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CSH authoredas title --------- Co-authored-by:
MeowZheng <meowzheng@outlook.com>CSH authoredas title --------- Co-authored-by:MeowZheng <meowzheng@outlook.com>
Package structures changes
This section is included if you are curious about what has changed between MMSeg 0.x and 1.x.
| MMSegmentation 0.x | MMSegmentation 1.x |
| mmseg.api | mmseg.api |
| - mmseg.core | + mmseg.engine |
| mmseg.datasets | mmseg.datasets |
| mmseg.models | mmseg.models |
| - mmseg.ops | + mmseg.structure |
| mmseg.utils | mmseg.utils |
| + mmseg.evaluation | |
| + mmseg.registry | |
Removed packages
mmseg.core
In OpenMMLab 2.0, core package has been removed. hooks and optimizers of core are moved in mmseg.engine, and evaluation in core is mmseg.evaluation currently.
mmseg.ops
ops package included encoding and wrappers, which are moved in mmseg.models.utils.
Added packages
mmseg.engine
OpenMMLab 2.0 adds a new foundational library for training deep learning, MMEngine. It servers as the training engine of all OpenMMLab codebases.
engine package of mmseg is some customized modules for semantic segmentation task, like SegVisualizationHook which works for visualizing segmentation mask.
mmseg.structure
In OpenMMLab 2.0, we designed data structure for computer vision task, and in mmseg, we implements SegDataSample in structure package.
mmseg.evaluation
We move all evaluation metric in mmseg.evaluation.
mmseg.registry
We moved registry implementations for all kinds of modules in MMSegmentation in mmseg.registry.
Modified packages
mmseg.apis
OpenMMLab 2.0 tries to support unified interface for multitasking of Computer Vision, and releases much stronger Runner, so MMSeg 1.x removed modules in train.py and test.py renamed init_segmentor to init_model and inference_segmentor to inference_model.
Here is the changes of mmseg.apis:
| Function | Changes |
|---|---|
init_segmentor |
Renamed to init_model
|
inference_segmentor |
Rename to inference_model
|
show_result_pyplot |
Implemented based on SegLocalVisualizer
|
train_model |
Removed, use runner.train to train. |
multi_gpu_test |
Removed, use runner.test to test. |
single_gpu_test |
Removed, use runner.test to test. |
set_random_seed |
Removed, use mmengine.runner.set_random_seed. |
init_random_seed |
Removed, use mmengine.dist.sync_random_seed. |
mmseg.datasets
OpenMMLab 2.0 defines the BaseDataset to function and interface of dataset, and MMSegmentation 1.x also follow this protocol and defines the BaseSegDataset inherited from BaseDataset. MMCV 2.x collects general data transforms for multiple tasks e.g. classification, detection, segmentation, so MMSegmentation 1.x uses these data transforms and removes them from mmseg.datasets.
| Packages/Modules | Changes |
|---|---|
mmseg.pipelines |
Moved in mmcv.transforms
|
mmseg.sampler |
Moved in mmengine.dataset.sampler
|
CustomDataset |
Renamed to BaseSegDataset and inherited from BaseDataset in MMEngine |
DefaultFormatBundle |
Replaced with PackSegInputs
|
LoadImageFromFile |
Moved in mmcv.transforms.LoadImageFromFile
|
LoadAnnotations |
Moved in mmcv.transforms.LoadAnnotations
|
Resize |
Moved in mmcv.transforms and split into Resize, RandomResize and RandomChoiceResize
|
RandomFlip |
Moved in mmcv.transforms.RandomFlip
|
Pad |
Moved in mmcv.transforms.Pad
|
Normalize |
Moved in mmcv.transforms.Normalize
|
Compose |
Moved in mmcv.transforms.Compose
|
ImageToTensor |
Moved in mmcv.transforms.ImageToTensor
|
mmseg.models
models has not changed a lot, just added the encoding and wrappers from previous mmseg.ops