> ## 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.

# DA3Metric

> Metric monocular depth estimation using Depth Anything 3

Estimate metric depth from a single RGB image using Depth Anything 3. Returns depth values in meters.

## Parameters

<ParamField body="image_input" type="str | PIL.Image | np.ndarray" required>
  RGB image as file path, URL, PIL Image, or numpy array.
</ParamField>

<ParamField body="timeout" type="float | None">
  Optional timeout in seconds for the HTTP request.
</ParamField>

## Returns

`np.ndarray` — Metric depth map of shape `(H, W)` with dtype `float32`. Values represent depth in meters.

## Example Output

<img src="https://mintcdn.com/scaledfoundations/lgZgGQWKvUIw0C7n/assets/images/cortex/da3metric-output.jpg?fit=max&auto=format&n=lgZgGQWKvUIw0C7n&q=85&s=ebc65e61106d912ad8921fd39d6188b2" alt="DA3Metric input and depth map output" width="1136" height="552" data-path="assets/images/cortex/da3metric-output.jpg" />

## Example

```python theme={null}
from grid_cortex_client import CortexClient
from PIL import Image

client = CortexClient()
image = Image.open("scene.jpg")  # 640x480 RGB
depth = client.run(model_id="da3metric", image_input=image)

print(depth.shape, depth.dtype)
# (378, 504) float32 — note: output resolution differs from input

print(f"min={depth.min():.4f}, max={depth.max():.4f}, mean={depth.mean():.4f}")
# min=1.6177, max=53.1848, mean=12.9778  (meters)
```


## Related topics

- [Metric3D](/models/cortex/metric3d.md)
- [Metric3D ](/models/depth/metric3d.md)
- [DepthAnything v2 ](/models/depth/depth_anything_v2.md)
- [ZoeDepth](/models/cortex/zoedepth.md)
- [Sessions](/grid/open-grid/sessions.md)