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[Docker] fix cv2 import error of ligGL.so.1 #3891

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merged 1 commit into from
Oct 8, 2020

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aboettcher
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When I train a faster_rcnn network with the current docker script I get the following error:

Traceback (most recent call last):
  File "tools/train.py", line 8, in <module>
    import mmcv
  File "/opt/conda/lib/python3.7/site-packages/mmcv/__init__.py", line 4, in <module>
    from .fileio import *
  File "/opt/conda/lib/python3.7/site-packages/mmcv/fileio/__init__.py", line 4, in <module>
    from .io import dump, load, register_handler
  File "/opt/conda/lib/python3.7/site-packages/mmcv/fileio/io.py", line 4, in <module>
    from ..utils import is_list_of, is_str
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/__init__.py", line 29, in <module>
    from .env import collect_env
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/env.py", line 8, in <module>
    import cv2
  File "/opt/conda/lib/python3.7/site-packages/cv2/__init__.py", line 5, in <module>
    from .cv2 import *
ImportError: libGL.so.1: cannot open shared object file: No such file or directory

If found a solution to this problem at stackoverflow

In the pull request I added the listed packages in the stackoverflow thread linked above into the existing list of packages.

With the fix I can train models as expected.

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CLAassistant commented Oct 6, 2020

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@aboettcher aboettcher changed the title fix cv2 import error of ligGL.so.1 [Docker] fix cv2 import error of ligGL.so.1 Oct 6, 2020
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codecov bot commented Oct 6, 2020

Codecov Report

Merging #3891 into master will decrease coverage by 0.32%.
The diff coverage is n/a.

Impacted file tree graph

@@            Coverage Diff             @@
##           master    #3891      +/-   ##
==========================================
- Coverage   62.34%   62.01%   -0.33%     
==========================================
  Files         219      219              
  Lines       16273    16193      -80     
  Branches     2760     2760              
==========================================
- Hits        10145    10042     -103     
- Misses       5632     5657      +25     
+ Partials      496      494       -2     
Flag Coverage Δ
#unittests 62.01% <ø> (-0.33%) ⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files Coverage Δ
mmdet/models/roi_heads/mask_scoring_roi_head.py 58.92% <0.00%> (-32.15%) ⬇️
mmdet/models/roi_heads/mask_heads/maskiou_head.py 92.22% <0.00%> (-5.63%) ⬇️
mmdet/core/bbox/coder/base_bbox_coder.py 75.00% <0.00%> (-5.00%) ⬇️
mmdet/models/roi_heads/base_roi_head.py 76.31% <0.00%> (-3.69%) ⬇️
mmdet/models/detectors/base.py 47.54% <0.00%> (-3.23%) ⬇️
mmdet/models/detectors/htc.py 87.50% <0.00%> (-1.39%) ⬇️
mmdet/models/necks/pafpn.py 41.86% <0.00%> (-1.33%) ⬇️
mmdet/core/bbox/samplers/base_sampler.py 73.17% <0.00%> (-1.25%) ⬇️
mmdet/models/losses/gfocal_loss.py 45.28% <0.00%> (-1.02%) ⬇️
mmdet/models/dense_heads/base_dense_head.py 89.47% <0.00%> (-1.01%) ⬇️
... and 25 more

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@ZwwWayne ZwwWayne merged commit aebbaff into open-mmlab:master Oct 8, 2020
wangruohui pushed a commit to wangruohui/mmdetection that referenced this pull request Oct 15, 2020
ZwwWayne added a commit that referenced this pull request Oct 19, 2020
* 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>
ZwwWayne added a commit that referenced this pull request Nov 29, 2020
* 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

Co-authored-by: v-qjqs <qjliqiaofei@gmail.com>
Co-authored-by: Qiaofei Li <34116221+v-qjqs@users.noreply.github.com>
Co-authored-by: Cao Yuhang <yhcao6@gmail.com>
Co-authored-by: yuzhj <31239926+yuzhj@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>
ZwwWayne added a commit that referenced this pull request Nov 29, 2020
* 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>
mattdawkins added a commit to VIAME/mmdetection that referenced this pull request Dec 3, 2020
* tag 'v2.5.0': (102 commits)
  Bump to v2.5.0 (open-mmlab#3879)
  [Fix]: fix mask rcnn training stuck problem when there is no positive rois (open-mmlab#3713)
  Add missing notes in data customization (open-mmlab#3906)
  support to use pytorch 1.6 in docker (open-mmlab#3905)
  [enhance]: Improve documentation of modules and dataset customization (open-mmlab#3821)
  fix cv2 import error of ligGL.so.1 (open-mmlab#3891)
  fix the API change bug of PAA (open-mmlab#3883)
  Fix typo in bbox_flip (open-mmlab#3886)
  [Enhance]: Convert mask to bool before using it as img's index for robustness and speedup (open-mmlab#3870)
  [Docs] Remove duplicate content in docs/config.md (open-mmlab#3875)
  [Docs] Fix typo in docs/tutorials/new_dataset.md (open-mmlab#3876)
  Support TTA of ATSS, FCOS, YOLOv3 (open-mmlab#3844)
  Fix nonzero in NMS for PyTorch 1.6.0 (open-mmlab#3867)
  [Refactor] refactor get_subset_by_classes in dataloader for training with empty-GT images (open-mmlab#3695)
  fix rpn transforming bug in two stage networks (open-mmlab#3754)
  Clean background_labels in the dense heads (open-mmlab#3221)
  improve the function of simple_test_bboxes (open-mmlab#3853)
  Add doc of modify loss (open-mmlab#3777)
  fix sabl validating bug (open-mmlab#3849)
  YOLACT (open-mmlab#3456)
  ...
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4 participants