GitLab

* 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

- fix 'invalid configuration argument' error triggered by empty point input. test cases covering similar situations are added to test_dynamic_scatter.py as well.
trivial changes:
- switch to using torch::unique_dim to generate reduce mapping instead of calculating it from scratch.

* support nuimages visualization

* recover config

* support nuimages visualization

* support batchsize > 1

* add comments

* 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

* fix pt1.8 issues

* fix pt1.8 issues

* Update README.md

* Update README_zh-CN.md

* Update getting_started.md

* Update changelog.md

* Change pdf to abs link and revise the highlights

* modify vote_head to support 3dssd

* delete .keys()

* add 3dssd unittest

* 3dssd->ssd3d

* sunrgbd doc update and change in image path

* rephrase

* add 3dssd model and log link

* add kitti devkit evaluation result

* update perfermance

* update perfermance

* modify perfermance

* add numba and numpy version problem to FAQ

* delete duplicate docs

* modify numpy->numba

* add workaround

* numpy version < 1.20.0

* modify docstring

* Update faq.md
Co-authored-by: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com>

* fix compilation error in pytorch 1.7

* add pt1.7 build

* Update build.yml

* fix link to convert_votenet_checkpoints.py

* remove redundant space in docstring

* fix typos

* fix link and latex citation in README

* fix link error for publish_model.py

* fix link error for regnet2mmdet.py

* fix link error for files under tools/misc/ folder

* fix link error for files under tools/analysis_tools/ folder

* fix latex citation in README_zh-CN.md

* fix typo and a link to mmdet

* add model zoo

* change bibtex and more doc

* support nuscenes dataset in demo

* add convert_SyncBN in __init__

* fix meshlab visualization bug

* modify meshlab unittest

* add docstring

* add empty line in docstring
Co-authored-by: xiliu8006 <xiliu800@gmail.com>

* 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 a bug when adding val to workflow

* update

* Avoid 4 dims points

* add assert prinf

* modify print info

* fix SECOND Waymo results

* fix pr number

* support knn gpu op

* made it more robust and fixed comments

* bugfix and add warning in docstring

* add citation format

* add CN version citation format

* delete 's

* delete 's

* modify citation title

* Update README.md

* Update README_zh-CN.md

* Update README.md

* support knn gpu op

* made it more robust and fixed comments

* add ini

* add semantickitti_dataset

* add test semantickitti_dataset

* delete last line in test_semmaticdataset

* add test data

* change_names

* load_labels dytype

* change_name

* numpy

* name

* dtype string

* minor issue-string

* seg_3d_dtype

* add_fast hist

* add per_class iou

* add seg_eval

* add unitest

* minor error

* minor error2

* minor error3

* refactor

* refactor train/test

* refactor train/test

* refactor train.py/test.py

* refactor train.py/test.py --- specify default of seed to 0 & save mmdet version instead of mmdet3d git hash

* refactor train.py/test.py --- specify default of seed to 0 & save mmdet version instead of mmdet3d git hash

* add faq

* faq revised

* faq revised

* faq revised

* faq revised

* faq revised --- add title & add line to index.rst

* Update README.md

* Update README_zh-CN.md

* Update getting_started.md

* Update version.py

* Update changelog.md

* Update changelog.md

* Update changelog.md

[Fix] fix a bug that may cause compilation failure of dynamic voxelization when using GPUs with compute capability lower than 6.x (#326)

* fix a bug that may cause compilation failure of dynamic voxelization when using gpus with compute capability lower than 6.x
fix imperfection kernel code that may unintentionally discard valid points when input points count is larger than 50000 * 512 (nearly impossible though).

* Modified scatter_points_cuda.cu to ensure backward compatibility with PyTorch1.5 on CUDA9.0

* fix the issue of DynamicScatter gradient check failure by explicit mark non-floating-point tensor as non-differentiable.

* fix nonzero warning with as_tuple

* fix nonzero warning with as_tuple #320

* Reduce the open3d dependency

* Reduce the open3d dependency

* Reduce dependency of open3d if open3d is not used

* remove the warning in show_result

* a faster & more memory-efficient implementation of DynamicScatter

* fix format issues and add pytest skip code for tests on machines without cuda support

* some trivial changes:

decrease the number of kernel threads per block to 512, to enable inference on GPUs with computing capability lower than 2.0

change the backpropagation behavior of max-reduction. when there are multiple points shares the same maximum feature value, only the first point (with lowest row index) among them is chosen to propagate the output gradient back. before this change, all points with the same maximum feature value can propagate the output gradient back. this change makes the max-reduction behaves in consistence with torch.max. this change may cause gradcheck failure in test_dynamic_scatter.py. please do not worry about it because torch.max fails the gradcheck too.

* fix typo
Co-authored-by: zhanggefan <1152009@tongji.edu.cn>