PRBonn / MaskPLS

Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving, RA-L, 2023
MIT License
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Softmax for Class Probabilities in Panoptic Inference Function #2

Closed YilmazKadir closed 1 year ago

YilmazKadir commented 1 year ago

Thank you for publishing your code. I wanted to ask if there is a small mistake in this line: https://github.com/PRBonn/MaskPLS/blob/f80691232bd25183435fd28dc54026652c209627/mask_pls/models/mask_model.py#LL135C35-L135C35 I believe you should apply a softmax function to get the probabilities similar to what you do in the semantic inference function: https://github.com/PRBonn/MaskPLS/blob/f80691232bd25183435fd28dc54026652c209627/mask_pls/models/mask_model.py#LL119C16-L119C16 Am I missing something or is there a slight mistake?

rmarcuzzi commented 1 year ago

Hi! You can apply the softmax() function and then argmax() to obtain the class probabilities but you can also directly use argmax(). We empirically found that not using the softmax() yielded a slightly better performance. You can try adding it and evaluating and you'll see the difference.