
| `detection_threshold` |  | number | no | `0.5` | 0.01 – 1 | Noteikšanas ticamības slieksnis ar noklusējuma vērtību 0.5 esošajiem objektiem un 0.7 jaunajiem objektiem. Diapazonā 0.0–1.0 mazākas vērtības samazina precizitāti, bet palielina noteikšanu skaitu; ja teksta uzvednes nedarbojas, izmēģiniet 0.2–0.3. |
| `frame_index` |  | integer | no | `0` |  | Kadru indekss sākotnējai mijiedarbībai, piegādājot 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.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} | Segmentēšanas rezultātā iegūtais video. |
| `boundingbox_frames_zip` | object {url, content_type, file_name, file_size} \| null | ZIP arhīvs ar katra kadra ierobežojošo rāmju pārklājumiem. |

## 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