GitLab

* extract RGB images for ScanNet

* update scannet_data_utils with rgb

* fix docs an tools; add use_camera to ScanNetDataset

* fix typos is scannet doc

* fix very rare undefined poses for ScanNet

* update ScanNet dataset for more clear MultiViewPipeline

* update compatibility for ScanNet

* fix typo in compatibility doc

* use mmcv.track_parallel_progress for scannet images

* Add Lyft fixer file and instructions

* Restore Lyft split files

* support S3DIS data download and pre-processing (to ScanNet format)

* add S3DIS data for unittest

* add S3DIS semseg dataset class and unittest

* add config file for S3DIS dataset

* add eval_pipeline to S3DIS dataset config file

* clean code for S3DIS pre-processing scripts

* reformat code

* fix small bugs

* resolve conflicts & modify show() to use pipeline

* fix small errors

* polish data pre-processing code

* add more comments about S3DIS dataset

* fix markdown lint error

* Support nuscenes mono3d json info generation

* Support nuscenes mono3d dataset class

* Support attribute and bbox2d prediction in bbox3dnms and bbox3d2result

* Rename dataset class and add comments to 'attrs'

* Support mono3d related pipelines

* Fix unittest for loading 3D annotations

* Add unit test for nuscenes mono3d dataset

* Rename the sample result file

* Upload sample data for mono3d unit test

* Upload sample data for mono3d unit test

* Upload sample image for unit test

* Delete tests/data/nuscenes/samples/LIDAR_TOP/CAM_BACK_LEFT directory

* Add files via upload

* Remove unnecessary 'f'

* Remove unnecessary \ in arguments

* Remove check for pycocotools version because it has been done in the cocodataset

* Remove unnecessary comma, add TODO and change init of attrs in format_results

* Merge RandomFlip3D and RandomFlipMono3D

* Add pytest to check whether cuda is available in the unit test

* Support monocular 3D detection on KITTI dataset

* Add visualization TODO

* Merge nus_mono3d and update dataset init

* Remove duplicated loading images in mono3d

* Remove aos evaluation of bbox2d predictions on KITTI

* Add unit test for kitti mono3d dataset

* Add accidentally deleted classes in the dataset init

* Replace .format with f-string in kitti dataset

* Clean comma

* Toy data for unit test of kitti mono dataset

* Sample image data for unit test

* add format_results function for ScanNet test set results submission

* support ScanNet test set data pre-processing

* replace is_train with test_mode for better consistency

* fix link error in docstring

* Support nuscenes mono3d json info generation

* Support nuscenes mono3d dataset class

* Support attribute and bbox2d prediction in bbox3dnms and bbox3d2result

* Rename dataset class and add comments to 'attrs'

* Support mono3d related pipelines

* Fix unittest for loading 3D annotations

* Add unit test for nuscenes mono3d dataset

* Rename the sample result file

* Upload sample data for mono3d unit test

* Upload sample data for mono3d unit test

* Upload sample image for unit test

* Delete tests/data/nuscenes/samples/LIDAR_TOP/CAM_BACK_LEFT directory

* Add files via upload

* Remove unnecessary 'f'

* Remove unnecessary \ in arguments

* Remove check for pycocotools version because it has been done in the cocodataset

* Remove unnecessary comma, add TODO and change init of attrs in format_results

* Merge RandomFlip3D and RandomFlipMono3D

* Add pytest to check whether cuda is available in the unit test

* Add visualization TODO

* Remove useless init in loading mono3d images

* remove max_num_point in ScanNet data preprocessing

* add config file for ScanNet semantic segmentation dataset

* modify NormalizePointsColor in pipeline

* add visualization function for semantic segmentation

* add ignore_index to semantic segmentation visualization function

* add ignore_index to semantic segmentation evaluation function

* fix ignore_index bug in semantic segmentation evaluation function

* add test function to check ignore_index assignment in PointSegClassMapping

* fix slicing bug in BasePoints class and add unittest

* add IndoorPatchPointSample class for indoor semantic segmentation data loading and add unittest

* modify LoadPointsFromFile class and its unittest to support point color loading

* fix data path in unittest

* add setter function for coord and attributes of BasePoint and modify unittest

* modify color normalization operation to work on BasePoint class

* add unittest for ScanNet semantic segmentation data loading pipeline

* fix ignore_index bug in seg_eval function

* add ScanNet semantic segmentation dataset and unittest

* modify config file for ScanNet semantic segmentation

* fix visualization function and modify unittest

* fix a typo in seg_eval.py

* raise exception when semantic mask is not provided in train/eval data loading

* support custom computation of label weight for loss calculation

* modify seg_eval function to be more efficient

* fix small bugs & change variable names for clarity & add more cases to unittest

* move room index resampling and label weight computation to data pre-processing

* add option allowing user to determine whether to sub-sample point clouds

* fix typos & change .format to f-string & fix link in comment

* save all visualizations into .obj format for consistency

* infer num_classes from label2cat in eval_seg function

* add pre-computed room index and label weight for ScanNet dataset

* replace .ply with .obj in unittests and documents

* add TODO in case data is on ceph

* add base dataset for all semantic segmentation tasks & add ScanNet dataset inheriting from base dataset

* rename class for consistency

* fix minor typos in comment

* move Custom3DSegDataset to a new file

* modify BasePoint setter function to enable attribute adding

* add unittest for NormalizePointsColor and fix small bugs

* fix unittest for BasePoints

* modify ScanNet data pre-processing scripts

* change ignore_idx to -1 in seg_eval function

* remove sliding inference from PatchSample function and modify unittest

* remove PatchSample from scannet seg test_pipeline

* Added image loading in SUNRGB-D dataset (#195)

* image loading

* format and docstring fix

* removed irrelevant files

* removed irrelevant files

* load image only if modality is pc+img

* added modality like nuscenes

* Added imvotenet image branch pretrain (#217)

* image loading

* naive commit

* format and docstring fix

* removed irrelevant files

* removed irrelevant files

* load image only if modality is pc+img

* added modality like nuscenes

* pretrain_2d_model

* finetune sunrgbd

* finetune sunrgbd

* deleted unused code

* fixed a bug

* resolve conflict

* update config file

* fix docstring and configs

* integrated vote fusion

* coords transform and unit test

* Update docstring

* refactor and add unit test

* fix bug caused by mmcv upgrade; delete pdb breakpoint

* add point fusion unittest

* remove unused file

* fix typos

* updates

* add assertion info

* update

* add unittest

* add vote fusion unittest

* add vote fusion unittest

* [Refactor] VoteNet refactor (#322)

* votenet refactor

* remove file

* minor update

* docstring

* initial update of imvotenet

* [Feature] Support vote fusion (#297)

* integrated vote fusion

* coords transform and unit test

* Update docstring

* refactor and add unit test

* add point fusion unittest

* remove unused file

* updates

* add assertion info

* update

* add unittest

* add vote fusion unittest

* add vote fusion unittest

* minor update

* docstring

* change np ops to torch

* refactor test

* update

* refactor of image mlp and np random ops to torch

* add docstring

* add config and mod dataset

* fix bugs

* add_comments

* fix bugs

* fix_bug

* fix bug

* fix bug

* fix bug

* fix bug

* final fix

* fix bug

* ?

* add docstring

* move train/test cfg

* change img mlp default param

* rename config

* minor mod

* change config name

* move train/test cfg

* some fixes and 2d utils

* fix config name

* fix config override issue

* config simplify & reformat

* explicitly set eval mode->override train()

* add fix_img_branch to config

* remove set_img_branch_eval_mode

* temporal fix, change calibs to calib

* more docstring and view/reshape, expand/repeat change

* complete imvotenet docstring

* fix docstring

* add config and some minor fix

* rename config
Co-authored-by: ZwwWayne <wayne.zw@outlook.com>

* Fix the bug on the commit #211 for the create_gt_database in nuscenes

* Fix bugs for the create_gt_database of kitti

* Fix bugs for '__get_item__' of BasePoints

* make nuimage cat order consistent

* support semantic seg

* update model links

* update readme

* Reduce requirements if waymo dataset is not used

* Update waymo.md

* Update optional.txt

* Update waymo.md

Add instructions of requirements/optional.txt related to waymo

* Add gitlab CI back

* clean isort

* Update gitlab CI version

* Update mmcv install

* fix unit test bug

* waymo

* Use new flake8

* Update mmdet3d/core/evaluation/waymo_utils/prediction_kitti_to_waymo.py, tools/data_converter/waymo_converter.py files

* Add baseline configs for waymo

* fix linting

* yapf reformat

* update waymo results

* Update waymo model zoo and docs

* Bump v0.6.0

* Fix a minor bug when converting waymo data

* Fix cmds in the waymo doc

* Fix setup.cfg to pass isort test

* Fix waymo configs

* Update model zoo link & doc

* update version date

* clean ci
Co-authored-by: wangtai <wangtai@sensetime.com>
Co-authored-by: Tai-Wang <tab_wang@outlook.com>

* Change gt_database and dbsampler.

* Add int condition for use_dim.

* Change default sweep_num.

* Change docstring.

* Change to pipeline in db_sampler.

* remove comments.

* [Feature]: support using nuimages for instance segmentation

* Update performance and start benchmark

* Change default path names

* Update performance

* Update mmcv version

* Update model links

* Update model links and fix unit tests

* rephrase

* Add bottom2gravity and balance_class option.

* Add valid_flag.

* Add use_valid_flag.

* Change balance_class option.

* Add wrapper, remove gravity and balance_class option.

* Change flag, change load_infos to repeat_indices.

* Remove pdb, change docstring.

* Change name, remove unnecessary args.

* Remove _concat_dataset.

* Change name of ClassSampledDataset.

* Change docstring.

* Add get_cat_ids in nus_dataset, add unittest for wrapper.

* Change to len(self.dataset)

* Update nus data.