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Class label mismatch issue (the 127 classes) #41
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Possible Solution
So that we will have 132 (defined in the |
Hi:
This cumbersome solution is just trying to mitigate the overlapping class issue. A better solution might just output 127 separate binary masks. I will update readme asap and thanks for pointing them out. |
Thanks for your patient response! This is really helpful to my project. |
Hi @heyufan1995 , In your answer, you suggest "ii. Do 3 class "bone", "lung", "kidney" through model-zoo." It turns out that if I use But if I just trying to get label 2/20/21 in the output with label prompt 2/20/21, and simply changed the So I'm wondering if this phenomenon is normal, or I have something missing here. Hope to have your response. Thanks! |
Hi Tianyu: {'2': 2, '20': 20, '21': 21} means no mapping at all. We only have a few annotations of "lung" "kidney" "bone", most of the training data are their substructures. Those 3 class_prompt are basically not trained during training, and thus we just merge their sub-structure for them. For example, if you directly use "kidney" prompt, this prompt is just a random 1x512 random class_embedding with no relationships with "left" and "right" kidney prompts. That's why we have this mapping. |
Understood! Thanks for your detailed explanation! |
Describe the phenomenon
infer.py
of VISTA codebase, theEVERYTHING_PROMPT
has a total of 118 classes.label_dict.json
file of VISTA codebase defines 132 classes.labels.json
of the MONAI wrapper of VISTA3D defines 135 classes.Questions
infer.py
of VISTA codebase?Thank you!
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