- 09 Dec, 2021 1 commit
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lea-v authored
* Add basic support for Pandaset dataset * Add gt_sampling support for pandaset * Enable training on different classes than raw dataset * Save pandaset output in the same format as annotations * Add dataset config file for pandaset * Make pandaset dataset compatible with test.py - add 'evaluation' method - add 'name' key to predictions dict * Enable selecting lidar device for pandaset
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- 06 Dec, 2021 2 commits
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jihan.yang authored
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Dingry authored
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- 05 Dec, 2021 1 commit
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jihan.yang authored
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- 04 Dec, 2021 1 commit
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xiazhongyv authored
Co-authored-by:xiazhongyu <xiazhongyu@pku.edu.cn>
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- 01 Dec, 2021 1 commit
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Shaoshuai Shi authored
Release OpenPCDet v0.5.0
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- 30 Nov, 2021 6 commits
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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- 28 Nov, 2021 1 commit
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Shaoshuai Shi authored
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- 26 Nov, 2021 2 commits
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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- 25 Nov, 2021 2 commits
- 24 Nov, 2021 6 commits
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
support FILTER_EMPTY_BOXES_FOR_TRAIN and DISABLE_NLZ_FLAG_ON_POINTS for WOD by default, eval with sample_interval=1
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- 23 Nov, 2021 9 commits
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
update create_groundtruth_database of WOD to generate global npy file for sharedmemory based GT_database
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Shaoshuai Shi authored
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Shaoshuai Shi authored
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Shaoshuai Shi authored
Improve WOD performance with two LiDAR returns, speed up WOD data pre-processing with multiprocesssing.Pool
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Shaoshuai Shi authored
Add support for spconv 2.0
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Shaoshuai Shi authored
bugfixed: weights transformation between spconv 1.x and spconv 2.x, should consider both native/implicit spconv 2.x
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Shaoshuai Shi authored
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- 16 Nov, 2021 1 commit
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acivgin1 authored
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- 05 Nov, 2021 2 commits
- 04 Nov, 2021 4 commits
- 03 Nov, 2021 1 commit
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acivgin1 authored
- as per the spconv documentation, the order of channels in weights is now changed - we need to get all the affected weights, using the util function in spconv_utils - we need to check the version with the version checker in __init__.py - we need to transpose last two dimensions of existing weights, from older models - to avoid duplication a single _load_state_dict method is added
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