To get the first depth prediction, load `prs-eth/marigold-depth-lcm-v1-0` checkpoint into `MarigoldDepthPipeline` pipeline, put the image through the pipeline, and save the predictions:  
```python
import diffusers
import torch

pipe = diffusers.MarigoldDepthPipeline.from_pretrained(
"prs-eth/marigold-depth-lcm-v1-0", variant="fp16", torch_dtype=torch.float16
).to("cuda")

image = diffusers.utils.load_image("https://marigoldmonodepth.github.io/images/einstein.jpg")
depth = pipe(image)

vis = pipe.image_processor.visualize_depth(depth.prediction)
vis[0].save("einstein_depth.png")

depth_16bit = pipe.image_processor.export_depth_to_16bit_png(depth.prediction)
depth_16bit[0].save("einstein_depth_16bit.png")
```  
The visualization function for depth [`~pipelines.marigold.marigold_image_processing.MarigoldImageProcessor.visualize_depth`] applies one of [matplotlib's colormaps](https://matplotlib.org/stable/users/explain/colors/colormaps.html) (`Spectral` by default) to map the predicted pixel values from a single-channel `[0, 1]` depth range into an RGB image.
With the `Spectral` colormap, pixels with near depth are painted red, and far pixels are assigned blue color.
The 16-bit PNG file stores the single channel values mapped linearly from the `[0, 1]` range into `[0, 65535]`.
Below are the raw and the visualized predictions; as can be seen, dark areas (mustache) are easier to distinguish in the visualization:  
<div class="flex gap-4">
<div style="flex: 1 1 50%; max-width: 50%;">
<img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/marigold/marigold_einstein_lcm_depth_16bit.png"/>
<figcaption class="mt-1 text-center text-sm text-gray-500">
Predicted depth (16-bit PNG)
</figcaption>
</div>
<div style="flex: 1 1 50%; max-width: 50%;">
<img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/marigold/marigold_einstein_lcm_depth.png"/>
<figcaption class="mt-1 text-center text-sm text-gray-500">
Predicted depth visualization (Spectral)
</figcaption>
</div>
</div>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/using-diffusers/marigold_usage.md