Avoids naming clash with torchvision CocoDetection class

* make pixel indexes 0-based for bounding box in pascal voc dataset

* replacing all instances of torch.distributed.deprecated with torch.distributed

* replacing all instances of torch.distributed.deprecated with torch.distributed

* add GroupNorm

* add GroupNorm -- sort out yaml files

* use torch.nn.GroupNorm instead, replace 'use_gn' with 'conv_block' and use 'BaseStem'&'Bottleneck' to simply codes

* modification on 'group_norm' and 'conv_with_kaiming_uniform' function

* modification on yaml files in configs/gn_baselines/ and reduce the amount of indentation and code duplication

* use 'kaiming_uniform' to initialize resnet, disable gn after fc layer, and add dilation into ResNetHead

* agnostic-regression for bbox

* please set 'STRIDE_IN_1X1' to be 'False' when backbone use GN

* add README.md for GN

* add dcn from mmdetection

* add documentation for finetuning cityscapes

* add documentation for finetuning cityscapes

* add documentation for finetuning cityscapes

* add 'once_differentiable' for dcn and modify 'configs/cityscapes/README.md'

* rectify the 'padding' for 'DFConv2d'

* Update documentation for testing and calculating mAP for each class

* Update documentation for testing and calculating mAP for each class

* Add ImportError to generic except

* Black formatter

* OpenCV is no longer optional

* Update README w.r.t. FPN_POST_NMS_PER_BATCH

* make pixel indexes 0-based for bounding box in pascal voc dataset

* replacing all instances of torch.distributed.deprecated with torch.distributed

* replacing all instances of torch.distributed.deprecated with torch.distributed

* add GroupNorm

* add GroupNorm -- sort out yaml files

* use torch.nn.GroupNorm instead, replace 'use_gn' with 'conv_block' and use 'BaseStem'&'Bottleneck' to simply codes

* modification on 'group_norm' and 'conv_with_kaiming_uniform' function

* modification on yaml files in configs/gn_baselines/ and reduce the amount of indentation and code duplication

* use 'kaiming_uniform' to initialize resnet, disable gn after fc layer, and add dilation into ResNetHead

* agnostic-regression for bbox

* please set 'STRIDE_IN_1X1' to be 'False' when backbone use GN

* add README.md for GN

* add dcn from mmdetection

* add documentation for finetuning cityscapes

* add documentation for finetuning cityscapes

* add documentation for finetuning cityscapes

* add 'once_differentiable' for dcn and modify 'configs/cityscapes/README.md'

* make pixel indexes 0-based for bounding box in pascal voc dataset

* replacing all instances of torch.distributed.deprecated with torch.distributed

* replacing all instances of torch.distributed.deprecated with torch.distributed

* add GroupNorm

* add GroupNorm -- sort out yaml files

* use torch.nn.GroupNorm instead, replace 'use_gn' with 'conv_block' and use 'BaseStem'&'Bottleneck' to simply codes

* modification on 'group_norm' and 'conv_with_kaiming_uniform' function

* modification on yaml files in configs/gn_baselines/ and reduce the amount of indentation and code duplication

* use 'kaiming_uniform' to initialize resnet, disable gn after fc layer, and add dilation into ResNetHead

* agnostic-regression for bbox

* please set 'STRIDE_IN_1X1' to be 'False' when backbone use GN

* add README.md for GN

* add dcn from mmdetection

* add documentation for finetuning cityscapes

* add documentation for finetuning cityscapes

* add documentation for finetuning cityscapes

* Initial multi-precision training

Adds fp16 support via apex.amp
Also switches communication to apex.DistributedDataParallel

* Add Apex install to dockerfile

* Fixes from @fmassa review

Added support to tools/test_net.py
SOLVER.MIXED_PRECISION -> DTYPE \in {float32, float16}
apex.amp not installed now raises ImportError

* Remove extraneous apex DDP import

* Move to new amp API

* proposals from RPN per image during training

* README

* Update README for setting FPN_POST_NMS_TOP_N_TRAIN

* Update README.md

* removing extra space change

* add color jitter augmentation

* fix spelling

* make pixel indexes 0-based for bounding box in pascal voc dataset

* replacing all instances of torch.distributed.deprecated with torch.distributed

* replacing all instances of torch.distributed.deprecated with torch.distributed

* add GroupNorm

* add GroupNorm -- sort out yaml files

* use torch.nn.GroupNorm instead, replace 'use_gn' with 'conv_block' and use 'BaseStem'&'Bottleneck' to simply codes

* modification on 'group_norm' and 'conv_with_kaiming_uniform' function

* modification on yaml files in configs/gn_baselines/ and reduce the amount of indentation and code duplication

* use 'kaiming_uniform' to initialize resnet, disable gn after fc layer, and add dilation into ResNetHead

* agnostic-regression for bbox

* please set 'STRIDE_IN_1X1' to be 'False' when backbone use GN

* add README.md for GN

* add dcn from mmdetection

https://gist.github.com/botcs/a59f3f59e22e5df93e3e5e4f86718af3

* fix py2

* fix py2

* support RLE and binary mask

* do not convert to numpy

* be consistent with Detectron

* delete wrong comment

* [WIP] add tests for segmentation_mask

* update tests

* minor change

* Refactored segmentation_mask.py

* Add unit test for segmentation_mask.py

* Add RLE support for BinaryMaskList

* PEP8 black formatting

* Minor patch

* Use internal  that handles 0 channels

* Fix polygon slicing