pydensecrf | Python wrapper to Philipp Krähenbühl | Machine Learning library

by lucasb-eyer C++ Version: 1.0rc3 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pydensecrf Summary

pydensecrf is a C++ library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, OpenCV, Numpy applications. pydensecrf has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.

Support

Quality

Security

License

Reuse

Support

pydensecrf has a medium active ecosystem.

It has 1827 star(s) with 406 fork(s). There are 40 watchers for this library.

It had no major release in the last 12 months.

There are 40 open issues and 63 have been closed. On average issues are closed in 59 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pydensecrf is 1.0rc3

Quality

pydensecrf has 0 bugs and 0 code smells.

Security

pydensecrf has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pydensecrf code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pydensecrf is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

pydensecrf releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

It has 323 lines of code, 20 functions and 9 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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pydensecrf Key Features

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pydensecrf Examples and Code Snippets

No Code Snippets are available at this moment for pydensecrf.

Community Discussions

Trending Discussions on pydensecrf

Using custom dependencies in Google Cloud ML Engine

QUESTION

Using custom dependencies in Google Cloud ML Engine

Asked 2017-Jul-21 at 14:52

I am trying to use a python package that is not listed in PyPI with the Google Cloud ML Engine. This package has itself dependencies that even though are listed in PyPI are not installed by default in the ML engine environment, namely the Cython package.

Looking at the documentation it is not really clear how to proceed in this case, I have tried packaging this package in a .tar.gz file and passing it under the --packages argument, but I got the following error:

...

ANSWER

Answered 2017-Jul-21 at 14:43

To do this, you will need to add the Cython to the list of required packages in your setup.py. Instructions can be found here.

Here is a sample setup.py, that would reside in the parent directory of the directory you pass as --package-path to gcloud.

Source https://stackoverflow.com/questions/45234155

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install pydensecrf

The package is on PyPI, so simply run pip install pydensecrf to install it.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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