# Sam 3

> SAM 3D allows for accurate 3D reconstruction of human body shape and position from a single image.


## Overview

- **Endpoint**: `https://fal.run/fal-ai/sam-3/3d-body`
- **Model ID**: `fal-ai/sam-3/3d-body`
- **Category**: image-to-3d
- **Kind**: inference
**Tags**: 3d, human, pose



## Pricing

Your request will cost $0.02 per unit.

For more details, see [fal.ai pricing](https://fal.ai/pricing).

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:


- **`image_url`** (`string`, _required_):
  URL of the image containing humans
  - Examples: "https://v3b.fal.media/files/b/0a8439f8/E8gEXWsl2C-Euo4dGayzi_An_zyCCnSaytVklh_99sSYt4Z4Hh5e3s7VnNlx5JfN5KuC0j_bnq1AP9JfRoAmOQz5TP0DdCYMk4796Gloe5no1vvpoqhD-p3kE.jpeg"

- **`mask_url`** (`string`, _optional_):
  Optional URL of a binary mask image (white=person, black=background). When provided, skips auto human detection and uses this mask instead. Bbox is auto-computed from the mask.

- **`export_meshes`** (`boolean`, _optional_):
  Export individual mesh files (.ply) per person Default value: `true`
  - Default: `true`

- **`include_3d_keypoints`** (`boolean`, _optional_):
  Include 3D keypoint markers (spheres) in the GLB mesh for visualization Default value: `true`
  - Default: `true`

- **`include_mhr_params`** (`boolean`, _optional_):
  Include the full MHR (Meta Human Representation) parameter set per person in the response metadata (shape, pose, expression, global rotations, joint coordinates, packed model params, raw pose). Set to `false` to return a leaner metadata block with only keypoints and camera parameters. Default value: `true`
  - Default: `true`



**Required Parameters Example**:

```json
{
  "image_url": "https://v3b.fal.media/files/b/0a8439f8/E8gEXWsl2C-Euo4dGayzi_An_zyCCnSaytVklh_99sSYt4Z4Hh5e3s7VnNlx5JfN5KuC0j_bnq1AP9JfRoAmOQz5TP0DdCYMk4796Gloe5no1vvpoqhD-p3kE.jpeg"
}
```

**Full Example**:

```json
{
  "image_url": "https://v3b.fal.media/files/b/0a8439f8/E8gEXWsl2C-Euo4dGayzi_An_zyCCnSaytVklh_99sSYt4Z4Hh5e3s7VnNlx5JfN5KuC0j_bnq1AP9JfRoAmOQz5TP0DdCYMk4796Gloe5no1vvpoqhD-p3kE.jpeg",
  "export_meshes": true,
  "include_3d_keypoints": true,
  "include_mhr_params": true
}
```


### Output Schema

The API returns the following output format:

- **`model_glb`** (`File`, _required_):
  3D body mesh in GLB format with optional 3D keypoint markers
  - Examples: "https://v3b.fal.media/files/b/0a8439f9/5LVt3C2YesqnQzg-CxPpu_combined_bodies.glb"

- **`visualization`** (`File`, _required_):
  Combined visualization image (original + keypoints + mesh + side view)

- **`meshes`** (`list<File>`, _optional_):
  Individual mesh files (.ply), one per detected person (when export_meshes=True)
  - Array of File

- **`metadata`** (`SAM3DBodyMetadata`, _required_):
  Structured metadata including keypoints and camera parameters



**Example Response**:

```json
{
  "model_glb": "https://v3b.fal.media/files/b/0a8439f9/5LVt3C2YesqnQzg-CxPpu_combined_bodies.glb",
  "visualization": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "meshes": [
    {
      "url": "",
      "content_type": "image/png",
      "file_name": "z9RV14K95DvU.png",
      "file_size": 4404019
    }
  ],
  "metadata": {
    "people": [
      {}
    ]
  }
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/sam-3/3d-body \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "image_url": "https://v3b.fal.media/files/b/0a8439f8/E8gEXWsl2C-Euo4dGayzi_An_zyCCnSaytVklh_99sSYt4Z4Hh5e3s7VnNlx5JfN5KuC0j_bnq1AP9JfRoAmOQz5TP0DdCYMk4796Gloe5no1vvpoqhD-p3kE.jpeg"
   }'
```

### Python

Ensure you have the Python client installed:

```bash
pip install fal-client
```

Then use the API client to make requests:

```python
import fal_client

def on_queue_update(update):
    if isinstance(update, fal_client.InProgress):
        for log in update.logs:
           print(log["message"])

result = fal_client.subscribe(
    "fal-ai/sam-3/3d-body",
    arguments={
        "image_url": "https://v3b.fal.media/files/b/0a8439f8/E8gEXWsl2C-Euo4dGayzi_An_zyCCnSaytVklh_99sSYt4Z4Hh5e3s7VnNlx5JfN5KuC0j_bnq1AP9JfRoAmOQz5TP0DdCYMk4796Gloe5no1vvpoqhD-p3kE.jpeg"
    },
    with_logs=True,
    on_queue_update=on_queue_update,
)
print(result)
```

### JavaScript

Ensure you have the JavaScript client installed:

```bash
npm install --save @fal-ai/client
```

Then use the API client to make requests:

```javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/sam-3/3d-body", {
  input: {
    image_url: "https://v3b.fal.media/files/b/0a8439f8/E8gEXWsl2C-Euo4dGayzi_An_zyCCnSaytVklh_99sSYt4Z4Hh5e3s7VnNlx5JfN5KuC0j_bnq1AP9JfRoAmOQz5TP0DdCYMk4796Gloe5no1vvpoqhD-p3kE.jpeg"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);
```


## Additional Resources

### Documentation

- [Model Playground](https://fal.ai/models/fal-ai/sam-3/3d-body)
- [API Documentation](https://fal.ai/models/fal-ai/sam-3/3d-body/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/sam-3/3d-body)

### fal.ai Platform

- [Platform Documentation](https://fal.ai/docs/documentation)
- [Python Client](https://fal.ai/docs/api-reference/client-libraries/python)
- [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript)

### Other agent-readable surfaces

This file covers one model. To find anything else:

- [Platform overview](https://fal.ai/llms.txt): Entry points and representative endpoint IDs
- [Documentation index](https://fal.ai/docs/llms.txt): Every documentation page
- [Full documentation text](https://fal.ai/docs/llms-full.txt): The whole documentation inlined
- Any other model: `https://fal.ai/models/<endpoint-id>/llms.txt`