Using labelled segmentation image for object classification

I am using the “Object Classification [Inputs: Raw Data, Segmentation]” pipeline, i.e., I prepare my own segmentation image as the input.

My question is whether the segmentation input can be a label image (each object has its own integer identifier, with image type as uint16 to accommodate > 255 objects), instead of a binary image.

The reason is if I save my own segmentation results into a binary image, connect components will then be incorrectly treated as one object during the object classification workflow.


Hi @Mark,

yes, you can use such an image and object identities will be respected. uint32 will also work. It’s only important that the background is 0.


Thank you for the quick reply! It indeed works, as I see an example where connecting cells were assigned different class labels. Awesome!

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