Teachable Machine Node Example

A demonstration of using Teachable Machine, which is intended to run in the browser, in Node. Based on the clever approach by tr7zw in their original demo.

How It Works

1. A workaround is used to simulate in Node just enough of the browser parts required for Teachable Machine to work.
   • jsdom to emulate a subset of browser APIs.
   • node-canvas to simulate the browser's canvas.
   • node-fetch to polyfill fetch for Node.
2. The script makes Teachable Machine models available through API endpoints defined in the script using Express.
3. An image posted to an endpoint is parsed and passed to the model. Predictions are made and the endpoint responds to the request with JSON formatted prediction results.

Usage

1. Clone this repo, cd into it, and run npm install
2. Edit app.js and add create endpoints associated with a trained model.
3. Run app server either with npm start or node app.js
4. Post an image to the endpoint. This has the potential to be a source of frustration — if POSTing the image is not done correctly the application may crash of malfunction. See "Image POST Tips and Notes" and "Post Examples" below.

Image POST Tips and Notes

• Ensure you are pointing to the right endpoint name on the right port. (e.g. localhost:3000 if posting from the same computer the app is running on, or myhostname:3000 if posting from another computer)
• Ensure you are supplying the correct path to the image being posted.

POST Examples

Linux/OSX curl -X POST -H "Content-Type: image/jpeg" --data-binary '@./sample_images/person-using-iphone-1194760.jpg' http://localhost:3000/test ^{view a breakdown of this command}

Windows PowerShell.exe Invoke-WebRequest -uri http://localhost:3000/test -Method Post -Infile "./sample_images/person-using-iphone-1194760.jpg" -ContentType 'image/jpeg'

Notes

• The sample model used makes a prediction on whether a supplied image contains a Solo Human, a Solo Phone, or a Human and Phone. I am not the creator of this model. It is used here with permission from the author, lachlanjc, who uses it in this post.
  • Use the model's URL to explore interactively in the Teachable Machine UI or use it in the code for this demo by passing the URL to the addEndpoint() method.
• node-canvas is a jsdom dependency for canvas/img support
  • See system dependency info at https://bit.ly/3bI4V2a
• Notable changes from the original demo on which this is based:
  • Removes requirement in original demo to monkey patch (comment out) part of the Teachable Machine npm package.
  • Removes custom _arrayBufferToBase64 method in favor of built-in conversion.
  • Dynamically allows for different image Content-Types (i.e. image/jpeg, image/png).
  • Uses eslint with Google style guide configuration for linting.
    • Adds additional comments and JSDOCs.