GitLab

* reorganize requirements, make albumentations optional

* fix flake8 error

* force older version of Pillow until torchvision is fixed

* make imagecorruptions optional and update INSTALL.dm

* update INSTALL.md

* Add note about pillow version

* Add build requirements to install instructions

* First Draft

On branch non-color-images
Changes to be committed:
modified:   mmdet/datasets/pipelines/loading.py

* Add option to load non color images

Add 'color_type' parameter to LoadImageFromFile class
Change __repr__ method accordingly
Since non-color images maybe two dimensional expand image
dimensions if necessary in DefaultFormatBundle and
ImageToTensor classes

Changes to be committed:
    modified:   mmdet/datasets/pipelines/formating.py
    modified:   mmdet/datasets/pipelines/loading.py

* Fix RandomCrop to work with grayscale images

Changes to be committed:
    modified:   mmdet/datasets/pipelines/transforms.py

* Modify retrieving w, h of padded image in anchor heads

This addreses problems with single channel images for which the
shape is  tuple with 2 values

Changes to be committed:
    modified:   mmdet/models/anchor_heads/anchor_head.py
    modified:   mmdet/models/anchor_heads/guided_anchor_head.py
    modified:   mmdet/models/anchor_heads/reppoints_head.py

* add crop seg to RandomCrop trans

* minor fix comment

* Split seg trans

* Modify cfg

* fix typo

* Allow for images to contain zero true detections

* Allow for empty assignment in PointAssigner

* Allow ApproxMaxIouAssigner to return an empty result

* Fix CascadeRNN forward when entire batch has no truth

* Correctly assign boxes to background when there is no truth

* Fix assignment tests

* Make flatten robust

* Fix bbox loss with empty pred/truth

* Fix logic error in BBoxHead.loss

* Add tests for empty truth cases

* tests faster rcnn empty forward

* Skip roipool forward tests if torchvision is not installed

* Add tests for bbox/anchor heads

* Consolidate test_forward and test_forward2

* Fix assign_results.labels = None when gt_labels is given; Add test for this case

* Fix OHEM Sampler with zero truth

* remove xdev

* resolve 3 reviews

* Fix flake8

* refactoring

* fix yaml format

* add filter flag

* minor fix

* delete redundant code in load anno

* fix flake8 errors

* quick fix for empty truth with masks

* fix yapf error

* fix mask padding for empty masks
Co-authored-by: Cao Yuhang <yhcao6@gmail.com>
Co-authored-by: Kai Chen <chenkaidev@gmail.com>

* reformat for yapf0.29

* fix conflicts of yapf and flake8

* flake 8 is prior than yapf

* Update GETTING_STARTED.md

Found out that this method is required. The torch.nn.Module doesn't contain this method thus you need to implement it

* update docstring 

see https://github.com/open-mmlab/mmdetection/issues/1582

* correct for flake8

* flake8: trailing space has removed

Allows to use not only 0.5 probability.

* Add seg transform to Expand and MinIoUCrop

* fix bug of repr

* Albumentations wrapper

* 2 single quote format

* version >= 0.3.2

* add g++ requirement for INSTALL.md.

* fix bugs for cropping masks in RandomCrop.

* simplify the code to fix bugs for cropping masks in RandomCrop.

* fix bug of ssd

* clean

* 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