hkchengrex/CascadePSP
A PyTorch deep learning model that refines coarse segmentation masks to produce high-resolution, class-agnostic image segmentation.
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CascadePSP is a segmentation refinement network that takes an image and a coarse segmentation mask as input and produces a refined, high-resolution segmentation output. The model uses a cascade architecture with global and local refinement steps to handle very high-resolution images. It includes training and testing code in PyTorch, and is distributed as a pip-installable package for easy use.
Frequently asked
- What is hkchengrex/CascadePSP?
- A PyTorch deep learning model that refines coarse segmentation masks to produce high-resolution, class-agnostic image segmentation.
- Is CascadePSP open source?
- Yes — hkchengrex/CascadePSP is open source, released under the MIT license.
- What language is CascadePSP written in?
- hkchengrex/CascadePSP is primarily written in Python.
- How popular is CascadePSP?
- hkchengrex/CascadePSP has 884 stars on GitHub.
- Where can I find CascadePSP?
- hkchengrex/CascadePSP is on GitHub at https://github.com/hkchengrex/CascadePSP.