lucasb-eyer/pydensecrf
Python/Cython wrapper for Fully Connected CRFs with Gaussian edge potentials used in computer vision tasks like image segmentation.
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PyDenseCRF provides a Python interface to Philipp Krähenbühl and Vladlen Koltun’s efficient dense (fully connected) CRF implementation. CRFs are a structured prediction model used in computer vision for tasks like semantic segmentation and pixel-wise labeling. The library exposes both unary and pairwise (Gaussian edge) potentials and uses Cython/Eigen for performance.
Frequently asked
- What is lucasb-eyer/pydensecrf?
- Python/Cython wrapper for Fully Connected CRFs with Gaussian edge potentials used in computer vision tasks like image segmentation.
- Is pydensecrf open source?
- Yes — lucasb-eyer/pydensecrf is open source, released under the MIT license.
- What language is pydensecrf written in?
- lucasb-eyer/pydensecrf is primarily written in C++.
- How popular is pydensecrf?
- lucasb-eyer/pydensecrf has 2k stars on GitHub.
- Where can I find pydensecrf?
- lucasb-eyer/pydensecrf is on GitHub at https://github.com/lucasb-eyer/pydensecrf.