# Sam 3 · 3D Body API

> Tek bir fotoğraftan, tespit edilen kişi başına bir tane olacak şekilde 3D insan vücudu poligon ağlarını yeniden oluşturur

Tek bir görseldeki kişilerin 3D vücut poligon ağlarını oluşturur. Kişiler otomatik olarak algılanır veya `mask_url` içinde ikili maske sağlanabilir (kişi için beyaz). Değiştirmeler kişi başına .ply dışa aktarımını, GLB içindeki 3D anahtar nokta işaretlerini ve meta verilerdeki tam MHR parametre kümesini kontrol eder. GLB, poligon ağları, meta veriler ve görselleştirme görseli döndürür.

- Model id: `sam-3/3d-body`
- 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-body`
- Quote: `POST https://api.doitong.com/v1/quote/sam-3/3d-body`
- Docs page: https://doitong.com/tr/developers/models/sam-3/3d-body

## 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-body` 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 |  |  | İnsanları gösteren görsel URL'si. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | Otomatik insan algılamasının yerine geçen ve otomatik sınırlayıcı kutu hesaplaması için veri sağlayan isteğe bağlı ikili maske görsel URL'si. Kişiyi beyaz, arka planı siyah olarak kodlayın. |
| `export_meshes` |  | boolean | no | `true` |  | Her kişi için ayrı bir .ply mesh dosyasının dışa aktarılıp aktarılmayacağı. |
| `include_3d_keypoints` |  | boolean | no | `true` |  | Görselleştirme için GLB mesh'ine küresel 3D kilit nokta işaretçilerinin eklenip eklenmeyeceği. |
| `include_mhr_params` |  | boolean | no | `true` |  | Her kişinin yanıt meta verilerinin tam MHR (Meta Human Representation) verilerini mi, yoksa yalnızca kamera parametreleri ve kilit noktalarını (`false`) mı içereceği. Tam veriler ifade ve şekil, poz ve ham poz, eklem koordinatları ve küresel dönüşlerin yanı sıra paketlenmiş model parametrelerini kapsar. |

File parameters (`image`, `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
{
  "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-body?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-body?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-body", 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-body",
      "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-body",
  "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": {
    "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
    },
    "visualization": {
      "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
    },
    "meshes": [
      {
        "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": {
      "num_people": 1,
      "people": [
        {
          "person_id": 1,
          "bbox": [],
          "focal_length": 1.0,
          "pred_cam_t": [],
          "keypoints_2d": [],
          "keypoints_3d": [],
          "shape_params": [],
          "body_pose_params": [],
          "hand_pose_params": [],
          "global_rot": [],
          "pred_global_rots": [],
          "scale_params": [],
          "expr_params": [],
          "pred_joint_coords": [],
          "mhr_model_params": [],
          "pred_pose_raw": []
        }
      ],
      "keypoint_names": [
        "string"
      ]
    }
  },
  "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 |
|---|---|---|
| `model_glb` | object {url, content_type, file_name, file_size} | İsteğe bağlı olarak 3D kilit noktaları için işaretçiler içeren GLB formatında 3D gövde mesh'i. |
| `visualization` | object {url, content_type, file_name, file_size} | Orijinal görseli, kilit noktalarını, mesh'i ve yan görünümü gösteren bileşik görselleştirme. |
| `meshes` | array of object {url, content_type, file_name, file_size} \| null | Her algılanan kişi için ayrı .ply mesh dosyaları; export_meshes True olduğunda döndürülür. |
| `metadata` | object {num_people, people, keypoint_names} | Kamera parametreleri ve kilit noktalarını içeren yapılandırılmış meta veriler. |

## 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 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
- [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-body
- 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-body
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/sam-3/3d-body