@tensorflow-models/body-pix

WebJar for @tensorflow-models/body-pix

License	Apache-2.0
Categories	TensorFlow Business Logic Libraries Machine Learning
GroupId	org.webjars.npm
ArtifactId	tensorflow-models__body-pix
Last Version	1.1.2
Release Date	Sep 10, 2020
Type	jar
Description	@tensorflow-models/body-pix WebJar for @tensorflow-models/body-pix
Project URL	https://www.webjars.org
Source Code Management	https://github.com/tensorflow/tfjs-models

Download tensorflow-models__body-pix

Filename	Size
tensorflow-models__body-pix-1.1.2.pom
tensorflow-models__body-pix-1.1.2.jar	55 KB
tensorflow-models__body-pix-1.1.2-sources.jar	22 bytes
tensorflow-models__body-pix-1.1.2-javadoc.jar	22 bytes

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/org.webjars.npm/tensorflow-models__body-pix/ -->
<dependency>
    <groupId>org.webjars.npm</groupId>
    <artifactId>tensorflow-models__body-pix</artifactId>
    <version>1.1.2</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/org.webjars.npm/tensorflow-models__body-pix/
implementation 'org.webjars.npm:tensorflow-models__body-pix:1.1.2'

Gradle Kotlin

// https://jarcasting.com/artifacts/org.webjars.npm/tensorflow-models__body-pix/
implementation ("org.webjars.npm:tensorflow-models__body-pix:1.1.2")

Apache Buildr

'org.webjars.npm:tensorflow-models__body-pix:jar:1.1.2'

Apache Ivy

<dependency org="org.webjars.npm" name="tensorflow-models__body-pix" rev="1.1.2">
  <artifact name="tensorflow-models__body-pix" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='org.webjars.npm', module='tensorflow-models__body-pix', version='1.1.2')
)

Scala SBT

libraryDependencies += "org.webjars.npm" % "tensorflow-models__body-pix" % "1.1.2"

Leiningen

[org.webjars.npm/tensorflow-models__body-pix "1.1.2"]

Dependencies

There are no dependencies for this project. It is a standalone project that does not depend on any other jars.

Project Modules

There are no modules declared in this project.

Pre-trained TensorFlow.js models

This repository hosts a set of pre-trained models that have been ported to TensorFlow.js.

The models are hosted on NPM and unpkg so they can be used in any project out of the box. They can be used directly or used in a transfer learning setting with TensorFlow.js.

To find out about APIs for models, look at the README in each of the respective directories. In general, we try to hide tensors so the API can be used by non-machine learning experts.

For those interested in contributing a model, please file a GitHub issue on tfjs to gauge interest. We are trying to add models that complement the existing set of models and can be used as building blocks in other apps.

Models

Type	Model	Demo	Details	Install
Images	MobileNet		Classify images with labels from the ImageNet database.	npm i @tensorflow-models/mobilenet
		source
	HandPose	live	Real-time hand pose detection in the browser using TensorFlow.js.	npm i @tensorflow-models/handpose
		source
	PoseNet	live	A machine learning model which allows for real-time human pose estimation in the browser. See a detailed description here.	npm i @tensorflow-models/posenet
		source
	Coco SSD		Object detection model that aims to localize and identify multiple objects in a single image. Based on the TensorFlow object detection API.	npm i @tensorflow-models/coco-ssd
		source
	BodyPix	live	Real-time person and body part segmentation in the browser using TensorFlow.js.	npm i @tensorflow-models/body-pix
		source
	BlazeFace	live	Real-time rapid Face detection in the browser using TensorFlow.js.	npm i @tensorflow-models/blazeface
		source
	DeepLab v3		Semantic segmentation	npm i @tensorflow-models/deeplab
		source
Audio	Speech Commands	live	Classify 1 second audio snippets from the speech commands dataset.	npm i @tensorflow-models/speech-commands
		source
Text	Universal Sentence Encoder		Encode text into a 512-dimensional embedding to be used as inputs to natural language processing tasks such as sentiment classification and textual similarity.	npm i @tensorflow-models/universal-sentence-encoder
		source
	Text Toxicity	live	Score the perceived impact a comment might have on a conversation, from "Very toxic" to "Very healthy".	npm i @tensorflow-models/toxicity
		source
General Utilities	KNN Classifier		This package provides a utility for creating a classifier using the K-Nearest Neighbors algorithm. Can be used for transfer learning.	npm i @tensorflow-models/knn-classifier
		source

Development

You can run the unit tests for any of the models by running the following inside a directory:

yarn test

New models should have a test NPM script (see this package.json and run_tests.ts helper for reference).

To run all of the tests, you can run the following command from the root of this repo:

yarn presubmit

Versions

Version
1.1.2 Sep 10, 2020