GitLab

* define data pipelines

* update two config files

* minor fix for config files

* allow img_scale to be optional and update config

* add some docstrings

* add extra aug to transform

* bug fix for mask resizing

* fix cropping

* add faster rcnn example

* fix imports

* fix robustness testing

* add img_norm_cfg to img_meta

* fix the inference api with the new data pipeline

* fix proposal loading

* delete args of DefaultFormatBundle

* add more configs

* update configs

* bug fix

* add a brief doc

* update gt_labels in RandomCrop

* fix key error for new apis

* bug fix for masks of crowd bboxes

* add argument data_root

* minor fix

* update new hrnet configs

* update docs

* rename MultiscaleFlipAug to MultiScaleFlipAug

* add __repr__ for all transforms

* move DATA_PIPELINE.md to docs/

* fix image url

* add testing in Travis

* add proj. requirements

* install CUDA

* def tested packages

* add missing meta in setup

* add empty test

* restructure travis tests

* add sample doctest

* switch to nose2

* add sample test

* using pytest

* minor fixes

If list gt_ignore was empty, it should become None after the following if statement: if not gt_ignore, which was not getting handled correctly. Changed gt_ignore = gt_ignore to gt_ignore = None.

* add coco analyze tool

* update

* update

* update

* update

* update

* update model zoo

* update model zoo

* update model links

* update HRNet README

* update HRNet README

* remove .DS_Store

* update HRNet results

* update HRNet results and remove .DS_Store

* update FCOS results

* update HRFPN to support FCOS

* remove blank line

* remove blank line

* update Modelzoo

* update models

* update model url

* fix typo

* fix typo

* change name of backbones

* add 20e to cascade w18

* update url

* add flops counter

* minor fix

* add forward_dummy() for most detectors

* add documentation for some tools

* add dockerfile

* update installation guide

* minor fix

* update readme

* add different datasets on model zoo

* Fix bug of FCOS when image has no positive sample

* somes changes for fcos

* Allowing validation dataset for computing validation loss

* added validation dataset

* fixing datasets errors

* Fixing linting errors

* Added vertical flipping in bbox_flip

* Fixed linting errors

* Fixed linting errors

* Added a blank line in docstrings

* Fixed linting errors.

* Add robust detection benchmark

* Update readmes

* Changed readmes for pull request

* Ensure pep8 conformity

* fixed formatting

* Fix yapf errors

* minor formatting

* fix imports order

* bug fix for recursive imports

* minor formatting

* fix the imports in __init__.py

* update contribution guide

* add isort config

* use isort to sort imports

* add isort to travis

* add major components for training double head

double head only with two losses and no attention

remove double_head detector for now, merge upchannel to double_head bbox head

change the stype using yapl

remove uncessary comment#

to pass check

to pass v2

to pass v3

line too long and style again

reuse bottlenet

* refactoring

* bug fix

* bug fix for weight initialization

* add reg roi scale factor and modify loss weights

* rescale the roi after mapping to fpn levels

* format the codebase with yapf

* add yapf to travis

* restructure the ops directory

* add some repr strings

* added cityscapes

* updated configs

* removed wip configs

* Add initial dataset instructions

* Add cityscapes readme

* Add explanation for lr scaling

* Ensure pep8 conformity

* Add CityscapesDataset to the registry

* add benchmark

* rename config, modify README.md

* fix typo

* fix typo in config

* modify INSTALL.md

Update information how to arrange cityscapes data.

* Add cityscapes class names

* Require an operation(Save or Show the results) when testing

* using parentheses

* Warning when skip image

* added parameter skip_img_without_anno for dataset

* print filename when warning