> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/workflows/blocks/blocks/run-a-model/depth-estimation.md).

# Depth Estimation

Run Depth Estimation on an image.

### Type identifier

Use the following identifier in step `"type"` field: `roboflow_core/depth_estimation@v1` to add the block as a step in your workflow.

### Properties

| **Name**        | **Type** | **Description**                                       | Refs |
| --------------- | -------- | ----------------------------------------------------- | ---- |
| `name`          | `str`    | Enter a unique identifier for this step..             | ❌    |
| `model_version` | `str`    | The Depth Estimation model to be used for inference.. | ✅    |

The **Refs** column marks possibility to parametrise the property with dynamic values available in `workflow` runtime. See *Bindings* for more info.

### Runtime compatibility

`hard` - runtime `self_hosted_cpu`; execution `local` : Requires a GPU; run\_locally() loads a model that needs CUDA.

### Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds `Depth Estimation` in version `v1` has.

<details>

<summary>Input and output bindings</summary>

* input
  * `images` ([*`image`*](/workflows/developer-guide/developer-guide/kinds/image.md)): The image to infer on..
  * `model_version` ([*`string`*](/workflows/developer-guide/developer-guide/kinds/string.md)): The Depth Estimation model to be used for inference..
* output
  * `image` ([`image`](/workflows/developer-guide/developer-guide/kinds/image.md)): Image in workflows.
  * `normalized_depth` ([`numpy_array`](/workflows/developer-guide/developer-guide/kinds/numpy-array.md)): Numpy array.

</details>

<details>

<summary>Example JSON definition</summary>

```json
{
	    "name": "<your_step_name_here>",
	    "type": "roboflow_core/depth_estimation@v1",
	    "images": "$inputs.image",
	    "model_version": "depth-anything-v2/small"
	}
```

</details>