Rendering Deep Images with mental ray in Maya 2016

Deep OpenEXR files allow to store a variable number of samples per pixel at different depth locations to aid advanced depth compositing workflows.

To render a Deep OpenEXR file with mental ray, open the Render Settings dialog and make sure that the image output format is set to “exr” in the Common tab:

render-settings-common

In the Scene tab, enable the “Use Deep Image format” checkbox:

render-settings-scene

The  Deep OpenEXR file is written in multi-part, which means that files can contain a number of separate but related images. Each render pass gets its own part (i. e. direct_diffuse, indirect_diffuse).

In order to save memory during rendering, mental ray creates tiled Deep OpenEXR files. These files need to be converted to scanline for use in compositing applications like Nuke. This conversion can be performed using imf_copy, a command line tool that is part of your mental ray for Maya installation. It can be found in the bin directory. Call

imf_copy -s tiled-exr-file.exr scanline-exr-file.exr

to perform the conversion. Click on the image below to see a screenshot of the tool executed on a Windows system:

cmd

Please note that currently only z front is supported. This means that rendering deep volumes is not possible yet. Deep and flat data cannot be mixed in the same OpenEXR file.

 

 

8 thoughts on “Rendering Deep Images with mental ray in Maya 2016

    1. bgawboy says:

      Yes, it comes with Maya. Carefully read the download and installation instructions, as it is a separate download coming with Maya 2016. It’s Service Packs (SPs) are synchronized with Maya’s.

  1. Tried to convert the tiled deep exr to scaline using imf_copy and the resulting file errors out in nuke “unexpected end of file” i have no idea what that refers to though.

    1. bgawboy says:

      We now encourage our simpler pass system which can be seen in the Render Settings > Scene tab in Camera > Passes section. Simple checkboxes. Plus light specific passes enabled. Not quite as complex as contribution maps, but should give you most of what you typically need. We will grow this based on need. For example, there are also new techniques coming out for flexible extractable matte passes, with the proposed addition for Open EXR as well as CryptoMatte.

  2. Glenn says:

    You output in a format that nothing supports and make users convert them manually using a commandline tool? That’s … “deeply” awful.

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