Thanks for your contribution and we appreciate it a lot. The following
instructions would make your pull request more healthy and more easily
get feedback. If you do not understand some items, don't worry, just
make the pull request and seek help from maintainers.
## Motivation
Add Huasdorff distance loss
---------
Co-authored-by: xiexinch <xiexinch@outlook.com>
## Motivation
Fix bug cannot use both '--tta' and '--out' while testing.
For details, please refer to #3064 .
## Modification
Add 'img_path' in TTA predictions.
---------
Co-authored-by: xiexinch <xiexinch@outlook.com>
## Motivation
For support with reading multiple remote sensing image formats, please
refer to https://gdal.org/drivers/raster/index.html.
Byte, UInt16, Int16, UInt32, Int32, Float32, Float64, CInt16, CInt32,
CFloat32 and CFloat64 are supported for reading and writing.
Support input of two images for change detection tasks, and support the
LEVIR-CD dataset.
## Modification
Add LoadSingleRSImageFromFile in 'mmseg/datasets/transforms/loading.py'.
Load a single remote sensing image for object segmentation tasks.
Add LoadMultipleRSImageFromFile in
'mmseg/datasets/transforms/loading.py'.
Load two remote sensing images for change detection tasks.
Add ConcatCDInput in 'mmseg/datasets/transforms/transforms.py'.
Combine images that have been separately augmented for data enhancement.
Add BaseCDDataset in 'mmseg/datasets/basesegdataset.py'
Base class for datasets used in change detection tasks.
---------
Co-authored-by: xiexinch <xiexinch@outlook.com>
## Motivation
1. It is used to save the segmentation predictions as files and upload
these files to a test server
## Modification
1. Add output_file and format only in `IoUMetric`
## BC-breaking (Optional)
No
## Use cases (Optional)
If this PR introduces a new feature, it is better to list some use cases
here, and update the documentation.
## Checklist
1. Pre-commit or other linting tools are used to fix the potential lint
issues.
3. The modification is covered by complete unit tests. If not, please
add more unit test to ensure the correctness.
4. If the modification has potential influence on downstream projects,
this PR should be tested with downstream projects, like MMDet or
MMDet3D.
5. The documentation has been modified accordingly, like docstring or
example tutorials.
## Modification
I changed the hardcoded 3 channel length to dynamic channel length in
`np.full` function arguments.
This modification enables `RandomMosaic` transform to support
multispectral image (e.g. RGB image with NIR band) or bi-temporal image
pairs for change detection task.
## Checklist
1. Pre-commit or other linting tools are used to fix the potential lint
issues.
2. The modification is covered by complete unit tests. If not, please
add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects,
this PR should be tested with downstream projects, like MMDet or
MMDet3D.
4. The documentation has been modified accordingly, like docstring or
example tutorials.
Thanks for your contribution and we appreciate it a lot. The following
instructions would make your pull request more healthy and more easily
get feedback. If you do not understand some items, don't worry, just
make the pull request and seek help from maintainers.
## Motivation
fix#2593
## Modification
1. Only when gt seg map is 2D, extend its shape to 3D PixelData
2. If seg map is not 2D, we raised warning for users.
---------
Co-authored-by: xiexinch <xiexinch@outlook.com>
## 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>
## Motivation
Support `MMSegInferencer` for providing an easy and clean interface for
single or multiple images inferencing.
Ref: https://github.com/open-mmlab/mmengine/pull/773https://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
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
The DETR-related modules have been refactored in
open-mmlab/mmdetection#8763, which causes breakings of MaskFormer and
Mask2Former in both MMDetection (has been fixed in
open-mmlab/mmdetection#9515) and MMSegmentation. This pr fix the bugs in
MMSegmentation.
### TO-DO List
- [x] update configs
- [x] check and modify data flow
- [x] fix unit test
- [x] aligning inference
- [x] write a ckpt converter
- [x] write ckpt update script
- [x] update model zoo
- [x] update model link in readme
- [x] update
[faq.md](https://github.com/open-mmlab/mmsegmentation/blob/dev-1.x/docs/en/notes/faq.md#installation)
## Tips of Fixing other implementations based on MaskXFormer of mmseg
1. The Transformer modules should be built directly. The original
building with register manner has been refactored.
2. The config requires to be modified. Delete `type` and modify several
keys, according to the modifications in this pr.
3. The `batch_first` is set `True` uniformly in the new implementations.
Hence the data flow requires to be transposed and config of
`batch_first` needs to be modified.
4. The checkpoint trained on the old implementation should be converted
to be used in the new one.
### Convert script
```Python
import argparse
from copy import deepcopy
from collections import OrderedDict
import torch
from mmengine.config import Config
from mmseg.models import build_segmentor
from mmseg.utils import register_all_modules
register_all_modules(init_default_scope=True)
def parse_args():
parser = argparse.ArgumentParser(
description='MMSeg convert MaskXFormer model, by Li-Qingyun')
parser.add_argument('Mask_what_former', type=int,
help='Mask what former, can be a `1` or `2`',
choices=[1, 2])
parser.add_argument('CFG_FILE', help='config file path')
parser.add_argument('OLD_CKPT_FILEPATH', help='old ckpt file path')
parser.add_argument('NEW_CKPT_FILEPATH', help='new ckpt file path')
args = parser.parse_args()
return args
args = parse_args()
def get_new_name(old_name: str):
new_name = old_name
if 'encoder.layers' in new_name:
new_name = new_name.replace('attentions.0', 'self_attn')
new_name = new_name.replace('ffns.0', 'ffn')
if 'decoder.layers' in new_name:
if args.Mask_what_former == 2:
# for Mask2Former
new_name = new_name.replace('attentions.0', 'cross_attn')
new_name = new_name.replace('attentions.1', 'self_attn')
else:
# for Mask2Former
new_name = new_name.replace('attentions.0', 'self_attn')
new_name = new_name.replace('attentions.1', 'cross_attn')
return new_name
def cvt_sd(old_sd: OrderedDict):
new_sd = OrderedDict()
for name, param in old_sd.items():
new_name = get_new_name(name)
assert new_name not in new_sd
new_sd[new_name] = param
assert len(new_sd) == len(old_sd)
return new_sd
if __name__ == '__main__':
cfg = Config.fromfile(args.CFG_FILE)
model_cfg = cfg.model
segmentor = build_segmentor(model_cfg)
refer_sd = segmentor.state_dict()
old_ckpt = torch.load(args.OLD_CKPT_FILEPATH)
old_sd = old_ckpt['state_dict']
new_sd = cvt_sd(old_sd)
print(segmentor.load_state_dict(new_sd))
new_ckpt = deepcopy(old_ckpt)
new_ckpt['state_dict'] = new_sd
torch.save(new_ckpt, args.NEW_CKPT_FILEPATH)
print(f'{args.NEW_CKPT_FILEPATH} has been saved!')
```
Usage:
```bash
# for example
python ckpt4pr2532.py 1 configs/maskformer/maskformer_r50-d32_8xb2-160k_ade20k-512x512.py original_ckpts/maskformer_r50-d32_8xb2-160k_ade20k-512x512_20221030_182724-cbd39cc1.pth cvt_outputs/maskformer_r50-d32_8xb2-160k_ade20k-512x512_20221030_182724.pth
python ckpt4pr2532.py 2 configs/mask2former/mask2former_r50_8xb2-160k_ade20k-512x512.py original_ckpts/mask2former_r50_8xb2-160k_ade20k-512x512_20221204_000055-4c62652d.pth cvt_outputs/mask2former_r50_8xb2-160k_ade20k-512x512_20221204_000055.pth
```
---------
Co-authored-by: MeowZheng <meowzheng@outlook.com>
## 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.
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._
## Motivation
Support for biomedical 3d images augmentation.
## Modification
Add BioMedical3DRandomFlip in mmseg/datasets/transforms/transforms.py.
Co-authored-by: MeowZheng <meowzheng@outlook.com>
## 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`.
* 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 Decathlon dataset
* fix test data
* add file
* remove order
* revise default value for prefix
* modify example
* revise based on comments
* add comments for ut
CastleDream
jinxianwei
谢昕辰
nightrain01
CSH
WuFan
zoulinxin
Miao Zheng
MengzhangLI
Junhwa Song
Tianlong Ai
Andrew Lau
Qingyun
Siddharth Ancha
Leeinsn
Wencheng Wu
王永韬
legendchilli
Fivethousand
Haoyu Wang
Jin Ye