* Add markdown lint in pre-commit hook

* add markdown lint

* fixed typos

* replace url with download

* update to http

* update inf speed

* update some models

* update benchmark config and model

* add no aug config

* merge log model table with performance table

* add detectron2 url

* add configs for all models

* fix some configs

* Add benchmark models

* update some benchmarks

* Fix retina config

* add more benchmarks

* update MODEL_ZOO.md

* fix cascade mask num_class bug

* change caffe pretrained url

* fix paramwise_cfg bug

* fix paramwise cfg

* restrict minimum h and w in crop_and_resize

* add grad clip for fcos

* add grad clip for ga retinanet

* fix grad clip

* fix img norm

* fix rpn loss bbox

* fix rpn proposal num

* fix url

* clean

* update comparison

* minor update

* add grad clip for guided anchoring

* fix some typos

* add inference time details

* clean

Co-authored-by: ZwwWayne <wayne.zw@outlook.com>

* add coder registry

* add coder for single stage

* rename to bbox_coder

* add doc string

* add doc string

* change default

* Refactor (all): all category -1 in anchor/bbox head and anchor/bbox target assign

* Fix (datasets): remove label + 1 in datasets

* Fix (bbox_head): fix bug of fc_cls that forget + 1

* Fix (atss_head & free_anchor): fix cat -1 bugs

* Fix (mask_head): remove label + 1 in mask heads

* fix atss

* Fix (rpn): fix cross_entropy_loss bug of RPN

* Fix (anchor_head): fix typo

* Refactor (anchor_head): use background_label rather than num_classes to indicate background class

* Refactor (docstring): add and reformat docstrings

* fix mask iou head

* Fix (mask_head): fix cat -1 bug

* Fix (mask_head): fix bug in mask inference

* Add (tests): add tests for mask rcnn and mask heads

* Refactor (unittest): refactor test_forward

* Refactor (new_empty): use new_full rather than new_empty

* Refactor (background_label): check background_label

* Add TODO

* Refactor (unittest): allow BP in unittest

Co-authored-by: Cao Yuhang <yhcao6@gmail.com>

* create roi_head

* create roi_head
mv shared_head into roi_head

* fix conflict

* refactor(cascade rcnn): create cascade head in roi head, simplify cascade rcnn

* type: fix
scope: cascade_head
subject: mv stage_loss_weight from train_cfg to roi_head creation

* type: fix
scope: roi_heads
subject: handle the case when train_cfg is None

* type: fix
scope: roi_heads mask inference
subject: fix test_cfg.rcnn bug to test_cfg

* fix mask eval bug

* refactor(double_head): refactor double head roi head

* fix(double_head): clean code and fix __init__.py

* refactor(mask scoring): create mask scoring roi head

* refactor(htc_head): add htc_head

* fix(htc_head): add htc_head in __init__.py

* fix (htc_head): fix htc_head bugs

* fix (ms_roi_head): rm test_cfg.rcnn to test_cfg

* feature (grid rcnn): grid roi head

* fix (grid_head): fix grid head bug

* reformat and change all cfgs

* reformat (roi_head): reformat __init__.py for isort=4.3.21

* fix roi_head test bug

* fix (carafe): change carafe cfgs to use roi_head

* fix (roi_head): fix missing roi_head refactor

* reformat to pass CI

* test all cfgs

* match keys of configs with previous commit 77d073a

* add and pass unittest for all roi heads

* Refactor (roi_head): extract abstract base class for roi head

* Refactor (roi_head): refactor init functions

* Refactor (roi_head): weight init

* Refactor (roi_head): add _bbox_forwrd & _mask_forward as basic functions

* Fix (grid_roi_head): fix bug in bbox_forward_train

* Refactor (roi_head): change to use img.device in forward_dummy)

* Refactor (roi_heads): simplify init functions and _mask_forward

* Fix (cascade_roi_head): fix init bug of cascade roi_head

* Refactor (roi_head): use dict as outputs of _bbox_forward and _mask_forward

* Refactor (test_config): scan valid configs rather than list them all

* delete work_dir in all configs

* add comment on work_dir priority

* add new config sample and check scripts

* context managere to prevent import

* refactor backbone, add caffe

* add fast rcnn

* all basci config done

* rm coco_proposal

* add scratch, wider_face, voc

* add reppoints

* delete device id, auto resume

* add libra_rcnn, ms_rcnn, nas_fpn

* add hrnet, fcos

* add free_anchor, gn, grid_rcnn, guided_anchoring, gcnet, ghm, gn+ws

* finished all, but some need refactor and unified logic

* fixed albu

* update ReseNet101

* reduce ResNet101, add norm_cfg, 4conv1fc

* refactor caffe backbone

* merge act_cfg, dcn from master

* rename 2fc head, add 4conv1fc head

* delete 4con1fc model

* rename components -> _base_

* flatten _base_

* refactor _base_ structure

* refactor config structure

* reduce _base/models

* rename all config

* add _coco inside configs

* fixed _coco in files

* fixed albu in test

* migrate to new sys

* fixed test

* fixed test

* rm cascade, fast_rcnn

* rm cascade, fast_rcnn from _base_

* fixed fcos_center

* rename from rule

* collopse third party model

* fixed test

* fixed some minor bug

* rename gn-neck_head -> gn-neck+head

* add norm_cfg in ResNet pytorch backbone

* delete redundent fields

* move evaluation part to datasets

* use dataset.evaluate() in testing scripts

* remove redundant codes

* fix some log formats

* update config with evaludation

* move evaluation below dataset

* remove coco_utils.py and fix test_robustness

Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>

* 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 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