# VGGT-1B API

> Rekonstruē 3D ainu no līdz 48 attēliem vai video, atgriežot dziļuma kartes, kameras pozas un punktu mākoni

Novērtē ģeometriju no vairākiem skatiem. Norādiet līdz 48 attēliem laukā `image_urls`, pēc izvēles pievienojot `video_url`, kas tiks atlasīts ik pēc `frame_sampling_rate` kadriem. Tas atgriež katra kadra dziļuma kartes, kameras ārējos un iekšējos parametrus, neapstrādātus prognožu failus un GLB punktu mākoni ar kameras konusiem. `confidence_percentile` un `max_points` kontrolē punktu mākoņa blīvumu.

- Model id: `vggt-1b`
- Made by: Meta
- Category: Vision
- Output: json
- Charged by usage (up to $1.755 per run, typical $0.04; the rest of the hold is refunded): $0.000975 / second of processing time (cheapest run $0.04 (40 API credits))
- Run: `POST https://api.doitong.com/v1/run/vggt-1b`
- Quote: `POST https://api.doitong.com/v1/quote/vggt-1b`
- Docs page: https://doitong.com/lv/developers/models/vggt-1b

## Pricing

Price: **$0.000975 / second of processing time**. Charged by actual usage at $0.000975 / second of processing time: up to $1.755 per run (the quote gives the maximum for your input), the rest is refunded automatically after the run. A typical run costs $0.04.

The full example input below holds up to $1.755 = 1755 API credits (up to 1800 s of processing time × $0.000975) when it starts; a typical run costs $0.04 (40 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). This model is charged by usage: `POST https://api.doitong.com/v1/quote/vggt-1b` with the same JSON body returns the most the run can cost for that input (`credits`, debited when the run starts); after the run you pay the usage the model reports and the rest is refunded automatically. An input whose maximum would exceed the per-run limit is refused with 422. 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 |
|---|---|---|---|---|---|---|
| `image_urls` | `images` | array of image URL | no |  | ≤ 48 items | Rekonstrukcijas avota attēli, katrs papildināts līdz kvadrātam un mainīts tā izmērs, lai garākā dimensija būtu 518 pikseļi. Tiek pieņemti JPEG, PNG, WEBP un jebkurš papildu attēla formāts, ko spēj dekodēt Pillow. |
| `video_url` | `video` | string (video URL) \| null | no |  |  | Neobligāts avota video, kura atlasītie kadri seko image_urls apvienotajā ievadē. Atlase izmanto katru `frame_sampling_rate`-to kadru, vienmēr iekļaujot pirmo un pēdējo kadru. |
| `frame_sampling_rate` |  | integer | no | `24` | 1 – 1,000 | Kadru intervāls, kas tiek lietots tikai tad, ja video tiek nodrošināts, izmantojot `video_url`; citādi tam nav ietekmes. Abi robežkadri tiek saglabāti neatkarīgi no intervāla, bet starp tiem tiek atlasīts katrs n-tais kadrs. |
| `alpha_blend_onto` |  | enum (string) | no | `white` | `keep`, `white`, `black`, `mean` | Alfa kanāla apstrādei ir četras izvēles: 'keep' noņem alfa kanālu, nemainot sākotnējās pikseļu vērtības; 'mean' kompozitē pret ImageNet vidējo RGB. Vienkrāsainam fonam izvēlieties 'white' vai 'black', lai kompozitētu pret atbilstošo krāsu. |
| `export_prediction_data` |  | boolean | no | `true` |  | Eksportēt neapstrādātās prognozes kā atsevišķus JSON failus katram kadram. Katrā failā ir dziļums un tā ticamība, maska un kodēta kameras poza. |
| `export_depth_maps` |  | boolean | no | `true` |  | Eksportēt dziļuma rastrus ar `depth_range` lineāru kartējumu uz pikseļu vērtībām 0–65535. Katram kadram tiek izveidots atsevišķs 16 bitu pelēktoņu PNG fails. |
| `export_point_cloud` |  | boolean | no | `true` |  | Eksportēt sapludināto krāsaino punktu mākoni GLB formātā, ainā attēlojot aprēķinātās kameras kā atsevišķus konusa tīklus. |
| `array_encoding` |  | enum (string) | no | `base64` | `base64`, `list` | Prognožu JSON failu masīva krātuves formāts, kur 'list' aizņem daudz vairāk vietas nekā 'base64'. Izvēlieties 'list' ligzdotiem JSON sarakstiem vai 'base64' objektiem, kas satur {data, shape, dtype}. |
| `exclude_keys` |  | array of enum (string) | no |  |  | Atslēgas, kas tiek izslēgtas no katra prognozes JSON faila. |
| `confidence_percentile` |  | number | no | `50` | 0 – 100 | Uz ticamību balstīta filtrēšanas procentuālā vērtība punktu mākoņa izveidei: 0 atspējo filtrēšanu, bet citas vērtības izslēdz norādīto procentu punktu, sākot ar vismazāk ticamajiem. |
| `max_points` |  | integer | no | `250000` | 1,000 – 5,000,000 | GLB punktu skaita ierobežojums, pēc noklusējuma 250,000. Lai samazinātu serializēšanas un augšupielādes aizkavi, ja mākonis pārsniedz šo budžetu, tiek ierakstīta vienmērīgi atlasīta apakškopa. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Ievades attēlu un video drošības pārbaudes slēdzis. |

File parameters (`images`, `video`) 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
{}
```

A fuller example:

```json
{}
```

## 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/vggt-1b?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{}'

# 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/vggt-1b?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({}),
});
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 = {}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/vggt-1b", 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": "vggt-1b",
      "input": {},
      "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": "vggt-1b",
  "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": 1755,
    "usd": "1.755",
    "charged": 1755,
    "refunded": 0
  },
  "input": {},
  "output": {
    "point_cloud": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "depth_maps": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200,
        "width": 1024,
        "height": 768
      }
    ],
    "prediction_data": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200
      }
    ],
    "num_frames": 1,
    "depth_range": [
      1.0
    ],
    "extrinsics": [
      [
        [
          1.0
        ]
      ]
    ],
    "intrinsics": [
      [
        [
          1.0
        ]
      ]
    ],
    "timings": {}
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "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 |
|---|---|---|
| `point_cloud` | object {url, content_type, file_name, file_size} \| null | Punktu mākoņa izvade, kas tiek atgriezta, ja `export_point_cloud` ir true; tās GLB ainā sapludināts mākonis apvienots ar kameru konusiem. |
| `depth_maps` | array of object {url, content_type, file_name, file_size, width, height} | Dziļuma kartes izvade, kas pieejama, ja `export_depth_maps` ir true. Ieraksti seko avota kadru secībai, katru kadru attēlojot kā 16 bitu pelēktoņu PNG rastru. |
| `prediction_data` | array of object {url, content_type, file_name, file_size} | Neapstrādāto prognožu izvade: ja `export_prediction_data` ir true, katram kadram ir savs JSON fails, un faili seko kadru secībai. |
| `num_frames` | integer | Kopējais rekonstruēto kadru skaits, ieskaitot attēlus un no video atlasītos kadrus. |
| `depth_range` | array of number | Dziļuma robežas [min, max], ko izmanto `depth_maps` kvantēšanai. Dziļumu atjauno, izmantojot min + pixel * (max - min) / 65535. |
| `extrinsics` | array of array of array of number | Kameras no pasaules ārējās matricas, 3x4 lielumā, katram kadram; OpenCV asis vērstas pa labi gar x, uz leju gar y un uz priekšu gar z. |
| `intrinsics` | array of array of array of number | Cauruma kameras iekšējās matricas, 3x3 lielumā, katram kadram, izteiktas modeļa 518x518 kadra pikseļu koordinātēs. |
| `timings` | object | Pagājušais reāllaika ilgums katram posmam sekundēs. |

## Related models

- [Sam 3 · Image · Embed](https://doitong.com/developers/models/sam-3/image/embed.md) (`sam-3/image/embed`): $0.005 / run
- [Bagel · Understand](https://doitong.com/developers/models/bagel/understand.md) (`bagel/understand`): $0.05 / request
- [Bria Ad Delayer](https://doitong.com/developers/models/bria/ad-delayer.md) (`bria/ad-delayer`): $0.30 / request
- [Florence 2 Large Caption](https://doitong.com/developers/models/florence-2-large/caption.md) (`florence-2-large/caption`): $0.003 / run
- [Florence 2 Large Detailed Caption](https://doitong.com/developers/models/florence-2-large/detailed-caption.md) (`florence-2-large/detailed-caption`): $0.004 / run
- [Florence 2 Large OCR](https://doitong.com/developers/models/florence-2-large/ocr.md) (`florence-2-large/ocr`): $0.003 / run
- [Florence 2 Large Region To Category](https://doitong.com/developers/models/florence-2-large/region-to-category.md) (`florence-2-large/region-to-category`): $0.003 / run
- [Florence-2 Large · More Detailed Caption](https://doitong.com/developers/models/florence-2-large/more-detailed-caption.md) (`florence-2-large/more-detailed-caption`): $0.004 / run

## Links

- HTML page: https://doitong.com/developers/models/vggt-1b
- 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=vggt-1b
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/vggt-1b