* Support progressive test with fewer memory cost.

* Temp code

* Using processor to refactor evaluation workflow.

* refactor eval hook.

* Fix process bar.

* Fix middle save argument.

* Modify some variable name of dataset evaluate api.

* Modify some viriable name of eval hook.

* Fix some priority bugs of eval hook.

* Depreciated efficient_test.

* Fix training progress blocked by eval hook.

* Depreciated old test api.

* Fix test api error.

* Modify outer api.

* Build a sampler test api.

* TODO: Refactor format_results.

* Modify variable names.

* Fix num_classes bug.

* Fix sampler index bug.

* Fix grammaly bug.

* Support batch sampler.

* More readable test api.

* Remove some command arg and fix eval hook bug.

* Support format-only arg.

* Modify format_results of datasets.

* Modify tool which use test apis.

* support cityscapes eval

* fixed cityscapes

* 1. Add comments for batch_sampler;

2. Keep eval hook api same and add deprecated warning;

3. Add doc string for dataset.pre_eval;

* Add efficient_test doc string.

* Modify test tool to compat old version.

* Modify eval hook to compat with old version.

* Modify test api to compat old version api.

* Sampler explanation.

* update warning

* Modify deploy_test.py

* compatible with old output, add efficient test back

* clear logic of exclusive

* Warning about efficient_test.

* Modify format_results save folder.

* Fix bugs of format_results.

* Modify deploy_test.py.

* Update doc

* Fix deploy test bugs.

* Fix custom dataset unit tests.

* Fix dataset unit tests.

* Fix eval hook unit tests.

* Fix some imcompatible.

* Add pre_eval argument for eval hooks.

* Update eval hook doc string.

* Make pre_eval false in default.

* Add unit tests for dataset format_results.

* Fix some comments and bc-breaking bug.

* Fix pre_eval set cfg field.

* Remove redundant codes.

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

* init scripts

* update markdown

* update markdown

* add docs

* delete mit converter and use torch load function

* rename segformer readme

* update doc

* modify doc

* 更新中文文档

* Update useful_tools.md

* Update useful_tools.md

* modify doc

* update segformer.yml

* Add header for files

* Delete header in config files

* [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

* [Feature] Add segformer decode head and related train config

* Add ade20K trainval support for segformer

1. Add related train and val configs;

2. Add AlignedResize;

* Set arg: find_unused_parameters = True

* parameters init refactor

* 1. Refactor segformer backbone parameters init;

2. Remove rebundant functions and unit tests;

* Remove rebundant codes

* Replace Linear Layer to 1X1 Conv

* Use nn.ModuleList to refactor segformer head.

* Remove local to_xtuple

* 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.

* Modify configs of segformer.

* resolve the shape convertion functions doc string.

* Add pad_to_patch_size arg.

* Support progressive test with fewer memory cost.

* Modify default value of pad_to_patch_size arg.

* Temp code

* Using processor to refactor evaluation workflow.

* refactor eval hook.

* Fix process bar.

* Fix middle save argument.

* Modify some variable name of dataset evaluate api.

* Modify some viriable name of eval hook.

* Fix some priority bugs of eval hook.

* Fix some bugs about model loading and eval hook.

* Add ade20k 640x640 dataset.

* Fix related segformer configs.

* Depreciated efficient_test.

* Fix training progress blocked by eval hook.

* Depreciated old test api.

* Modify error patch size.

* Fix pretrain of mit_b0

* Fix the test api error.

* Modify dataset base config.

* Fix test api error.

* Modify outer api.

* Build a sampler test api.

* TODO: Refactor format_results.

* Modify variable names.

* Fix num_classes bug.

* Fix sampler index bug.

* Fix grammaly bug.

* Add part of benchmark results.

* Support batch sampler.

* More readable test api.

* Remove some command arg and fix eval hook bug.

* Support format-only arg.

* Modify format_results of datasets.

* Modify tool which use test apis.

* Update readme.

* Update readme of segformer.

* Updata readme of segformer.

* Update segformer readme and fix segformer mit_b4.

* Update readme of segformer.

* Clean AlignedResize related config.

* Clean code from pr #709

* Clean code from pr #709

* Add 512x512 segformer_mit-b5.

* Fix lint.

* Fix some segformer head bugs.

* Add segformer unit tests.

* Replace AlignedResize to ResizeToMultiple.

* Modify readme of segformer.

* Fix bug of ResizeToMultiple.

* Add ResizeToMultiple unit tests.

* Resolve conflict.

* Simplify the implementation of ResizeToMultiple.

* Update test results.

* Fix multi-scale test error when resize_ratio=1.75 and input size=640x640.

* Update segformer results.

* Update Segformer results.

* Fix some url bugs and pipelines bug.

* Move ckpt convertion to tools.

* Add segformer official pretrain weights usage.

* Clean redundant codes.

* Remove redundant codes.

* Unfied format.

* Add description for segformer converter.

* Update workers.

* Replace interpolate with resize

* Replace nn.Upsample with ops.Upsample

* Fix test

* Add docker/serve

* Add handler

* Add mmseg2torchserve

* Fix mmv minimum version

* Update docs with model serving section

* Update useful_tools.md

* pre-commit

* Update useful_tools.md

* Add 3dogs to resources

* Move mask to resources

* [Refactor]: Unified parameter initialization

* fixed pretrained

* Add  save_best option in eval_hook.

* Update meta to fix best model can not test bug

* refactor with _do_evaluate

* remove redundent

* add meta

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

* add trt test tool

* create deploy_test, update document

* fix with isort

* move import inside __init__

* remove comment, fix doc

* update document

* fix verify bugs

* rename args

* add onnxruntime test tool, update pytorch2onnx to support slice export

* onnx convert with custom output shape, update test code

* update pytorch2onnx, add rescale_shape support, add document

* update doc for lint error fixing

* remove cpu flag in ort_test.py

* change class name, fix cuda error

* remote comment

* fix bug of torch2onnx

* mIOU to mIoU

* fixed fp16

* update fps

* add tool pytorch2torchscript

* fix the assert message for pytorch version.

* add dynamic export and visualize to pytorch2onnx

* update document

* fix lint

* fix dynamic error and add visualization

* fix lint

* update docstring

* update doc

* Update help info for --show

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

* fix lint

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

* add print model graph for print_config tool

* add print model graph for print_config tool

* fix double quoted

* fix iosort

* Support plot logs

* add plot log docs

* [Improvement] Move train_cfg/test_cfg inside model

* fixed config dict

* fixed config dict

* memory efficient test

* implement efficient test

* merge

* Add document and docstring

* fix unit test

* add memory usage report

* refactor docs

* add docs

* add modelzoo

* refactor getting started

* fix dataset jpg bug

* fix syntax error

* fix filename bug

* define blood vessel dataset

* redo debug

* fix small bug

* rename dataset

Co-authored-by: yamengxi <yamengxi@sensetime.com>

* Add blood vessel dataset processing script

* Fix syntax error

* Fix syntax error

* Fix syntax error

* Fix bugs

* Fix bugs

* Fix bugs

* Use safe functions and expand more apis

* Use safe functions and expand more apis

* Fix hard code and verify dataset integrity

* rm redundancies

* re-add some packages

* Add Pascal Context to mmsegmentation

* Add benchmark result to Pascal Context

* fix mmcv version

* fix code syntax

* fix code syntax again

* Update mmseg/models/segmentors/encoder_decoder.py

update hint

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

* update comment

* fix pascal context model path

* fix model path mistake again

* fix model path mistake again

* fix model path mistakes again

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

* add customized Upsample which can convert to ONNX

* support multiply decode head for hrnet

* support size for Upsample

* add pytorch2onnx part

* Update according to the latest mmcv

* add docstring

* update docs

* update docs

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

* Auto get version info and git hash

* bump 0.5.1 and update doc

* fixed docs

* Add change log

* Add load-from flag

* minor update

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

* Fixed voc aug convert

* update getting_started.md

* add class balanced doc

* add test tutorial

* remote torch/torchvision from requirements

* update getting started

* rename drop_out_ratio -> dropout_ratio