Pass the image to the pipeline.

predictions = depth_estimator(image)

The pipeline returns a dictionary with two entries. The first one, called predicted_depth, is a tensor with the values
being the depth expressed in meters for each pixel.
The second one, depth, is a PIL image that visualizes the depth estimation result.
Let's take a look at the visualized result:

predictions["depth"]