pytorch_unet

by acai66 Python Version: Current License: GPL-3.0

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

kandi X-RAY | pytorch_unet Summary

pytorch_unet is a Python library. pytorch_unet has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Customized implementation of the U-Net in PyTorch for Kaggle's Carvana Image Masking Challenge from high definition images.

Support

Quality

Security

License

Reuse

Support

pytorch_unet has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

pytorch_unet has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pytorch_unet is current.

Quality

pytorch_unet has no bugs reported.

Security

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

License

pytorch_unet is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

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

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

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pytorch_unet Key Features

No Key Features are available at this moment for pytorch_unet.

pytorch_unet Examples and Code Snippets

No Code Snippets are available at this moment for pytorch_unet.

Community Discussions

No Community Discussions are available at this moment for pytorch_unet.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install pytorch_unet

You can download it from GitHub.
You can use pytorch_unet like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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