> ## Documentation Index
> Fetch the complete documentation index at: https://docs.generalrobotics.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# ZoeDepth 

<Note>
  This page documents the `grid.model.*` local inference wrapper. For cloud-hosted inference via **GRID Cortex**, see the [Cortex ZoeDepth page](/models/cortex/zoedepth).
</Note>

The `ZoeDepth` class provides a wrapper for the ZoeDepth model, which estimates depth maps from RGB images using the `pipeline` method from the Hugging Face transformers library.

<ResponseField name="class ZoeDepth()">
  <ResponseField name="use_local" type="boolean" default="False">
    If True, inference call is run on the local VM, else offloaded onto GRID-Cortex. Defaults to False.
  </ResponseField>
</ResponseField>

<ResponseField name="def run()">
  <ResponseField name="rgbimage" type="np.ndarray" required="True">
    The input RGB image of shape $(M,N,3)$.
  </ResponseField>

  <ResponseField name="Returns" type="np.ndarray">
    The predicted depth map of shape $(M,N)$.
  </ResponseField>
</ResponseField>

<RequestExample>
  ```python Inference Call theme={null}
  from grid.model.perception.depth.zoedepth import ZoeDepth
  car = AirGenCar()

  # We will be capturing an image from the AirGen simulator 
  # and run model inference on it.

  img =  car.getImage("front_center", "rgb").data

  model = ZoeDepth(use_local = False)
  result = model.run(rgbimage=img)
  print(result.shape)
  ```
</RequestExample>

<Tabs>
  <Tab title="License">
    This code is licensed under the MIT License.
  </Tab>

  <Tab title="Source">
    [https://huggingface.co/Intel/zoedepth-kitti](https://huggingface.co/Intel/zoedepth-kitti)
  </Tab>
</Tabs>