react-native-tensorflow | A TensorFlow inference library | iOS library

by reneweb Java Version: 0.1.8 License: Apache-2.0

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

kandi X-RAY | react-native-tensorflow Summary

react-native-tensorflow is a Java library typically used in Mobile, iOS, Tensorflow, React Native applications. react-native-tensorflow has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However react-native-tensorflow build file is not available. You can install using 'npm i react-native-tensorflow' or download it from GitHub, npm.

A TensorFlow inference library for react native

Support

Quality

Security

License

Reuse

Support

react-native-tensorflow has a low active ecosystem.

It has 357 star(s) with 57 fork(s). There are 15 watchers for this library.

It had no major release in the last 12 months.

There are 19 open issues and 20 have been closed. On average issues are closed in 24 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of react-native-tensorflow is 0.1.8

Quality

react-native-tensorflow has no bugs reported.

Security

react-native-tensorflow has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

react-native-tensorflow is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

react-native-tensorflow releases are not available. You will need to build from source code and install.

Deployable package is available in npm.

react-native-tensorflow has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Feeds a Tensorflow inference
Converts a ReadableArray to a byte array
To double array
Convert a ReadableArray to a byte array
Initializes a TensorFlow inference
Fetch data from URL
Creates a new TfContext for the given model and model
Loads a resource
Runs an ontology inference
Run the inference
Convert a ReadableArray to a String array
Process an image
Creates a matrix that can be used to represent the image
Tries to recognize an image
Init ImageRecognizer
Initializes an ImageRecognizer instance
Get the output list for the specified operation
Closes a graph
Closes the inference
Resets the inference context

Get all kandi verified functions for this library.

react-native-tensorflow Key Features

No Key Features are available at this moment for react-native-tensorflow.

react-native-tensorflow Examples and Code Snippets

No Code Snippets are available at this moment for react-native-tensorflow.

Community Discussions

Trending Discussions on react-native-tensorflow

react native adding custom assets not possible, metro.config.js ignored

QUESTION

react native adding custom assets not possible, metro.config.js ignored

Asked 2019-Nov-21 at 10:53

I'm trying to use custom assets within a react native application with following configuration:

...

ANSWER

Answered 2019-Nov-19 at 11:55

Try adding them in a react-native.config.js file with the same structure. Mine looks like this:

Source https://stackoverflow.com/questions/58933354

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

Vulnerabilities

No vulnerabilities reported

Install react-native-tensorflow

You can install using 'npm i react-native-tensorflow' or download it from GitHub, npm.
You can use react-native-tensorflow like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the react-native-tensorflow component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .