Highlights
We are excited to announce the release of MMSegmentation v1.0.0 as a part of the OpenMMLab 2.0 project! MMSegmentation v1.0.0 introduces an updated framework structure for the core package and a new section called "Projects". This section showcases a range of engaging and versatile applications built upon the MMSegmentation foundation.
In this latest release, we have significantly refactored the core package's code to make it clearer, more comprehensible, and disentangled. This has resulted in improved performance for several existing algorithms, ensuring that they now outperform their previous versions. Additionally, we have incorporated some cutting-edge algorithms, such as PIDNet and SegNeXt, to further enhance the capabilities of MMSegmentation and provide users with a more comprehensive and powerful toolkit.
The new "Projects" section serves as an essential addition to MMSegmentation, created to foster innovation and collaboration among users.
Exciting Features
Inferencer
In this release, we introduce the MMSegInferencer, a versatile API for inference that accommodates multiple input types. The API enables users to easily specify and customize semantic segmentation models, streamlining the process of performing semantic segmentation with MMSegmentation.
Usage:
shell
python demo/image_demo_with_inferencer.py ${IMAGE} ${MODEL} --show --device ${DEVICE}
Optimizations
In addition to new features, MMSegmentation v1.0.0 delivers key optimizations for an enhanced user experience.
PyTorch 2.0 Compatibility