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I'm encountering some problem when running the annotation-free setup models e.g. [RegionPLC + OpenScene + SparseUNet32] or [RegionPLC + SparseUNet32]. When inferenced on scannet validation, every point would be given the same label. This is my scripts used for running: python3 test.py --cfg_file cfgs/scannet_models/spconv_clip_openvocab_test.yaml --ckpt ../checkpoints/sparseunet32_596.pth --save_results semantic
I barely changed the yaml file, only for those categories I want to add, like from CATEGORY_NAMES: [door, window, desk, keyboard, others]
to CATEGORY_NAMES: [trash can, television ,door, window, desk, keyboard, chair, others]
this is my yaml file, since I only need the qualitiative results, I put all my labels in base labels.
Thank you if you can reply !
The text was updated successfully, but these errors were encountered:
Hi, thanks for your great work!
I'm encountering some problem when running the annotation-free setup models e.g. [RegionPLC + OpenScene + SparseUNet32] or [RegionPLC + SparseUNet32]. When inferenced on scannet validation, every point would be given the same label. This is my scripts used for running:
python3 test.py --cfg_file cfgs/scannet_models/spconv_clip_openvocab_test.yaml --ckpt ../checkpoints/sparseunet32_596.pth --save_results semantic
I barely changed the yaml file, only for those categories I want to add, like from
CATEGORY_NAMES: [door, window, desk, keyboard, others]
to
CATEGORY_NAMES: [trash can, television ,door, window, desk, keyboard, chair, others]
this is my yaml file, since I only need the qualitiative results, I put all my labels in base labels.
Thank you if you can reply !
The text was updated successfully, but these errors were encountered: