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Allow saving to a different folder each time RenderBurst is used #2

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Pilchard123 opened this issue Jan 4, 2019 · 4 comments
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@Pilchard123
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Pilchard123 commented Jan 4, 2019

Currently, RenderBurst will overwrite files in a folder if they have the same names. If you make a change and want to compare the original images with the results of the change, the original renders are lost if you do not move the images to a new folder.

It might be useful to have a checkbox that, when checked, will save the images into a different folder each time RenderBurst is used. Maybe the date and time that the rendering started would be a good naming pattern, so rather than having:

 /outputDirectory
    Camera.001.png
    Camera.002.png
    Camera.003.png

it can produce

 /outputDirectory
   /2019-01-03-17-30
      Camera.001.png
      Camera.002.png
      Camera.003.png
   /2019-01-04-17-00
      Camera.001.png
      Camera.002.png
      Camera.003.png
   /2019-01-04-17-30
      Camera.001.png
      Camera.002.png
      Camera.003.png

Of course, if the checkbox is not checked, the old behaviour would remain. I'd be happy to proved a pull request, but I'm not enormously familiar with Blender add-on development so it would probably not be of high quality.

@Pilchard123
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This is (and more) covered by #3

@norrid
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norrid commented Feb 14, 2019

I forked this project off recently and have made a version that allows you to chose if files are overwritten or not. It won't create a new folder but will date/time stamp all file names. My version works a bit differently with how you select cameras, just so you are aware.

@banolka
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banolka commented Dec 14, 2020

Can You share the fork ?

@ldo
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ldo commented May 11, 2021

Batch-mode rendering makes all this--and more--possible. That’s why I wrote render-batch (part of my render-useful collection). It lets you choose output destinations, choice of action with existing files, setting resolution quality and output format, switching active scenes and cameras, setting visible collections and view layers, and execution of custom Python code where the standard options aren’t enough.

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4 participants