GitLab

* add sample data for waymo dataset unit test

* support getitem unit test

* unit test for show

* unfinished evaluate unit test

* KITTI format evaluate done, Waymo format uncomplete

* add format_results unit test

* make waymo sample data size small

* remove unused comment

* add pipeline show test

* finish

* compress img size

* [Feature] Adding PWC metafile

* fix url in nuimages

* removing inaccurate training time

* refine pwc index

* refine training resources

* removing empty metric of metafile in regnet

* removing 'Focal_Loss' and 'SECOND' from Architecture

* typos in gitignore

* modify customize_runtime docs

* update MMGen description

* replace mmdet with mmdet3d

* add MMOCR

* remove registry.py in datasets/

* remove registry.py in ops/pointnet_modules/

* remove registry.py in models/

* refactor builder using mmcv.MODELS registry

* update mmcv min version requirement

* change min mmcv version requirement in mmdet3d/__init__.py

* min mmcv version to 1.3.2

* fix small errors in seg dataset cfgs

* add box field to 3d seg dataset

* fix small bug in S3DIS data generation scripts

* fix small bugs in scannet data generation

* efficient mapping by matrix indexing

* add pointsegmapping unit test

* add max_cat_id args everywhere PointSegClassMapping is called in codebase

* add default value for max_cat_id for safety

* add assertion of max_cat_id

* Support base mono3d dense head and anchor free mono3d head

* Support FCOS3D head

* Support FCOS3D baseline on nuScenes

* Fix an import error caused by update of mmcv/mmdet

* Change img_scale to scale_factor in the MultiScaleFlipAug in the config

* Add pred_bbox2d in the params of anchor_free_mono3d_head

* Add unit test for fcos3d head

* Fix a minor bug when setting img_metas in the unit test

* Add unit test for fcos3d detector

* Simplify the logic of weights initialization

* Add comments to specify the reason of cloning features

* Update head config

* 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

* Update GlobalRotScale in the config of pointpillars benchmark

* Update config in the ObjectNoise

* add QR code & add MMGen

* modify tag to comment

* update re-expression

* Clamp 2D Projection of 3D Votes to Image Boundaries

* 'lint'

* 'lint;

* lint
Co-authored-by: Yezhen Cong <52420115+THU17cyz@users.noreply.github.com>

* fix #460 and simplify configs

* fix duplicate key error

* delete unused _delete_

* add cosine docstring and fixed a bug

* revert config files under benchmark folder

* add type to runner in benchmark configs

* remove irrelevant change

* reuse pipeline in scannet-det dataset

* reuse pipeline in kitti dataset

* reuse pipeline in lyft dataset

* reuse pipeline in sunrgbd dataset

* reuse pipeline in nuscenes dataset

* reuse pipeline in waymo dataset

* reuse pipeline in scannet-seg dataset

* add eval_pipeline in configs which have custom data pipelines

* move data loading via pipeline to dataset._extract_data() for clarity

* use eval_pipeline in tools/misc/visualize_results.py

* get_pipeline from self when no pipeline is provided

* fix small bugs

* fix small bugs

* simplify and clear code

* remove unnecessary eval_pipeline added

* add comment about why we set self.test_mode=False

* small fix

* modify docs about config

* modify PointShuffle and add unittest

* modify PointsRangeFilter and add unittest

* fix small bugs in IndoorPointSample

* fix small typos in docstring

* Support single stage mono3d detector

* Add single stage mono3d detector in the init

* Support FCOS Mono3D detector

* Minor adjustment of docstring

* Fix detector import

* Move numpy import to header

* 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

* uncomplete

* support lidar2img loading

* add box_type_3d args in MVX-Net config file

* support multi-modality demo for LiDAR point clouds

* support multi-modality demo for indoor (depth) point clouds

* move demo data into folder and modify docs

* add input check & more general filename matching

* update docs for demo and add README file for demo

* add score_threshold option to demos

* add data for ScanNet & KITTI dataset multi-modality test

* add multi-modality visualization in ScanNet and KITTI dataset

* add unittest for modified visualization function

* delete saved temp file and dirs in unittests using TemporaryDirectory

* fix typos in docs & move README of demos to docs/

* add demo docs to documentation

* fix link error
Co-authored-by: wHao-Wu <wenhaowu.chn@gmail.com>

* browse_dataset

* move visualization config from 'configs/' to 'configs/_base_'

* refine

* refine

* adding argument option & browsing testing split only

* support get_loading_pipeline & browsing training split

* support get_loading_pipeline & browsing training split

* support get_loading_pipeline & browsing training split

* add condition of RepeatDataset & support the usage of cfg-options & refine useful_tools.md

* add condition of RepeatDataset & support the usage of cfg-options & refine useful_tools.md

* enable dataset browsing with empty gt & update docs/useful_tools

* support all 3d dataset

* fix small typos

* fix small bugs
Co-authored-by: Wuziyi616 <dazitu616@gmail.com>

* 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