* fix #4181, invalid link in readme for maskrcnn cityscapes

* undo

* get the last epoch from config

* read eval metrics from the config key

* read the latest log from multiple logs

* use lower case of RESULTS_LUT

* handle evaluation key with VOC dataset case

* toy

* move the position of scipy import

* move the position of scipy import

* fix invalid link of config in faster_rcnn

* supports for DETR transformer

* unit test with small data to avoid out of memory in CI

* use batch size 1 for unit test to avoid out of memory

* move transformer into utils folder and use more small data for unit test

* reformat docstring

* add more detailed docstring

* reforamt

* reformat and add build_transformer (#3866)

* Supports for DETR position embedding (#3850)

* supports for DETR position embedding

* reformat docstring

* reformat

* move transformer_head folder into utils

* remove unnecessary comments

* reformat

* reformat

* reformat docstring

* reformat

* add optional for default parameters

* add comments for unit test

* avoid inplace in MultiheadAttention and add optional add_residual for FFN

* Supports for DETR inference (#3941)

* fix forward in FFN

* supports detr inference mode with batchsize 1

* add docstring for DETR in detr.py

* reformat and add doctest for TransformerHead

* reformat, and move the mask construction from simple_test in detr.py to the forward process of transformer_head

* rename detr_r50_1x_coco as detr_r50_8x4_1x_coco in config

* reformat

* mask input_img_shape in img_meta as a general modification of base_detector forward_test

* reformat

* Supports for DETR hungarian matcher. (#3929)

* Add doc of modify loss (#3777)

* add doc of modify loss

* minor fix

* change name

* improve the function of simple_test_bboxes (#3853)

* update

* fix lint error

* add bbox_pred_split in sabl_head

* fix lint error

* fix yapf

* fix build error

* fix yapf

* Clean background_labels in the dense heads (#3221)

* Clean background_labels in the dense heads

* clean format

* Reformat

* Fix CI bug

* fix fsaf and the comments

* fix newly added heads

* fix yolact

* complete comments

* fix rpn transforming bug in two stage networks (#3754)

* fix rpn transforming bug in two_stage

* [Refactor] refactor get_subset_by_classes in dataloader for training with empty-GT images (#3695)

* Add regression test and test data

* Add fix for empty gt images

* Trigger CI build

* refactor get_subset_by_classes

* reformat and fix docstring

* [refactor]: move get_subset_by_classes to _filter_imgs

* make img_ids consistent

* resolve comments

* simplify logics

* add warning

* add warning

* add warning

Co-authored-by: mmeendez8 <miguelmndez@gmail.com>

* Fix nonzero in NMS for PyTorch 1.6.0 (#3867)

* Support TTA of ATSS, FCOS, YOLOv3 (#3844)

* Support TTA of ATSS, FCOS, YOLOv3

* Add comment

* [Docs] Fix typo in docs/tutorials/new_dataset.md (#3876)

* [Docs] Remove duplicate content in docs/config.md (#3875)

* [Enhance]: Convert mask to bool before using it as img's index for robustness and speedup (#3870)

* Convert mask to bool before using it as img's index

* lint

* Rewrite code in more concise way

* Fix typo in bbox_flip (#3886)

* fix the API change bug of PAA (#3883)

* fix cv2 import error of ligGL.so.1 (#3891)

* [enhance]: Improve documentation of modules and dataset customization (#3821)

* update tutorials for changing training settings

* update

* Update details of hook

* resolve comments

* reformat

* Update module documentations

* add notes for classes specification

* support to use pytorch 1.6 in docker (#3905)

* support to use pytorch 1.6 in docker

* update mmcv requirement

* update docs

* Add missing notes in data customization (#3906)

* [Fix]: fix mask rcnn training stuck problem when there is no positive rois (#3713)

* Fix mask rcnn stuck problem when there is no positive rois

* support non pos inference in cascade methods, link CU-49tawu

* print mmcv version in CI

* use mmcv repo to check wrappers

* change cpu build

* upgrade mmcv requirements and change ci back

* use pre-built whl in CI

* Bump to v2.5.0 (#3879)

* bump to v2.5.0

* update PR

* resolve comments

* clean unnecessary modification

* update bc breaking

* rephrase bc-breaking

* rephrase

* Added `generate_inputs_and_wrap_model` function for pytorch2onnx (#3857)

* added `generate_inputs_and_wrap_model` function for pytorch2onnx

* undo debugging changes

* added model.cpu().eval()

* refactored onnx

* fix verify

* move `generate_inputs_and_wrap_model` into mmdet.core.export

* use `generate_inputs_and_wrap_model` in tools/pytorch2onnx.py

* typo (#3917)

* Edit mmdet.core.export docstring (#3912)

* edit mmdet.core.export docstring

* update doctest

* fix small bugs

* supports for HungarianMatchAssigner, add bbox_cxcywh_to_xyxy and bbox_xyxy_to_cxcywh for bbox transform

* format box-wise related giou calculating as a function and implement it in iou2d_calculater.py

* supports for BboxGIoU2D and re-implements giou_loss using bbox_gious

* remove unnecessary

* reformat

* reformat docstring

* reformat

* rename

* supports for giou calculating in BboxOverlaps2D, and re-implements giou_loss using bbox_overlaps

* fix sabl validating bug in cascade_rcnn (#3913)

* reformat

* move giou related unit test from test_losses.py to test_iou2d_calculator.py

* reformat

* Avoid division by zero in PAA head when num_pos=0

* [Fix]: Avoid division by zero in PAA head when num_pos=0 (#3938)

* explicitly add mode in giou_loss

* Add supports for giou calculation in BboxOverlaps2D, and re-implements giou_loss using bbox_overlaps (#3936)

* supports for BboxGIoU2D and re-implements giou_loss using bbox_gious

* remove unnecessary

* reformat

* reformat docstring

* reformat

* rename

* supports for giou calculating in BboxOverlaps2D, and re-implements giou_loss using bbox_overlaps

* reformat

* move giou related unit test from test_losses.py to test_iou2d_calculator.py

* reformat

* Avoid division by zero in PAA head when num_pos=0

* explicitly add mode in giou_loss

* Add supports for giou calculation in BboxOverlaps2D, and add iou_calculator in hungarian_assigner

* rename hungarian_match_assigner as hungarian_assigner

* fix init

* reformat docstring

* Avoid division by zero in PAA head when num_pos=0

* fix cpu (#3948)

* add mode for iou_calculator and make giou cost as a default case

* make mode as a param in iou_calculator

* reformat docsting

* make iou_mode outside of iou_calculator

Co-authored-by: Cao Yuhang <yhcao6@gmail.com>
Co-authored-by: yuzhj <31239926+yuzhj@users.noreply.github.com>
Co-authored-by: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com>
Co-authored-by: mmeendez8 <miguelmndez@gmail.com>
Co-authored-by: Yosuke Shinya <42844407+shinya7y@users.noreply.github.com>
Co-authored-by: LabMemNo003 <LabMemNo003@gmail.com>
Co-authored-by: Ye Liu <yeliudev@outlook.com>
Co-authored-by: aboettcher <aboettcher@users.noreply.github.com>
Co-authored-by: Ryan Li <xlide@connect.ust.hk>
Co-authored-by: Jiangmiao Pang <pangjiangmiao@gmail.com>

* Re-implements RandomCrop to support different crop_type (#4093)

* re-implements RandomCrop to support different crop_type

* add assertion for relative related crop_type

* reformat, and add image shape assertion for unit test

* reformat

* Supports for DETR training mode in process. (#3963)

* add input_img_shape in img_meta, and supports training mode toy

* toy commit

* toy commit

* re-organize and support for detr training mode

* add unit test for detr training, testing, and transformer_head

* add more unit test for transformer

* reformat

* remove unnecessary

* use small transformer model for unit test

* reformat docstring

* reformat

* reformat

* Supports DETR e150 config (#4197)

* rename e300 config as e150 config

* reformat

* add comments on override option in Resize

* add comments on override option in Resize

* position embeddingto positional encoding

* fix unit tests

* fix registry name bug

* rename file

* remove unnecessary

Co-authored-by: ZwwWayne <wayne.zw@outlook.com>
Co-authored-by: Cao Yuhang <yhcao6@gmail.com>
Co-authored-by: yuzhj <31239926+yuzhj@users.noreply.github.com>
Co-authored-by: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com>
Co-authored-by: mmeendez8 <miguelmndez@gmail.com>
Co-authored-by: Yosuke Shinya <42844407+shinya7y@users.noreply.github.com>
Co-authored-by: LabMemNo003 <LabMemNo003@gmail.com>
Co-authored-by: Ye Liu <yeliudev@outlook.com>
Co-authored-by: aboettcher <aboettcher@users.noreply.github.com>
Co-authored-by: Ryan Li <xlide@connect.ust.hk>
Co-authored-by: Jiangmiao Pang <pangjiangmiao@gmail.com>

* Update pytorch2onnx.py which using new logic to convert pytorch to ONNX

* use standard API to check whether in ONNX convert process

* only compare the score value while verifying results between ONNX and pytorch

* move import onnx before import torch, or something weird will happen

* use real images for input

* modifying the way of calling nms

* modify docstring for bbox2result, and remove unnecessary part for onnx exporting

* modify the 'Convert to ONNX' part in docs

* replace or to | in docstring

* update according to the latest mmcv

* add normalize part

* raise error while using low version mmcv

* minor update

* minor update

Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>

* Refine docs and fix format issues

* reformat

* fix mock

* Refine format

* Reorganize tutorials

* clean op

* clean

* update build.yml

* fix setup

* change ci mmcv version

* change ci mmcv version

* add install pre-build mmcv instructions

* update mmcv url, move some unnit tests to mmcv

* update ci mmcv

* test

* test

* test

* fix unit test

* fix unit test

* fix onnx script

* update mmcv url

* fix typo

* fix some doc

* Bump version

* resolve comments

* Fix version bug

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

* fix typo in docs and docstring

* update launch utility url

* Add colab training tutorial

* Update tutorial codes and fix bug

* Clean files, refactor TBD

* Update tutorials

* Remove duplicated code

* Mv tutorial

* update docstring formats

* fix :func:

* minor update

* Create model file

* Update README.md

* update model url

Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>

* fix bbox_loss in fovea_head.py when num_pos=0

* Remove PIL from .isort.cfg

* Make loss_bbox scalar in fovea_head.py when num_pos==0

* Sum based reduction for loss_bbox in fovea_head

* reverting to scalar implementation

* refactor resnet, add deep_stem and avg_down opt

* move args into kwargs

* add default

* mv resnetv1d to resnet

* fixed res_layer

* add base_channels

* add doc

* add tests

* update test

* fixed backbone block conv_cfg/norm_cfg

* add test

* add tests

* add onnx convert script

* upload pytorch2onnx.py

* restore config

* set use_torchvion on-the-fly, update doc

* update doc

* support pass input

* fixed passes

* reimplement cityscapes

* fixed gt bbox mode

* convert cityscapes to coco style, add cityscapes eval

* add cityscapes convert script

* add doc

* Update INSTALL.md

* Update INSTALL.md

* update fater rcnn

* fix cityscapes eval

* support format only in cityscapes

* add docs

* remove redundancy

* resolve eval

* update cityscapes md

* more doc and rename

* update doc and cfg

* change to test set

* add soft_nms_cpu

* remove cython dependency

* merge soft_nms_cpu.cpp into nms_cpu.cpp

* add docs

* fixed typo

* fixed typo

* fixed typo

* add GN support for flops computation

* remove useless lines

* modify the flops computation for gn

* collect env info for trouble shoting

* minor fix

* update the issue template

* fix the travis building

* update setup classifiers

* update to v1.0rc1

* update maintainers

* Added pre-commit hook

* Trigger CI

* add isort config

* use isort to sort imports

* add isort to travis