Creating a workout tracker using Teachable Machine and SashiDo

This page summarizes the projects mentioned and recommended in the original post on dev.to

SurveyJS - Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App
With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
surveyjs.io
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InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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  • workout-tracker

  • Github Repository Official Parse Guide for Javascript SashiDo’s Getting Started Guide Teachable Machine on NodeJS Teachable Machine Community repo on GitHub

  • teachablemachine-community

    Example code snippets and machine learning code for Teachable Machine

  • Github Repository Official Parse Guide for Javascript SashiDo’s Getting Started Guide Teachable Machine on NodeJS Teachable Machine Community repo on GitHub

  • SurveyJS

    Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.

    SurveyJS logo
  • awesome-teachable-machine

    Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!

  • 1 const express = require(' express') 2 const TeachableMachine = require('@sashido/teachablemachine-node') 3 4 const cars = require('cors') 5 6 const model = new TeachableMachine(f 7 modelUrl: 'https://teachablemachine.withgoogle.com/models/aH894BqRS/', 8 }) 9 10 const app = express() 11 12 app.use(cors()) 13 14 app.use(express.json()) 15 app.post('/image/classify', async (req, res) => { 16 const { url } = req.body 17 18 return model 19 .classify({ 20 imageUrl: url, 21 }) 22 .then((predictions) => { 23 console.log(predictions) 24 return res.json(predictions) 25 }) 26 .catch((e) => { 27 console.error(e) 28 res.status(500).send('Something went wrong!') 29 }) 30 }) 31

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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