fast-neural-style-ncs | trained model checkpoint and export to a graph

by eridgd Python Version: Current License: No License

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

kandi X-RAY | fast-neural-style-ncs Summary

fast-neural-style-ncs is a Python library typically used in Institutions, Learning, Education applications. fast-neural-style-ncs has no bugs, it has no vulnerabilities and it has low support. However fast-neural-style-ncs build file is not available. You can download it from GitHub.

To download a trained model checkpoint and export to a graph compatible with mvNCCompile:.

Support

Quality

Security

License

Reuse

Support

fast-neural-style-ncs has a low active ecosystem.

It has 13 star(s) with 2 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 524 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fast-neural-style-ncs is current.

Quality

fast-neural-style-ncs has no bugs reported.

Security

fast-neural-style-ncs has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

fast-neural-style-ncs does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

fast-neural-style-ncs releases are not available. You will need to build from source code and install.

fast-neural-style-ncs has no build file. You will be need to create the build yourself to build the component from source.

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

Top functions reviewed by kandi - BETA

kandi has reviewed fast-neural-style-ncs and discovered the below as its top functions. This is intended to give you an instant insight into fast-neural-style-ncs implemented functionality, and help decide if they suit your requirements.

Optimize a training set
VGG16
Residual layer
Layer convolution layer
Get an image
Transpose convolution layer
Wrapper function for ffwd
Create a TFwd layer
Create an image from a stream
Build the argument parser
Wrapper function for fwd
Check options
Predict the prediction
Preserve the colors of the content_rgb
Read the next frame from the stream
List all files in_path

Get all kandi verified functions for this library.

fast-neural-style-ncs Key Features

No Key Features are available at this moment for fast-neural-style-ncs.

fast-neural-style-ncs Examples and Code Snippets

No Code Snippets are available at this moment for fast-neural-style-ncs.

Community Discussions

No Community Discussions are available at this moment for fast-neural-style-ncs.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install fast-neural-style-ncs

You can download it from GitHub.
You can use fast-neural-style-ncs 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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