Add documentation about unknown depth pixel convention (#2490)

Updated the documentation to explicate that zero value in depth images is treated as unknown depth. This behavior is defined in https://github.com/nerfstudio-project/nerfstudio/blob/a484d255b4f71c55915afcfc52d90ec88963779f/nerfstudio/model_components/losses.py#L242

Co-authored-by: Matthew Tancik <matt@lumalabs.ai>

docs/quickstart/data_conventions.md

@@ -82,7 +82,7 @@ For a transform matrix, the first 3 columns are the +X, +Y, and +Z defining the
 
 ### Depth images
 
-To train with depth supervision, you can also provide a `depth_file_path` for each frame in your `transforms.json` and use one of the methods that support additional depth losses (e.g., depth-nerfacto). The depths are assumed to be 16-bit or 32-bit and to be in millimeters to remain consistent with [Polyform](https://github.com/PolyCam/polyform). You can adjust this scaling factor using the `depth_unit_scale_factor` parameter in `NerfstudioDataParserConfig`. Note that by default, we resize the depth images to match the shape of the RGB images.
+To train with depth supervision, you can also provide a `depth_file_path` for each frame in your `transforms.json` and use one of the methods that support additional depth losses (e.g., depth-nerfacto). The depths are assumed to be 16-bit or 32-bit and to be in millimeters to remain consistent with [Polyform](https://github.com/PolyCam/polyform). Zero-value in the depth image is treated as unknown depth. You can adjust this scaling factor using the `depth_unit_scale_factor` parameter in `NerfstudioDataParserConfig`. Note that by default, we resize the depth images to match the shape of the RGB images.
 
 ```json
 {