* [Feature]Segformer re-implementation

* Using act_cfg and norm_cfg to control activation and normalization

* Split this PR into several little PRs

* Fix lint error

* Remove SegFormerHead

* parameters init refactor

* 1. Refactor segformer backbone parameters init;

2. Remove rebundant functions and unit tests;

* Remove rebundant codes

* 1. Remove rebundant codes;

2. Modify module name;

* Refactor the backbone of segformer using mmcv.cnn.bricks.transformer.py

* Fix some code logic bugs.

* Add mit_convert.py to match pretrain keys of segformer.

* Resolve some comments.

* 1. Add some assert to ensure right params;

2. Support flexible peconv position;

* Add pe_index assert and fix unit test.

* 1. Add doc string for MixVisionTransformer;

2. Add some unit tests for MixVisionTransformer;

* Use hw_shape to pass shape of feature map.

* 1. Fix doc string of MixVisionTransformer;

2. Simplify MixFFN;

3. Modify H, W to hw_shape;

* Add more unit tests.

* Add doc string for shape convertion functions.

* Add some unit tests to improve code coverage.

* Fix Segformer backbone pretrain weights match bug.

* resolve the shape convertion functions doc string.

* Add pad_to_patch_size arg.

* Modify default value of pad_to_patch_size arg.

* fix patch_embed and pos_embed mismatch error

* add docstring

* update unittest

* use downsampled image shape

* use tuple

* remove unused parameters and add doc

* fix init weights function

* revise docstring

* Update vit.py

If -> Whether

* fix lint

Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>

* add Swin Transformer

* add Swin Transformer

* fixed import

* Add some swin training settings.

* Fix some filename error.

* Fix attribute name: pretrain -> pretrained

* Upload mmcls implementation of swin transformer.

* Refactor Swin Transformer to follow mmcls style.

* Refactor init_weigths of swin_transformer.py

* Fix lint

* Match inference precision

* Add some comments

* Add swin_convert to load official style ckpt

* Remove arg: auto_pad

* 1. Complete comments for each block;

2. Correct weight convert function;

3. Fix the pad of Patch Merging;

* Clean function args.

* Fix vit unit test.

* 1. Add swin transformer unit tests;

2. Fix some pad bug;

3. Modify config to adapt new swin implementation;

* Modify config arg

* Update readme.md of swin

* Fix config arg error and Add some swin benchmark msg.

* Add MeM and ms test content for readme.md of swin transformer.

* Fix doc string of swin module

* 1. Register swin transformer to model list;

2. Modify pth url which keep meta attribute;

* Update swin.py

* Merge config settings.

* Modify config style.

* Update README.md

Add ViT link

* Modify main readme.md

Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>
Co-authored-by: sennnnn <201730271412@mail.scut.edu.cn>
Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>

* add config

* add cityscapes config

* add default value to docstring

* fix lint

* add deit-s and deit-b

* add readme

* add eps at norm_cfg

* add drop_path_rate experiment

* add deit case at init_weight

* add upernet result

* update result and add upernet 160k config

* update upernet result and fix settings

* Update iters number

* update result and delete some configs

* fix import error

* fix drop_path_rate

* update result and restore config

* update benchmark result

* remove cityscapes exp

* remove neck

* neck exp

* add more configs

* fix init error

* fix ffn setting

* update result

* update results

* update result

* update results and fill table

* delete or rename configs

* fix link delimiter

* rename configs and fix link

* rename neck to mln

* [Fix] Add setr & vit msg.

* Fix init bug

* Modify init_cfg arg

* Add conv_seg init

* Adjust vision transformer backbone architectures;

* Add DropPath, trunc_normal_ for VisionTransformer implementation;

* Add class token buring intermediate period and remove it during final period;

* Fix some parameters loss bug;

* * Store intermediate token features and impose no processes on them;

* Remove class token and reshape entire token feature from NLC to NCHW;

* Fix some doc error

* Add a arg for VisionTransformer backbone to control if input class token into transformer;

* Add stochastic depth decay rule for DropPath;

* * Fix output bug when input_cls_token=False;

* Add related unit test;

* Re-implement of SETR

* Add two head -- SETRUPHead (Naive, PUP) & SETRMLAHead (MLA);

* * Modify some docs of heads of SETR;

* Add MLA auxiliary head of SETR;

* * Modify some arg of setr heads;

* Add unit test for setr heads;

* * Add 768x768 cityscapes dataset config;

* Add Backbone: SETR -- Backbone: MLA, PUP, Naive;

* Add SETR cityscapes training & testing config;

* * Fix the low code coverage of unit test about heads of setr;

* Remove some rebundant error capture;

* * Add pascal context dataset & ade20k dataset config;

* Modify auxiliary head relative config;

* Modify folder structure.

* add setr

* modify vit

* Fix the test_cfg arg position;

* Fix some learning schedule bug;

* optimize setr code

* Add arg: final_reshape to control if converting output feature information from NLC to NCHW;

* Fix the default value of final_reshape;

* Modify arg: final_reshape to arg: out_shape;

* Fix some unit test bug;

* Add MLA neck;

* Modify setr configs to add MLA neck;

* Modify MLA decode head to remove rebundant structure;

* Remove some rebundant files.

* * Fix the code style bug;

* Remove some rebundant files;

* Modify some unit tests of SETR;

* Ignoring CityscapesCoarseDataset and MapillaryDataset.

* Fix the activation function loss bug;

* Fix the img_size bug of SETR_PUP_ADE20K

* * Fix the lint bug of transformers.py;

* Add mla neck unit test;

* Convert vit of setr out shape from NLC to NCHW.

* * Modify Resize action of data pipeline;

* Fix deit related bug;

* Set find_unused_parameters=False for pascal context dataset;

* Remove arg: find_unused_parameters which is False by default.

* Error auxiliary head of PUP deit

* Remove the minimal restrict of slide inference.

* Modify doc string of Resize

* Seperate this part of code to a new PR #544

* * Remove some rebundant codes;

* Modify unit tests of SETR heads;

* Fix the tuple in_channels of mla_deit.

* Modify code style

* Move detailed definition of auxiliary head into model config dict;

* Add some setr config for default cityscapes.py;

* Fix the doc string of SETR head;

* Modify implementation of SETR Heads

* Remove setr aux head and use fcn head to replace it;

* Remove arg: img_size and remove last interpolate op of heads;

* Rename arg: conv3x3_conv1x1 to kernel_size of SETRUPHead;

* non-square input support for setr heads

* Modify config argument for above commits

* Remove norm_layer argument of SETRMLAHead

* Add mla_align_corners for MLAModule interpolate

* [Refactor]Refactor of SETRMLAHead

* Modify Head implementation;

* Modify Head unit test;

* Modify related config file;

* [Refactor]MLA Neck

* Fix config bug

* [Refactor]SETR Naive Head and SETR PUP Head

* [Fix]Fix the lack of arg: act_cfg and arg: norm_cfg

* Fix config error

* Refactor of SETR MLA, Naive, PUP heads.

* Modify some attribute name of SETR Heads.

* Modify setr configs to adapt new vit code.

* Fix trunc_normal_ bug

* Parameters init adjustment.

* Remove redundant doc string of SETRUPHead

* Fix pretrained bug

* [Fix] Fix vit init bug

* Add some vit unit tests

* Modify module import

* Remove norm from PatchEmbed

* Fix pretrain weights bug

* Modify pretrained judge

* Fix some gradient backward bugs.

* Add some unit tests to improve code cov

* Fix init_weights of setr up head

* Add DropPath in FFN

* Finish benchmark of SETR

1. Add benchmark information into README.MD of SETR;

2. Fix some name bugs of vit;

* Remove DropPath implementation and use DropPath from mmcv.

* Modify out_indices arg

* Fix out_indices bug.

* Remove cityscapes base dataset config.

Co-authored-by: sennnnn <201730271412@mail.scut.edu.cn>
Co-authored-by: CuttlefishXuan <zhaoxinxuan1997@gmail.com>

* [Fix] Fix vit init bug

* Add some vit unit tests

* Modify module import

* Fix pretrain weights bug

* Modify pretrained judge

* Add some unit tests to improve code cov

* Optimize code

* Fix vit unit test

* [Refactor] Using mmcv bricks to refactor vit

* Follow the vit code structure from mmclassification

* Add MMCV install into CI system.

* Add  to 'Install MMCV' CI item

* Add 'Install MMCV_CPU' and 'Install MMCV_GPU CI' items

* Fix & Add

1. Fix low code coverage of vit.py;

2. Remove HybirdEmbed;

3. Fix doc string of VisionTransformer;

* Add helpers unit test.

* Add converter to convert vit pretrain weights from timm style to mmcls style.

* Clean some rebundant code and refactor init

1. Use timm style init_weights;

2. Remove to_xtuple and trunc_norm_;

* Add comments for VisionTransformer.init_weights()

* Add arg: pretrain_style to choose timm or mmcls vit pretrain weights.

* [Refactor]: Unified parameter initialization

* fixed pretrained

* Add arg: final_reshape to control if converting output feature information from NLC to NCHW;

* Fix the default value of final_reshape;

* Modify arg: final_reshape to arg: out_shape;

* Fix some unit test bug;

* mmcv eval hook

* mmcv evalhook compatible

* add warnings

* inherit from base class

* fix unitest

* adapt to mmcv 1.3.1

* fixed unittest

* set by_epoch=False

* fixed efficient test

* update docstring

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

* add mFscore and refactor the metrics return value

* fix linting

* some docstring and name fix

* Adjust vision transformer backbone architectures;

* Add DropPath, trunc_normal_ for VisionTransformer implementation;

* Add class token buring intermediate period and remove it during final period;

* Fix some parameters loss bug;

* * Store intermediate token features and impose no processes on them;

* Remove class token and reshape entire token feature from NLC to NCHW;

* Fix some doc error

* Add a arg for VisionTransformer backbone to control if input class token into transformer;

* Add stochastic depth decay rule for DropPath;

* * Fix output bug when input_cls_token=False;

* Add related unit test;

* * Add arg: out_indices to control model output;

* Add unit test for DropPath;

* Apply suggestions from code review

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

* support reading class_weight from file in loss function

* add unit test of loss with class_weight from file

* minor fix

* move get_class_weight to utils

* init

* upsample v1.0

* fix errors

* change to in_channels list

* add unittest, docstring, norm/act config and rename

Co-authored-by: xiexinch <test767803@foxmail.com>

* vit backbone

* fix lint

* add docstrings and fix pretrained pos_embed dim not match prob

* add unittest for vit

* fix lint

* add vit based fcn configs

* fix import error

* support multiple resolution input images

* upsample pos_embed at init_weights

* support resize pos_embed at evaluation

* fix training errors

* add more unitest code for vit backbone

* unitest for uncovered code

* add norm_eval unittest

* refactor _pos_embeding

* minor change

* change var name

* rafactor init_weight

* load weights after resize

* ignore 'module' in pretrain checkpoint

* add with_cp

* add with_cp

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

* Fix fence(IoU) = 0 when training on PascalContextDataset59;

* Add a test case in test_metrics() of tests/test_metrics.py to test the bug caused by torch.histc;

* Update tests/test_metrics.py

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

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

* refactor test organization

* fixed se layer

* update mmcv uper bound

* Fix typo: upsampe_cfg -> upsample_cfg

Signed-off-by: lizz <lizz@sensetime.com>

* convoluton -> convolution

Signed-off-by: lizz <lizz@sensetime.com>

* more

Signed-off-by: lizz <lizz@sensetime.com>

* ok

Signed-off-by: lizz <lizz@sensetime.com>

* fix training bugs

* fix unitest error

* fix error in num_classes==2 case

* delete comments

* pytorch metrics impl and test

* support list[str] input, delete unused test code and delete numpy version

* modify input data type

* add docstring and unitest of filename inputs

* add indents in docstring and use tempfile lib to create dir

* using with statement

* dice loss

* format code, add docstring and calculate denominator without valid_mask

* minor change

* restore

* [Improvement] Move train_cfg/test_cfg inside model

* fixed config dict

* fixed config dict

* add lovasz loss

* Modify as comments

* Modify paper url

* add unittest and remove Var

* impove unittest

* fix tta bug

* modify as suggested

* fix test_tta bug

* delete markdownlint

* Support MobileNetV3

* fix import

* add mobilenetv3 head and configs

* Modify MobileNetV3 to semantic segmentation version

* modify mobilenetv3 configs

* add std configs

* fix Conv2dAdaptivePadding bug

* add configs

* add unitest and fix bugs

* fix lraspp unitest bugs

* restore

* fix unitest

* add MobileNetV3 docstring

* add mmcv

* add mmcv

* fix syntax bug

* fix unitest bug

* fix unitest bug

* fix unitest bugs

* fix docstring

* add configs

* restore

* delete unnecessary assert

* modify unitest

* delete benchmark

* Support DMNet

* fix doc and delete norm_name

* Support APCNet

* code optimization

* add apcnet configs

* add benchmark

* add readme and model zoo

* fix doc

* Support resize data augmentation according to original image size (img_scale=None and retio_range is tuple)

* fix docstring

* fix bug

* add unittest

* img_scale=None in TTA

* fix bug

* add unittest

* fix typos

* fix bug

* add inference test

* fix E501 line too long (81 > 79 characters

* fix wrong config path

* fix num of augmentations (2) != num of image meta (1)

* Update test_inference.py

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

* add CLAHE transform

* fix syntax error

* fix syntax error

* restore

* add a test

* modify cv2 to mmcv

* add docstring

* modify

* restore

* fix mmcv.clahe error

* change mmcv version to 1.3.0

* fix bugs

* add all data transformers to __init__

* fix __init__

* fix test_transform

* add AdjustGamma transform

* restore

* change cv2 to mmcv

* simplify AdjustGamma

* fix syntax error

* modify

* fix syntax error

* change mmcv version to 1.3.0

* fix lut function name error

* fix syntax error

* fix range

* add dice evaluation metric

* add dice evaluation metric

* add dice evaluation metric

* support 2 metrics

* support 2 metrics

* support 2 metrics

* support 2 metrics

* fix docstring

* use np.round once for all

* [Enhancement] Add args check for ignore_index

* Support ignore_index

* add rerange transform

* restore

* delete rerange config

* delete rerange config hint

* add min < max assert

* restore

* add transformer Rgb2Gray

* restore

* fix self.weights

* restore

* fix code

* restore

* fix syntax error

* restore

* add RandomRotate for transforms

* change rotation function to mmcv.imrotate

* refactor

* add unittest

* fixed test

* fixed docstring

* fixed test

* add more test

* fixed repr

* rename to prob

* fixed unittest

Co-authored-by: hkzhang95 <GodBlessZhk@outlook.com>

* added cgnet

* added testing for cgnet

* git test

* add cgnet

* fix __init__

* rename FGlo with GlobalContextExtractor

* add readme.md and rename bn with norm

* delete cg_head

* fix a language mistake

* rename cgnet_m3n21.py to cgnet.py

* modify README.md

* modify list to tuple

* add fcn_head test

* add assert to fcn_head

* blank

* fix fcn_head assert bug

* add

* add cgnet to README.md and model_zoo.md

* modify cgnet README.md

Co-authored-by: KID <wps_@mail.nankai.edu.cn>

* Add runner_type option

* pre-commit

* Fix max_iters

* Add by_epoch to EvalHook

* Add test_eval_hook for epoch runner

* Remove runner-type arg from tools/train

* Add missing every_n_iters check for epoch mode

* Bump mmcv min version

* Use build_runner

* Use interval in tests

* Update test_eval_hook.py

* Use every_n_epochs instead of every_n_iters. Update DistEvalHook

* Add test_dist_eval_hook_epoch

* Fix tests

* Add DeprecationWarning

* Update docs

* Replace DeprecationWarning with UserWarning