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@tensorflow-models/coco-ssd

WebJar for @tensorflow-models/coco-ssd

License

License
Categories

Categories

TensorFlow Business Logic Libraries Machine Learning
GroupId

GroupId

org.webjars.npm
ArtifactId

ArtifactId

tensorflow-models__coco-ssd
Last Version

Last Version

2.1.0
Release Date

Release Date
Type

Type

jar
Description

Description

@tensorflow-models/coco-ssd
WebJar for @tensorflow-models/coco-ssd
Project URL

Project URL

https://www.webjars.org
Source Code Management

Source Code Management

https://github.com/tensorflow/tfjs-models

Download tensorflow-models__coco-ssd

Filename Size
tensorflow-models__coco-ssd-2.1.0.pom
tensorflow-models__coco-ssd-2.1.0.jar 65 KB
tensorflow-models__coco-ssd-2.1.0-sources.jar 22 bytes
tensorflow-models__coco-ssd-2.1.0-javadoc.jar 22 bytes
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How to add to project

<!-- https://jarcasting.com/artifacts/org.webjars.npm/tensorflow-models__coco-ssd/ -->
<dependency>
    <groupId>org.webjars.npm</groupId>
    <artifactId>tensorflow-models__coco-ssd</artifactId>
    <version>2.1.0</version>
</dependency>
// https://jarcasting.com/artifacts/org.webjars.npm/tensorflow-models__coco-ssd/
implementation 'org.webjars.npm:tensorflow-models__coco-ssd:2.1.0'
// https://jarcasting.com/artifacts/org.webjars.npm/tensorflow-models__coco-ssd/
implementation ("org.webjars.npm:tensorflow-models__coco-ssd:2.1.0")
'org.webjars.npm:tensorflow-models__coco-ssd:jar:2.1.0'
<dependency org="org.webjars.npm" name="tensorflow-models__coco-ssd" rev="2.1.0">
  <artifact name="tensorflow-models__coco-ssd" type="jar" />
</dependency>
@Grapes(
@Grab(group='org.webjars.npm', module='tensorflow-models__coco-ssd', version='2.1.0')
)
libraryDependencies += "org.webjars.npm" % "tensorflow-models__coco-ssd" % "2.1.0"
[org.webjars.npm/tensorflow-models__coco-ssd "2.1.0"]

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

org.webjars.npm

Versions

Version
2.1.0