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

Pretrained models for TensorFlow.js
https://github.com/tensorflow/tfjs-models

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Pretrained models for TensorFlow.js

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README 

        
# 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](https://github.com/tensorflow/tfjs/issues) 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


    live

    Classify images with labels from the ImageNet database.

    npm i @tensorflow-models/mobilenet

  

  

    source

  

  

  

    
Hand


    live

    Real-time hand pose detection in the browser using TensorFlow.js.

    npm i @tensorflow-models/hand-pose-detection

  

  

    source

  

    

  

    
Pose


    live

    An API for real-time human pose detection in the browser.

    npm i @tensorflow-models/pose-detection

  

  

    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

  

    
DeepLab v3


    

    Semantic segmentation

    npm i @tensorflow-models/deeplab

  

  

    source

  

    

  

    
Face Landmark Detection


    live

    Real-time 3D facial landmarks detection to infer the approximate surface geometry of a human face

    npm i @tensorflow-models/face-landmarks-detection

  

  

    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

  

  

  

  

    Depth Estimation

    
Portrait Depth


    live

    Estimate per-pixel depth (the distance to the camera center) for a single portrait image, which can be further used for creative applications such as 3D photo and relighting.

    npm i @tensorflow-models/depth-estimation

  

  

    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](./mobilenet/package.json) `package.json` and `run_tests.ts` [helper](./mobilenet/run_tests.ts) for reference).



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

repo:



`yarn presubmit`