# Sam 3 · 3D Objects API

> Reconstruye objetos 3D a partir de una imagen, seleccionados mediante texto, puntos, cuadros o máscaras, con salida de splats

Convierte los objetos de una foto en recursos 3D. Selecciona objetos con `mask_urls`, un `prompt` de texto, `point_prompts` o `box_prompts`; varios cuadros generan objetos independientes. `detection_threshold` acepta de 0.1 a 1 y `export_textured_glb` incorpora la textura y las UV. Las salidas incluyen un GLB, archivos de Gaussian splat, archivos por objeto para escenas con varios objetos, metadatos y un paquete zip.

- Model id: `sam-3/3d-objects`
- Made by: Meta
- Category: Image to 3D
- Output: 3d
- Estimated price per run: $0.02 / run (cheapest run $0.02 (20 API credits))
- Run: `POST https://api.doitong.com/v1/run/sam-3/3d-objects`
- Quote: `POST https://api.doitong.com/v1/quote/sam-3/3d-objects`
- Docs page: https://doitong.com/es/developers/models/sam-3/3d-objects

## Pricing

Price: **$0.02 / run**. Estimated from the typical cost of one run. The quote is exactly what the run charges.

The full example input below costs $0.02 = 20 API credits (1 request × 20 API credits).

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-3/3d-objects` 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 |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | URL de la imagen para la reconstrucción 3D. |
| `mask_urls` |  | array of image URL | no |  |  | Lista opcional de URL de máscaras por objeto. Sin máscaras, la segmentación automática utiliza prompt, point_prompts o box_prompts si se proporcionan; si no se proporcionan ni máscaras ni prompts de segmentación, se usa toda la imagen. |
| `prompt` |  | string \| null | no | `car` |  | Texto utilizado para la segmentación automática cuando no hay máscaras, como 'chair' o 'lamp'. |
| `point_prompts` |  | array of object {x, y, label, object_id} | no | `[]` |  | Prompts basados en puntos utilizados para la segmentación automática cuando no hay máscaras. |
| `point_prompts[].x` |  | integer \| null | no |  |  | Posición del prompt en el eje X. |
| `point_prompts[].y` |  | integer \| null | no |  |  | Posición del prompt en el eje Y. |
| `point_prompts[].label` |  | enum (integer) \| null | no |  | `0`, `1` | Etiqueta de primer plano/fondo: 1 indica primer plano; 0 indica fondo. |
| `point_prompts[].object_id` |  | integer \| null | no |  |  | Identificador opcional que agrupa prompts que refinan un único objeto. Si también se proporciona texto como prompt, este identificador determina qué objeto detectado refinan esos puntos. |
| `box_prompts` |  | array of object {x_min, y_min, x_max, y_max, object_id} | no | `[]` |  | Prompts de cuadros que producen máscaras de objetos individuales para la reconstrucción 3D mediante segmentación automática; se utilizan solo si no se proporcionan máscaras. Se pueden enviar varios cuadros. |
| `box_prompts[].x_min` |  | integer \| null | no |  |  | Coordenada x mínima del cuadro. |
| `box_prompts[].y_min` |  | integer \| null | no |  |  | Coordenada y mínima del cuadro. |
| `box_prompts[].x_max` |  | integer \| null | no |  |  | Coordenada X máxima del recuadro. |
| `box_prompts[].y_max` |  | integer \| null | no |  |  | Coordenada Y máxima del recuadro. |
| `box_prompts[].object_id` |  | integer \| null | no |  |  | Identificador opcional que agrupa recuadros que refinan un único objeto. |
| `seed` |  | integer \| null | no |  |  | Semilla utilizada para una generación aleatoria reproducible. |
| `pointmap_url` |  | string \| null | no |  |  | URL opcional para mejorar la estimación de profundidad en la reconstrucción 3D proporcionando datos externos de pointmap o profundidad en formato NPY o NPZ. |
| `detection_threshold` |  | number \| null | no |  | 0.1 – 1 | Umbral de confianza de detección; si se omite, se deja en el valor predeterminado del modelo. Los valores van de 0.1 a 1.0; los valores más pequeños reducen la precisión a cambio de un mayor número de detecciones. |
| `export_textured_glb` |  | boolean | no | `false` |  | Opción de exportación GLB: al activar esta opción, los colores de los vértices se reemplazan por una textura horneada y UV. |

File parameters (`image`, `mask_urls`) 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
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## 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-3/3d-objects?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# 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-3/3d-objects?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
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 = {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/sam-3/3d-objects", 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-3/3d-objects",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "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-3/3d-objects",
  "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": 20,
    "usd": "0.02",
    "charged": 20,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "gaussian_splat": {
      "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
    },
    "model_glb": {
      "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
    },
    "metadata": [
      {
        "object_index": 1,
        "scale": [
          []
        ],
        "rotation": [
          []
        ],
        "translation": [
          []
        ],
        "camera_pose": [
          []
        ]
      }
    ],
    "individual_splats": [
      {
        "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
      }
    ],
    "individual_glbs": [
      {
        "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
      }
    ],
    "artifacts_zip": {
      "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
    }
  },
  "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 |
|---|---|---|
| `gaussian_splat` | object {url, content_type, file_name, file_size} | Splat de escena combinada para resultados con varios objetos, o un único splat en los demás casos; se proporciona como un archivo Gaussian splat en formato .ply. |
| `model_glb` | object {url, content_type, file_name, file_size} | Salida 3D guardada como GLB: los objetos múltiples se ensamblan en una sola escena, mientras que los demás resultados contienen una malla. |
| `metadata` | array of object {object_index, scale, rotation, translation, camera_pose} | Metadatos de cada objeto, incluidos la rotación, la traslación y la escala. |
| `individual_splats` | array of object {url, content_type, file_name, file_size} \| null | Archivos Gaussian splat independientes para cada objeto, disponibles solo en escenas con varios objetos. |
| `individual_glbs` | array of object {url, content_type, file_name, file_size} \| null | Archivos de malla GLB independientes para cada objeto, disponibles solo en escenas con varios objetos. |
| `artifacts_zip` | object {url, content_type, file_name, file_size} \| null | Archivo ZIP con todos los artefactos y los metadatos. |

## 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 · Video RLE](https://doitong.com/developers/models/sam-3/video-rle.md) (`sam-3/video-rle`): $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 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
- [Hi3D Image to 3D](https://doitong.com/developers/models/hitem3d/hi3d/image-to-3d.md) (`hitem3d/hi3d/image-to-3d`): $0.50 / run

## Links

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