* add support for pascal voc dataset and evaluate

* optimization for adding voc dataset

* make inference.py dataset-agnostic; add use_difficult option to voc dataset

* handle voc difficult objects correctly

* Remove dependency on lxml plus minor improvements

* More cleanups

* More comments and improvements

* Lint fix

* Move configs to their own folder

* add opencv support to Dockerfile

cv2 is used by predictor.py, so it's required

* install opencv-python from conda

* Add an option to postprocess masks during inference

* Fix COCO evaluation to resize masks ony if needed.

* Fix casting

* Fix minor issues in paste_mask_in_image

* Cast mask to uint8

* Make Masker batch compatible

* Remove warnings and stylistic changes

* fix some minor issues in dockerfile


RUN echo 'debconf debconf/frontend select Noninteractive' | debconf-set-selections
fixes
debconf: unable to initialize frontend: Dialog
debconf: (TERM is not set, so the dialog frontend is not usable.)
debconf: falling back to frontend: Readline
debconf: unable to initialize frontend: Readline
debconf: (This frontend requires a controlling tty.)
debconf: falling back to frontend: Teletype
dpkg-preconfigure: unable to re-open stdin: 

RUN apt-get update -y && apt-get install -y apt-utils
fixes
debconf: delaying package configuration, since apt-utils is not installed

* remove redundant command

* add -y to conda install and pip install

* remove -y from pip install

* added Dockerfile

* intructions for installation with docker

* INSTALL.md: added note to inform nvidia-docker only works with Linux

* dockerfile nccl2 hotfix

* INSTALL.md update

* removes explicit install of NCCL2 as it is included in the CUDA image

* adding registry to hook custom building blocks

* adding customizable rpn head

* support customizable c2 weight loading

* added Dockerfile

* intructions for installation with docker

* adds nccl to dockerfile

* Update Dockerfile

* Update INSTALL.md

## Bug
When I repeatedly invoke build_detection_model function to build the model, I will get the error: `AttributeError: 'ResNet' object has no attribute 'layer1'`. 

## To Reproduce
```
model = build_detection_model(cfg)
model = build_detection_model(cfg)
```

## The reason
The variable `ResNet50StagesTo4` is a global generator expression, so when we build the model secondly, the code executes to Line 82 `for stage_spec in stage_specs:` and `stage_specs` will return empty leading to do not add any stage. Finally, `self._freeze_backbone` try to freeze the backbone by executing `m = getattr(self, "layer" + str(stage_index))` firstly. At the moment, it will throw the AttributeError `AttributeError: 'ResNet' object has no attribute 'layer1'`.

I guess you want to define ResNet50StagesTo4 as the tuple, so I try to fix by add tuple type qualifier.

## The solution
Add the tuple type to `ResNet50StagesTo5`, `ResNet50StagesTo4`, `ResNet50FPNStagesTo5`, `ResNet101FPNStagesTo5`.

I do not know whether there are similar bug existing, so you need to review my solution. Thank you!

* quick fix for area

* Update bounding_box.py

use cuda version torch.randperm to avoid copy from gpu to cpu and a fatal bug in multi-thread cpu version

Replace BoxList argument size with image_size.

Replace baseline with benchmark

Fix BoxList constructor call in README.md

* Add missing __init__.py files

* Add packages

* Rename logging.py to logger.py

Import rules from Python2 makes this a bad idea

* Make import_file py2 compatible

* list does not have .copy() in py2

* math.log2 does not exist in py2

* Miscellaneous fixes for py2

* Address comments

Access repos via https in INSTALL.md

It is simpler and requires less effort (i.e. no auth) compared to SSH

Fix a small typo

Add ISSUE_TEMPLATE for Github