Simplifies integration with Teachable Machine models from Google
A Node-RED node based in tensorflow.js that enables to run custom image classification trained models using Teachable Machine tool. All notable changes to this project will be documented in the CHANGELOG.md file.
You have two options to install the node.
Manage paletteoption in
Run the following command in your
Node-REDuser directory - typically
npm install node-red-contrib-teachable-machine
Note: If you run the command you will need to restart
Node-RED after installation. If installation goes wrong please open a new issue.
Go to Teachable Machine and follow the steps to train your custom classification model. Once trained click on the
Export Model button.
Tensorflow.js format and upload your trained model (for free). Once it is uploaded, copy the generated URL.
Once the URL is generated it will show the stored files.
Select Online Mode and paste the saved URL in the node configuration. That URL hosts all the information to load your trained model. Make sure you copy all the given URL including the
https://... and the
/ in the end.
Download all three files from the generated URL and save them locally in a folder maintaning the original filenames.
Select Local Mode and write down the absolute path of the folder that contain the three downloaded files in the node configuration. Make sure it ends with a
/ noting it is a folder.
Node-RED send a buffered image (jpeg or png) to the node. Check the example in the
Node Status Information
dot: node is idle
ring: node is working
green: model is available
yellow: preparing model
red: node error
Note: MacOSX, Windows 10 and Ubuntu 18.04+ are supported as well as using official
docker nodered/node-red image based on Alpine image. Works with Raspberry Pi too since release
- @dceejay: who inspired me thanks to node node-red-contrib-tfjs-coco-ssd