GitLab

Re-organize fix random seed code; Make saved checkpoint compatible among different torch versions (#986)

* Fix missing __init__.py

* Add further missing __init__.py

* add cbgs_dyn_pp_centerpoint.yaml

* add cbgs_voxel01_res3d_centerpoint.yaml

* add support of centerpoint on Nuscenes in README

* add translation augmentation, re-implement the performance of CenterPoints with 0.075m voxels

* cover the original world translation augmentation

* modify random_translation_along_X

* fix a small bug in random_world_translation()

* add cbgs_dyn_pp_centerpoint.yaml

* add cbgs_voxel01_res3d_centerpoint.yaml

* add support of centerpoint on Nuscenes in README

* add translation augmentation, re-implement the performance of CenterPoints with 0.075m voxels

* cover the original world translation augmentation

* modify random_translation_along_X

* add dynamic pillar vfe

* make the upperbound unaccessible

* add place holder for voxel generation

* add DynPillarVFE

* add PFNLayerV2

* add try except for torch_scatter package

* add dynamic pillar in readme

* add the cfg file of centerpoint with dynamic pillar

* add pyramid augmentation

* add pyramid augmentation

* format the modified file
Co-authored-by: Shaoshuai Shi <shaoshuaics@gmail.com>

* Fixes #718

* FIX: replaced wrong part

* #719 Fixes index error max_dt while inference: No gt_db_sampling -> MAX_SWEEPS-1 > # unique dt (e.g. first frame)

* move max_sweeps filter to PointFeatureEncoder with new config FILTER_SWEEPS

* update to lowercase
Co-authored-by: Christian Fruhwirth-Reisinger <christian.reisinger@student.tugraz.at>
Co-authored-by: Shaoshuai Shi <shaoshuaics@gmail.com>

* Fixes #718

* FIX: replaced wrong part
Co-authored-by: Christian Fruhwirth-Reisinger <christian.reisinger@student.tugraz.at>

Fix https://github.com/open-mmlab/OpenPCDet/issues/702

fixed a training bug

Added new augmentation methods and the option of augmentation by addition instead of replacement (#653)

* NOTEBOOK FOR DATA AUGMENTATION

* SMALL SAMPLE DATASET

* TRANSLACTIONS GLOBAL AND LOCAL

* LOCAL AUGMENTATIONS FINISHED

* ADJUSTED DATA FORMATS TO PCDET YAML COMPATIBILITY

* BUGFIX

* ADDED TITLES

* ADAPTED OPENPCDET TO FIT NEW AUGMENTATIONS

* SAVE IMAGES OF THE DATA AUGMENTATION EXAMPLES

* LOCAL TRANSFORMATION RANDOM VALUES VARY WITH OBJECT AND NOT SCENE

* FIXED YAML

* FIXED BUGS IN PARAMETERS

* FIX IN LOCAL BOXES

* NEW BOX FILTER

* FRUSTUM DROPOUT

* FRUSTUM DROPOUT IMPLEMENTED ON OPENPCDET

* REMOVE FIGURES FROM VERSION CONTROL

* MORE EFFICIENT LOCAL METHOD

* LOCAL TRANSFORMATION WITH NUMPY SPED UP

* BUGFIX ON AUGMENTATION FUNCTION

* GET PREDICTED LABELS

* AUGMENTATION DONE BY ADDITION

* RANDOM SELECTION OF REMAINIG FRAMES

* LOGGER WITH TRANSFORMATION DETAILS

* CHANGED COUNTER TO SAMPLE IDX SELECTION METHOD

* BUGFIX ON KITTY_DATABASE

* BUGFIX

* BUGFIX

* FIX ON GENERATOR

* DEBUG LOGS TO FILE

* FIXED LOGGER

* SAVE POINT CLOUDS TO OBJ FILE

* UPDATED NOTEBOOK

* CLEANUP

* .gitignore is now working

* fixed .gitignore

* REMOVED YAML FILES FROM .gitignore

* parse results to a csv

* yaml changed

* fixed gitignore

* FIXED BUG THAT DUPLICATED THE TEST SET

* small fixes on yaml

* fix gitignore

* updated generate_sets.py

* fixed csv_parser.py

* Delete output directory

* Delete output directory

* saving figures with better resolution

* implemented a way to chose to augment the raw pcs

* updated csv_parser.py

* fixed yamls to include the new selection system

* notebook updated

* mosaic added

* new models

* fixed gitignore

* fixed gitignore

* applied changes

* Delete data_aumentation.ipynb

* Delete pointpillar_fullaug.yaml

* updated gitignore

* bugfix

* updated training and notebook

* updated gitignore

* cleanup code

* updated yamls

* reset

* new augmentation methods

* example conf for pointpillars

* updated example config

* bugfix on the config file

* fixed get_points_in_box function

* fixed local frustum dropout

* fixed pointpillar_newaugs.yaml

* bugfixed: import math for some augmentations

* increased margin in point selection for local augmentation

* bugfixed: velocity should not be translated for translation augs. Add warning to check the correctness before using

* bugfixed: add back the aug of random_image_flip
Co-authored-by: Shaoshuai Shi <shaoshuaics@gmail.com>

* 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

Co-authored-by: xiazhongyu <xiazhongyu@pku.edu.cn>

support FILTER_EMPTY_BOXES_FOR_TRAIN and DISABLE_NLZ_FLAG_ON_POINTS for WOD by default, eval with sample_interval=1

update create_groundtruth_database of WOD to generate global npy file for sharedmemory based GT_database

Improve WOD performance with two LiDAR returns, speed up WOD data pre-processing with multiprocesssing.Pool

Improve WOD performance with two LiDAR returns, speed up WOD data pre-processing with multiprocesssing.Pool

* Added CaDDN detector and support for image, depth map, and 2D GT box
dataloading

* Moved image flip augmentation to augmentor_utils

* Updated default get item list to include points

* Moved utils functions into transform_utils

* Combined FFE + F2V into ImageVFE, renamed FFE to FFN, moved depth downsample into data_processor

* Updated README with updated CaDDN weights

* Updated comments for image vfe

In data_processor.py sample_points, when num_points < far_idx_choice, a negative value is passed into np.random.choice, which cause a ValueError.
In fact the variable `near_idxs_choice` return by the deleted line is never used.

* bugfixed: add num_points_in_gt to the waymo_infos for evaluation

* add clarification for Waymo evaluation

* add kitti_utils.py for evaluating with KITTI metrics