as title

## Motivation

Make MMSeginferencer easier to be used

## Modification

1. Add `_load_weights_to_model` to MMSeginferencer, it is for get
`dataset_meta` from ckpt
2. Modify and remove some parameters of `__call__`, `visualization` and
`postprocess`
3. Add function of save seg mask, remove dump pkl.
4. Refine docstring of MMSeginferencer and SegLocalVisualizer
5. Add the user documentation of MMSeginferencer

## BC-breaking (Optional)

yes, remove some parameters, we need to discuss whether keep them with
deprecated waring or just remove them as the MMSeginferencer just merged
in mmseg a few days.

Co-authored-by: xiexinch <xiexinch@outlook.com>

[Fix] Add out_channels  in `CascadeEncoderDecoder` and update OCRNet and MobileNet v2 results (#2656)

## Motivation

As title.

## Modification

1. update results in readme
2. fix attr error in cascade encoder decoder

## Motivation

Support `MMSegInferencer` for providing an easy and clean interface for
single or multiple images inferencing.

Ref: https://github.com/open-mmlab/mmengine/pull/773
https://github.com/open-mmlab/mmocr/pull/1608

## Modification

- mmseg/apis/mmseg_inferencer.py
- mmseg/visualization/local_visualizer.py
- demo/image_demo_with_inferencer.py

## Use cases (Optional)

Based on https://github.com/open-mmlab/mmengine/tree/inference



Add a new image inference demo with `MMSegInferencer`

- demo/image_demo_with_inferencer.py

```shell
python demo/image_demo_with_inferencer.py demo/demo.png fcn_r50-d8_4xb2-40k_cityscapes-512x1024
```

---------

Co-authored-by: MeowZheng <meowzheng@outlook.com>

## Motivation

The registry now supports auto-import modules from the given location.

register_all_modules before running is no longer needed. The modules
will be lazy-imported during building.

- [x] This PR can be merged after
https://github.com/open-mmlab/mmengine/pull/643. The MMEngine version
should be updated.

Ref: https://github.com/open-mmlab/mmdetection/pull/9143

## Motivation

In MMEngine >= 0.2.0, it might directly determine what the backend is by
using the `data_root` path.

## Modification

Set all default `backend_args` values are `None`.

## Motivation

Original motivation was after [MMDetection PR
#9533](https://github.com/open-mmlab/mmdetection/pull/9533)

With several experiments I found out that if a ndarray is contiguous,
numpy.transpose + torch.contiguous perform better, while if not, then
use numpy.ascontiguousarray + numpy.transpose

## Modification

Replace numpy.ascontiguousarray with torch.contiguous in
[PackSegInputs](https://github.com/open-mmlab/mmsegmentation/blob/1.x/mmseg/datasets/transforms/formatting.py

)

Co-authored-by: MeowZheng <meowzheng@outlook.com>

## Motivation 
Add REFUGE datasets
Old PR: https://github.com/open-mmlab/mmsegmentation/pull/2420



---------

Co-authored-by: MengzhangLI <mcmong@pku.edu.cn>

as title

## Motivation

Fix the bug in running ```collect_evn.py```. #2547 

## Modification

Rename typing.py to typing_utils.py

## Motivation

Use the new fileio from mmengine
https://github.com/open-mmlab/mmengine/pull/533

## Modification

1. Use `mmengine.fileio` to repalce FileClient  in mmseg/datasets
2. Use `mmengine.fileio` to repalce FileClient in
mmseg/datasets/transforms
3. Use `mmengine.fileio` to repalce FileClient in mmseg/visualization

## BC-breaking (Optional)

we modify all the dataset configurations, so please use the latest config file.

## Motivation

This is essentially #2535 that I had intended to submit to the `dev-1.x`
branch but accidentally submitted it directly to the `1.x` branch
(apologies!). This also got approved possibly because the core devs also
didn't realize this.

The problem is that now `1.x` and `dev-1.x` are out of sync -- the
changes introduced by #2535 will never be reflected in `dev-1.x`.

## Modification

I'm proposing this "backward-merge" so that `1.x` and `dev-1.x` can be
in sync again. If you look at "files changed", they are exactly the
changes introduced by #2535.

Co-authored-by: MeowZheng <meowzheng@outlook.com>

## Motivation

This is motivated by a previously unfinished PR (#2332). In that PR, the
label -1 was changed to 255 in `BaseSegDataset`, which is correct.
However, it was changed at only one location. There is another location
in `mmseg/datasets/basesegdataset.py` where -1 was still being used that
was not converted to 255. I have now converted it to 255.

This is exactly same as a similar fix to the `master` branch via #2515 .

## Modification

I've simply converted the snipped

```python
if new_id != -1:
    new_palette.append(palette[old_id])
```
to 
```python
if new_id != 255:
    new_palette.append(palette[old_id])
```

## Checklist

- [x] Pre-commit or other linting tools are used to fix the potential
lint issues.
  - _I've fixed all linting/pre-commit errors._
- [x] The modification is covered by complete unit tests. If not, please
add more unit test to ensure the correctness.
  - _No unit tests need to be added or were affected.
- [x] If the modification has potential influence on downstream
projects, this PR should be tested with downstream projects, like MMDet
or MMDet3D.
  - _I don't think this change affects MMDet or MMDet3D._
- [x] The documentation has been modified accordingly, like docstring or
example tutorials.
- _This change fixes an existing bug and doesn't require modifying any
documentation/docstring._

This is an almost exact duplicate of #2500 (that was made to the
`master` branch) now applied to the `1.x` branch.

---

## Motivation

I want to fix a bug through this PR. The bug occurs when two options --
`reduce_zero_label=True`, and custom classes are used.
`reduce_zero_label` remaps the GT seg labels by remapping the zero-class
to 255 which is ignored. Conceptually, this should occur *before* the
`label_map` is applied, which maps *already reduced labels*. However,
currently, the `label_map` is applied before the zero label is reduced.

## Modification

The modification is simple:
- I've just interchanged the order of the two operations by moving a few
lines from bottom to top.
- I've added a test that passes when the fix is introduced, and fails on
the original `master` branch.

## BC-breaking (Optional)

I do not anticipate this change braking any backward-compatibility.

## Checklist

- [x] Pre-commit or other linting tools are used to fix the potential
lint issues.
  - _I've fixed all linting/pre-commit errors._
- [x] The modification is covered by complete unit tests. If not, please
add more unit test to ensure the correctness.
  - _I've added a unit test._ 
- [x] If the modification has potential influence on downstream
projects, this PR should be tested with downstream projects, like MMDet
or MMDet3D.
  - _I don't think this change affects MMDet or MMDet3D._
- [x] The documentation has been modified accordingly, like docstring or
example tutorials.
- _This change fixes an existing bug and doesn't require modifying any
documentation/docstring._

as title

Co-authored-by: MengzhangLI <mcmong@pku.edu.cn>

## Motivation

Support for biomedical 3d images augmentation.

## Modification

Add BioMedical3DRandomFlip in mmseg/datasets/transforms/transforms.py.

Co-authored-by: MeowZheng <meowzheng@outlook.com>

## Motivation

Makes docstring to be consistent with actual argument name.

## Modification

Minor fix

## BC-breaking (Optional)

No

## Motivation

The motivation of this PR is to add `gt_edge_map` field to support
boundary loss.

## Modification

- GenerateEdge
Modify `gt_edge` field to `gt_edge_map`.

- PackSegInputs
Add `gt_edge_map` to data_sample.

- stack_batch
Pad `gt_edge_map` to max_shape.

## BC-breaking (Optional)

No

## Use cases (Optional)

Reference `GenerateEdge`.

## Motivation

Fix incorrect `img_shape` value assignment.

## Modification

- mmseg/datasets/transforms/transforms.py

## Motivation

Add Synapse dataset in MMSegmentation.
Old PR: https://github.com/open-mmlab/mmsegmentation/pull/2372.

## Motivation
Add the 3d pad transform for biomedical images, which follows the design
of the nnUNet.

Add the random gamma correction transform for biomedical images, which
follows the design of the nnUNet.

## Motivation

implement nnUNet-style Gaussian Noise and Blur

## Motivation

To release 1.0.0rc3  

## Modification

1. Modify mmseg version 
2. Add change log
3. Modify README
4. Modify faq 
5. Revise docker file

## Motivation

Calling `mmseg.utils.register_all_modules` will import `MaskFormerHead`
and `Mask2FormerHead`, it will crash if mmdet is not installed as `None`
cannot be initialized.

## Modification

- Modify `MMDET_MaskFormerHead=BaseModule` and `MMDET_Mask2FormerHead =
BaseModule` when cannot import from mmdet

* tta init

* use mmcv transform

* test city

* add multiscale

* fix merge

* add softmax to post process

* add ut

* add tta pipeline to other datasets

* remove softmax

* add encoder_decoder_tta ut

* add encoder_decoder_tta ut

* rename

* rename file

* rename config

* rm aug_test

* move flip to post process

* fix channel

* [Feature] Add Biomedical 3D array random crop transform

* fix lint

* fix gen crop bbox

* fix gen crop bbox

* docstring

* typo

Co-authored-by: MeowZheng <meowzheng@outlook.com>

* Bump 1.0.0rc2

* typo

* init commits

* fix crop size

* add seg_data2instance_data method

* add ut and update requirement

* update configs and readme

* add model-indel

* update optional requirements

* fix results

* fix lint error

* update results

* update results

* remove mmdet from requirements/optional.txt

* use try import and update README

* add docstring to overwrtied method

* minor change

Co-authored-by: MengzhangLI <mcmong@pku.edu.cn>

* [Feature] Support MaskFormer(NeurIPS'2021) in MMSeg 1.x

* add mmdet try except logic

* refactor config files

* add readme

* fix config

* update models & logs

* add MMDET installation and fix info

* fix comments

* fix

* fix config norm optimizer setting

* update models & logs & unittest

* add docstring of MaskFormerHead

* wait for mmdet 3.0.0rc4

* replace seg_mask with seg_logits & add docstring for batch_input_shape

* use mmdet3.0.0rc4

* fix readme and modify config comments

* add mmdet installation in pr_stage_test.yml

* update mmcv version in pr_stage_test.yml

* add mmdet in build_cpu of pr_stage_test.yml

* modify mmdet& mmcv installation in merge_stage_test.yml

* fix typo

* update test.yml

* update test.yml

* add img_padding_size

* minor change

* add pad_shape to data_samples