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Hi,
I am trying to do a semantic segmentation for a dataset containing plants.
My models contain a lot of leaves, which are basically built using support squares, with an image of a leaf on them.
In these images the background is transparent.
In the RGB render, the leaves appear normal, the transparency works - I can only see the leaves, not their supports.
However, in the depth and semantic windows, the leaves appear square (I tried .obj and .fbx formats).
Is there a setting that I can use, so that, the semantic mask is created using only the visible parts, without their transparent support square? Or do I have to fix the plant models first? (In Nvidia Omniverse the segmentation is correct for these models.)
Thanks.
The text was updated successfully, but these errors were encountered:
No, unfortunately, I did not find a solution (although I did not have much time to deal with this problem). Maybe a clue could be a different Blender version (not with bpycv, but just in the bare Blender these squares behave differently depending on the different Blender versions - but at this moment I do not remember exactly the version number)
Hi,
I am trying to do a semantic segmentation for a dataset containing plants.
My models contain a lot of leaves, which are basically built using support squares, with an image of a leaf on them.
In these images the background is transparent.
In the RGB render, the leaves appear normal, the transparency works - I can only see the leaves, not their supports.
However, in the depth and semantic windows, the leaves appear square (I tried .obj and .fbx formats).
Is there a setting that I can use, so that, the semantic mask is created using only the visible parts, without their transparent support square? Or do I have to fix the plant models first? (In Nvidia Omniverse the segmentation is correct for these models.)
Thanks.
The text was updated successfully, but these errors were encountered: