├── .gitignore ├── icons └── tensorflow_logo.png ├── .github ├── dependabot.yaml └── workflows │ ├── ci.yml │ └── npm-publish.yml ├── .pre-commit-config.yaml ├── package.json ├── examples ├── local_test.json └── basic.json ├── README.md ├── teachable_machine.html ├── CHANGELOG.md ├── teachable_machine.js └── LICENSE /.gitignore: -------------------------------------------------------------------------------- 1 | node_modules 2 | *.DS* 3 | .vscode 4 | -------------------------------------------------------------------------------- /icons/tensorflow_logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/bonastreyair/node-red-contrib-teachable-machine/HEAD/icons/tensorflow_logo.png -------------------------------------------------------------------------------- /.github/dependabot.yaml: -------------------------------------------------------------------------------- 1 | version: 2 2 | updates: 3 | - package-ecosystem: github-actions 4 | directory: / 5 | schedule: 6 | interval: weekly 7 | - package-ecosystem: npm 8 | directory: / 9 | schedule: 10 | interval: weekly 11 | -------------------------------------------------------------------------------- /.github/workflows/ci.yml: -------------------------------------------------------------------------------- 1 | name: CI 2 | on: 3 | push: 4 | branches: 5 | - main 6 | pull_request: 7 | jobs: 8 | install: 9 | runs-on: ubuntu-latest 10 | steps: 11 | - name: Checkout repository 12 | uses: actions/checkout@v6 13 | - name: Setup node 14 | uses: actions/setup-node@v6 15 | with: 16 | node-version: 12 17 | registry-url: https://registry.npmjs.org/ 18 | - name: npm install 19 | run: npm install 20 | -------------------------------------------------------------------------------- /.github/workflows/npm-publish.yml: -------------------------------------------------------------------------------- 1 | name: Publish npm package 2 | on: 3 | release: 4 | types: [created] 5 | jobs: 6 | publish: 7 | runs-on: ubuntu-latest 8 | steps: 9 | - name: Checkout repository 10 | uses: actions/checkout@v6 11 | - name: Setup node 12 | uses: actions/setup-node@v6 13 | with: 14 | node-version: 12 15 | registry-url: https://registry.npmjs.org/ 16 | - name: Publish npm package 17 | run: npm publish 18 | env: 19 | NODE_AUTH_TOKEN: ${{secrets.npm_token}} 20 | -------------------------------------------------------------------------------- /.pre-commit-config.yaml: -------------------------------------------------------------------------------- 1 | repos: 2 | - repo: https://github.com/pre-commit/pre-commit-hooks 3 | rev: v6.0.0 4 | hooks: 5 | - id: trailing-whitespace 6 | - id: check-added-large-files 7 | - id: check-yaml 8 | - id: end-of-file-fixer 9 | - id: check-json 10 | - id: pretty-format-json 11 | args: [--autofix, --no-sort-keys] 12 | - repo: https://github.com/standard/standard 13 | rev: v17.1.2 14 | hooks: 15 | - id: standard 16 | - repo: https://github.com/google/yamlfmt 17 | rev: v0.20.0 18 | hooks: 19 | - id: yamlfmt 20 | - repo: https://github.com/executablebooks/mdformat 21 | rev: 1.0.0 22 | hooks: 23 | - id: mdformat 24 | -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "node-red-contrib-teachable-machine", 3 | "version": "1.4.1", 4 | "description": "Simplifies integration with Teachable Machine models from Google", 5 | "dependencies": { 6 | "node-fetch": "3.3.2", 7 | "@tensorflow/tfjs-node": "4.22.0", 8 | "pureimage": "0.4.18" 9 | }, 10 | "engines": { 11 | "node": ">=16.20.0" 12 | }, 13 | "keywords": [ 14 | "node-red", 15 | "tensorflow", 16 | "tensorflowjs", 17 | "classification", 18 | "teachable machine", 19 | "google" 20 | ], 21 | "license": "Apache-2.0", 22 | "node-red": { 23 | "version": ">=2.1.0", 24 | "nodes": { 25 | "teachable machine": "teachable_machine.js" 26 | } 27 | }, 28 | "repository": { 29 | "type": "git", 30 | "url": "https://github.com/bonastreyair/node-red-contrib-teachable-machine" 31 | }, 32 | "author": { 33 | "name": "Yair Bonastre", 34 | "email": "bonastreyair@gmail.com" 35 | } 36 | } 37 | -------------------------------------------------------------------------------- /examples/local_test.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "id": "456d4286.6d5b2c", 4 | "type": "debug", 5 | "z": "17514116325f40c5", 6 | "name": "", 7 | "active": true, 8 | "tosidebar": true, 9 | "console": false, 10 | "tostatus": false, 11 | "complete": "true", 12 | "targetType": "full", 13 | "x": 650, 14 | "y": 540, 15 | "wires": [] 16 | }, 17 | { 18 | "id": "91ebc5b6.8ccdd8", 19 | "type": "teachable machine", 20 | "z": "17514116325f40c5", 21 | "name": "", 22 | "mode": "online", 23 | "modelUri": "https://teachablemachine.withgoogle.com/models/49PRz_c_9/", 24 | "localModel": "teachable_model", 25 | "output": "best", 26 | "activeThreshold": false, 27 | "threshold": 80, 28 | "activeMaxResults": false, 29 | "maxResults": 3, 30 | "passThrough": true, 31 | "x": 490, 32 | "y": 540, 33 | "wires": [ 34 | [ 35 | "456d4286.6d5b2c" 36 | ] 37 | ] 38 | }, 39 | { 40 | "id": "01e26608fa047b50", 41 | "type": "camera", 42 | "z": "17514116325f40c5", 43 | "name": "", 44 | "x": 310, 45 | "y": 540, 46 | "wires": [ 47 | [ 48 | "91ebc5b6.8ccdd8" 49 | ] 50 | ] 51 | }, 52 | { 53 | "id": "e5021a59647a2f5e", 54 | "type": "fileinject", 55 | "z": "17514116325f40c5", 56 | "name": "", 57 | "x": 300, 58 | "y": 580, 59 | "wires": [ 60 | [ 61 | "91ebc5b6.8ccdd8" 62 | ] 63 | ] 64 | }, 65 | { 66 | "id": "309069d9154be5ef", 67 | "type": "inject", 68 | "z": "17514116325f40c5", 69 | "name": "reload", 70 | "props": [ 71 | { 72 | "p": "reload", 73 | "v": "true", 74 | "vt": "bool" 75 | } 76 | ], 77 | "repeat": "", 78 | "crontab": "", 79 | "once": false, 80 | "onceDelay": 0.1, 81 | "topic": "", 82 | "x": 310, 83 | "y": 500, 84 | "wires": [ 85 | [ 86 | "91ebc5b6.8ccdd8" 87 | ] 88 | ] 89 | } 90 | ] 91 | -------------------------------------------------------------------------------- /examples/basic.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "id": "9b0a1240.fe6c2", 4 | "type": "http request", 5 | "z": "17514116325f40c5", 6 | "name": "random image", 7 | "method": "GET", 8 | "ret": "bin", 9 | "paytoqs": false, 10 | "url": "https://loremflickr.com/320/240/sport", 11 | "tls": "", 12 | "persist": false, 13 | "proxy": "", 14 | "authType": "", 15 | "x": 280, 16 | "y": 120, 17 | "wires": [ 18 | [ 19 | "91ebc5b6.8ccdd8" 20 | ] 21 | ] 22 | }, 23 | { 24 | "id": "9cbe3704.6bb118", 25 | "type": "inject", 26 | "z": "17514116325f40c5", 27 | "name": "new", 28 | "repeat": "", 29 | "crontab": "", 30 | "once": false, 31 | "onceDelay": 0.1, 32 | "topic": "", 33 | "payload": "", 34 | "payloadType": "date", 35 | "x": 130, 36 | "y": 120, 37 | "wires": [ 38 | [ 39 | "9b0a1240.fe6c2" 40 | ] 41 | ] 42 | }, 43 | { 44 | "id": "456d4286.6d5b2c", 45 | "type": "debug", 46 | "z": "17514116325f40c5", 47 | "name": "", 48 | "active": true, 49 | "tosidebar": true, 50 | "console": false, 51 | "tostatus": false, 52 | "complete": "true", 53 | "targetType": "full", 54 | "x": 650, 55 | "y": 120, 56 | "wires": [] 57 | }, 58 | { 59 | "id": "91ebc5b6.8ccdd8", 60 | "type": "teachable machine", 61 | "z": "17514116325f40c5", 62 | "name": "", 63 | "mode": "online", 64 | "modelUri": "https://teachablemachine.withgoogle.com/models/49PRz_c_9/", 65 | "localModel": "teachable_model", 66 | "output": "best", 67 | "activeThreshold": false, 68 | "threshold": 80, 69 | "activeMaxResults": false, 70 | "maxResults": 3, 71 | "passThrough": true, 72 | "x": 490, 73 | "y": 120, 74 | "wires": [ 75 | [ 76 | "456d4286.6d5b2c" 77 | ] 78 | ] 79 | }, 80 | { 81 | "id": "994234755381c0c0", 82 | "type": "inject", 83 | "z": "17514116325f40c5", 84 | "name": "reload", 85 | "props": [ 86 | { 87 | "p": "reload", 88 | "v": "true", 89 | "vt": "bool" 90 | } 91 | ], 92 | "repeat": "", 93 | "crontab": "", 94 | "once": false, 95 | "onceDelay": 0.1, 96 | "topic": "", 97 | "x": 310, 98 | "y": 80, 99 | "wires": [ 100 | [ 101 | "91ebc5b6.8ccdd8" 102 | ] 103 | ] 104 | } 105 | ] 106 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # node-red-contrib-teachable-machine 2 | 3 | [![Node-RED node](https://img.shields.io/badge/Node--RED-node-red?logo=node-red)](https://nodered.org) 4 | [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/bonastreyair/node-red-contrib-teachable-machine/main.svg)](https://results.pre-commit.ci/latest/github/bonastreyair/node-red-contrib-teachable-machine/main) 5 | [![CI](https://img.shields.io/github/actions/workflow/status/bonastreyair/node-red-contrib-teachable-machine/ci.yml?branch=main&label=CI&logo=github)](https://github.com/bonastreyair/node-red-contrib-teachable-machine/actions?workflow=CI) 6 | [![npm latest release](https://img.shields.io/npm/v/node-red-contrib-teachable-machine?logo=npm)](https://www.npmjs.com/package/node-red-contrib-teachable-machine) 7 | [![npm total downloads](https://img.shields.io/npm/dt/node-red-contrib-teachable-machine)](https://www.npmjs.com/package/node-red-contrib-teachable-machine) 8 | [![Package Quality](https://packagequality.com/shield/node-red-contrib-teachable-machine.svg)](https://packagequality.com/#?package=node-red-contrib-teachable-machine) 9 | [![JavaScript Style Guide](https://img.shields.io/badge/code_style-standard-brightgreen.svg?color=yellow&logo=JavaScript&logoColor=white)](https://standardjs.com) 10 | [![Code Climate maintainability](https://img.shields.io/codeclimate/maintainability/bonastreyair/node-red-contrib-teachable-machine?logo=codeclimate)](https://codeclimate.com/github/bonastreyair/node-red-contrib-teachable-machine/maintainability) 11 | [![GitHub license](https://img.shields.io/github/license/bonastreyair/node-red-contrib-teachable-machine?color=blue)](https://github.com/bonastreyair/node-red-contrib-teachable-machine/blob/master/LICENSE) 12 | [![donate PayPal](https://img.shields.io/badge/donate-PayPal-blue)](https://www.paypal.me/bonastreyair) 13 | 14 | A [Node-RED](https://nodered.org) node based in [tensorflow.js](https://www.tensorflow.org/js) that enables to run custom image classification trained models using [Teachable Machine](https://teachablemachine.withgoogle.com/train/image) tool. All notable changes to this project will be documented in the [CHANGELOG.md](https://github.com/bonastreyair/node-red-contrib-teachable-machine/blob/main/CHANGELOG.md) file. 15 | 16 |

17 | 18 |

19 | 20 | ## Install 21 | 22 | You have two options to install the node. 23 | 24 | - Use `Manage palette` option in `Node-RED` Menu (recommended) 25 | ![manage_pallete](https://user-images.githubusercontent.com/37800834/80922178-88923b00-8d7b-11ea-9fcf-ea1839bfee09.png) 26 | 27 | - Run the following command in your `Node-RED` user directory - typically `~/.node-red` 28 | 29 | ```bash 30 | npm install node-red-contrib-teachable-machine 31 | ``` 32 | 33 | **Note:** If you run the command you will need to restart `Node-RED` after installation. If installation goes wrong please open a [new issue](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues). 34 | 35 | ## Node usage 36 | 37 | ### Step 1 38 | 39 | Go to [Teachable Machine](https://teachablemachine.withgoogle.com/train/image) and follow the steps to train your custom classification model. Once trained click on the `Export Model` button. 40 | 41 | ![teachable_machine_export](https://user-images.githubusercontent.com/37800834/80190158-18b1e100-8614-11ea-9ccf-6668e49e7e2d.png) 42 | 43 | ### Step 2 44 | 45 | Select `Tensorflow.js` format and upload your trained model (for free). Once it is uploaded, copy the generated URL. 46 | 47 | ![use_teachable_machine](https://user-images.githubusercontent.com/37800834/79056723-8431a100-7c59-11ea-9488-346f4f8e6004.png) 48 | 49 | Once the URL is generated it will show the stored files. 50 | 51 | ![model_files](https://user-images.githubusercontent.com/37800834/204745026-40cf7cec-6775-4e78-a454-4c82271d613f.png) 52 | 53 | ### Step 3 54 | 55 | #### **Online Mode** 56 | 57 | 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. 58 | 59 | ![online-config](https://user-images.githubusercontent.com/37800834/204746402-2551eb8c-576c-40fa-a250-7f0f93a9d670.png) 60 | 61 | #### **Local Mode** 62 | 63 | Download all three files from the generated URL and save them locally in a folder maintaning the original filenames. 64 | 65 | 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. 66 | 67 | ![local-config](https://user-images.githubusercontent.com/37800834/204746412-fafc1b81-6431-4cb3-82bb-d4a29e415108.png) 68 | 69 | ### Step 4 70 | 71 | In `Node-RED` send a buffered image (jpeg or png) to the node. Check the example in the `Import` section. 72 | 73 | ## Node Status Information 74 | 75 | ### Shape 76 | 77 | - ■ `dot`: node is idle 78 | - □ `ring`: node is working 79 | 80 | ### Color 81 | 82 | - 🟩 `green`: model is available 83 | - 🟨 `yellow`: preparing model 84 | - 🟥 `red`: node error 85 | 86 | ## Requirements 87 | 88 | - `Node-RED v2.1.0+` 89 | - `Node.js v16.20.0+` 90 | 91 | *Warning:* Only the official Docker `nodered/node-red` [image](https://hub.docker.com/r/nodered/node-red/) based on [Debian](https://www.debian.org) `v3.1.0+` image works since it needs `ld-linux-x86-64.so.2`. This necessary library is not present in the default [Alpine](https://hub.docker.com/_/alpine) Docker image version. 92 | -------------------------------------------------------------------------------- /teachable_machine.html: -------------------------------------------------------------------------------- 1 | 2 | 56 | 57 | 58 | 102 | 103 | 104 | 137 | -------------------------------------------------------------------------------- /CHANGELOG.md: -------------------------------------------------------------------------------- 1 | # Changelog 2 | 3 | All notable changes to this project will be documented in this file following a [Semantic Versioning](https://semver.org/spec/v2.0.0.html). The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/). 4 | 5 | ## [1.4.0] - 2022-11-30 6 | 7 | ### Added 8 | 9 | - Local Mode Support 10 | 11 | ### Changed 12 | 13 | - Improved code structure 14 | - Upgrade pre-commit dependencies 15 | - Dependency change from `@tensorflow/tfjs` to `@tensorflow/tfjs-node` 16 | - Upgraded `node-fetch` to version `3.3.0` 17 | - Upgraded `pureimage` to version `0.3.14` 18 | 19 | ## [1.3.1] - 2021-10-09 20 | 21 | ### Added 22 | 23 | - Using `pre-commit.ci` with its own badge 24 | - New `Code Climate` mantainability score badge 25 | 26 | ### Changed 27 | 28 | - Improved status node information 29 | - shape: 30 | - ■ `dot`: node is idle 31 | - □ `ring`: node is working 32 | - color: 33 | - 🟩 `green`: model is available 34 | - 🟨 `yellow`: preparing model 35 | - 🟥 `red`: node error 36 | 37 | ### Fixed 38 | 39 | - Node hungs when using a bad image buffer, even with PNG images - [#21](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/21) 40 | 41 | ## [1.3.0] - 2021-09-24 42 | 43 | ### Added 44 | 45 | - Model reload option flag during running time - [#22](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/22) - Thanks [@acejacek](https://github.com/acejacek) for the suggestion and the PR 46 | - `pre-commit` common checks with `standard`, `yamlfmt` and `mdformat` style checks 47 | - GitHub Actions **CI** test with badge 48 | - **npm** quality badge to the `README` file 49 | - Automatic dependency checks with **dependabot** 50 | 51 | ### Changed 52 | 53 | - Upgraded `node-fetch` to version `3.0.0` 54 | - Upgraded `pureimage` to version `0.3.5` 55 | - Upgraded `package-lock.json` file format to `v7` 56 | - Updated the `basic` example with the new reload option flag 57 | 58 | ## [1.2.2] - 2020-10-24 59 | 60 | ### Changed 61 | 62 | - Upgraded `@tensorflow/tfjs-node` to version `1.4.0` to help Raspberry Pi installation - [#18](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/18) 63 | 64 | ## [1.2.1] - 2020-10-24 65 | 66 | ### Added 67 | 68 | - `package-lock.json` to ensure always exact versions during installation 69 | 70 | ### Fixed 71 | 72 | - Output API was changed by mistake, now msg.payload still outputs `class` and `score` keys for each classification as in `v1.1.0+` releases 73 | - When selecting all predictions without filter only one result was showing up 74 | 75 | ## [1.2.0] - 2020-10-23 76 | 77 | ### Added 78 | 79 | - Compatibility with official Node-RED Dockerized image based on [Alpine](https://hub.docker.com/_/alpine) image 80 | - Compatibility with Raspberry Pi 81 | - `pureimage` npm package dependency to manage buffer images using pure javascript - [#17](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/17) 82 | - `node-fetch` npm package dependency to manage http request to obtain the model info 83 | 84 | ### Removed 85 | 86 | - `@teachablemachine/image` npm package dependency 87 | - `jsdom` npm package dependency 88 | - `canvas` npm package dependency 89 | 90 | ## [1.1.5] - 2020-09-08 91 | 92 | ### Fixed 93 | 94 | - Error when installing nodes - [#15](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/15) 95 | 96 | ### Changed 97 | 98 | - Upgrade `jsdom` version from `16.2.2` to `16.4.0` 99 | 100 | ## [1.1.4] - 2020-06-05 101 | 102 | ### Fixed 103 | 104 | - Better usage of `HTMLVideoElement` class imported from `dom.window` 105 | - Better accuracy representation in the node status without decimals 106 | 107 | ### Changed 108 | 109 | - Some variable types from `const` to `var` 110 | 111 | ## [1.1.3] - 2020-06-05 112 | 113 | ### Fixed 114 | 115 | - Prediction does not work when save_image's box is checked - [#14](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/14) 116 | 117 | ### Changed 118 | 119 | - Dependancy is now `@tensorflow/tfjs 1.3.1` instead of `@tensorflow/tfjs-node 1.4.0`, to match teachable machine correct dependencies 120 | 121 | ## [1.1.2] - 2020-05-03 122 | 123 | ### Added 124 | 125 | - PayPal donation badge in `README` file 126 | 127 | ### Fixed 128 | 129 | - `className` key (when `Best prediction` option) fixed to `class` in the results 130 | - Refinements on `README` file 131 | - Alignment HTML icons in node configuration 132 | 133 | ## [1.1.1] - 2020-04-24 134 | 135 | ### Added 136 | 137 | - New configuration checkbox to pass through the input image in `msg.image` 138 | 139 | ### Changed 140 | 141 | - `probability` key changed to `score` in the results 142 | - Updated example with new configuration parameter 143 | 144 | ### Fixed 145 | 146 | - Selecting `Best prediction` option made the `Name` disappear 147 | 148 | ## [1.1.0] - 2020-04-22 149 | 150 | ### Changed 151 | 152 | - Updated image on how to use Teachable Machine and configuration node on Step 3 153 | - Use standard image treatment for `README` instead of HTML 154 | - Upgraded `@tensorflow/tfjs-node` to version `1.4.0` to enable coexistantce with [tfjs-nodes](https://github.com/dceejay/tfjs-nodes) nodes - [#8](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/8) 155 | 156 | ## [1.0.1] - 2020-04-15 157 | 158 | ### Changed 159 | 160 | - Updated information help node 161 | 162 | ## [1.0.0] - 2020-04-15 163 | 164 | ### Added 165 | 166 | - Total npm downloads badge 167 | - Online/Local options in configuration node (Local still not functional) 168 | - Internal common functions to set node status 169 | - New Filters configurations when `All predictions` Output mode is selected 170 | - Threshold in % - (0 -> 100%) 171 | - Max. results - (1 -> 5) 172 | - General code optimitzations 173 | - [Mentions](https://github.com/bonastreyair/node-red-contrib-teachable-machine#mentions) section in `README` file 174 | 175 | ### Changed 176 | 177 | - Icon updated to **Tensorflow 2.0** new logo 178 | - Updated configuration node 179 | - Using all `README` badges from [Shields.io](https://shields.io/) 180 | - Outputs is always an array of results even if `Best prediction` is selected 181 | 182 | ## [0.1.3] - 2020-04-12 183 | 184 | ### Added 185 | 186 | - Use of badges in `README` file 187 | - New images for _Installation_ and _Node usage_ in `README` 188 | - `JavaScript` code has been standarized following [Standard JS](https://standardjs.com/index.html) 189 | 190 | ### Changed 191 | 192 | - Information on HTML node [#5](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/5) 193 | 194 | ### Fixed 195 | 196 | - Typos on `README` 197 | - `basic` example with issues to load 198 | - Errors not shown on console or in `Node-RED` 199 | 200 | ## [0.1.2] - 2020-04-12 201 | 202 | ### Added 203 | 204 | - Improvements on `README` file 205 | 206 | ### Fixed 207 | 208 | - Loading model error `response.arrayBuffer is not a function` [#3](https://github.com/bonastreyair/node-red-contrib-teachable-machine/issues/3) 209 | 210 | ## [0.1.1] - 2020-04-11 211 | 212 | ### Added 213 | 214 | - Comments in the code 215 | 216 | ### Changed 217 | 218 | - Downgraded `@tensorflow/tfjs-node` from version `1.4.0` to `1.3.1` for better compatibility 219 | - Output has changed from `checkbox` to a `list`, you can now select `Best predictions` or `All predictions` 220 | - Code cleaning 221 | 222 | ### Fixed 223 | 224 | - WebGL loading error in JSDOM 225 | - When installing the node -> `npm WARN @teachablemachine/image@0.8.4 requires a peer of @tensorflow/tfjs@1.3.1 but none is installed` 226 | 227 | ## 0.1.0 - 2020-04-11 228 | 229 | ### Added 230 | 231 | - Functional using **Teachable Machine** Online Model URL 232 | - Option to select **Top-1** or all results 233 | - `CHANGELOG.md` file 234 | - `README.md` file 235 | 236 | [0.1.1]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v0.1.0...v0.1.1 237 | [0.1.2]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v0.1.1...v0.1.2 238 | [0.1.3]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v0.1.2...v0.1.3 239 | [1.0.0]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v0.1.3...v1.0.0 240 | [1.0.1]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.0.0...v1.0.1 241 | [1.1.0]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.0.1...v1.1.0 242 | [1.1.1]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.1.0...v1.1.1 243 | [1.1.2]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.1.1...v1.1.2 244 | [1.1.3]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.1.2...v1.1.3 245 | [1.1.4]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.1.3...v1.1.4 246 | [1.1.5]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.1.4...v1.1.5 247 | [1.2.0]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.1.5...v1.2.0 248 | [1.2.1]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.2.0...v1.2.1 249 | [1.2.2]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.2.1...v1.2.2 250 | [1.3.0]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.2.2...v1.3.0 251 | [1.3.1]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.3.0...v1.3.1 252 | [1.4.0]: https://github.com/bonastreyair/node-red-contrib-teachable-machine/compare/v1.3.1...v1.4.0 253 | -------------------------------------------------------------------------------- /teachable_machine.js: -------------------------------------------------------------------------------- 1 | module.exports = function (RED) { 2 | /* Initial Setup */ 3 | const { Readable } = require('stream') 4 | const fs = require('fs') 5 | const fetch = (...args) => import('node-fetch').then(({ default: fetch }) => fetch(...args)) 6 | const tf = require('@tensorflow/tfjs-node') 7 | const PImage = require('pureimage') 8 | 9 | function isPng (buffer) { 10 | if (!buffer || buffer.length < 8) { 11 | return false 12 | } 13 | 14 | return buffer[0] === 0x89 && 15 | buffer[1] === 0x50 && 16 | buffer[2] === 0x4E && 17 | buffer[3] === 0x47 && 18 | buffer[4] === 0x0D && 19 | buffer[5] === 0x0A && 20 | buffer[6] === 0x1A && 21 | buffer[7] === 0x0A 22 | } 23 | 24 | function teachableMachine (config) { 25 | /* Node-RED Node Code Creation */ 26 | RED.nodes.createNode(this, config) 27 | const node = this 28 | 29 | const nodeStatus = { 30 | MODEL: { 31 | LOADING: { fill: 'yellow', shape: 'ring', text: 'loading...' }, 32 | RELOADING: { fill: 'yellow', shape: 'ring', text: 'reloading...' }, 33 | READY: { fill: 'green', shape: 'dot', text: 'ready' }, 34 | DECODING: { fill: 'green', shape: 'ring', text: 'decoding...' }, 35 | PREPROCESSING: { fill: 'green', shape: 'ring', text: 'preprocessing...' }, 36 | INFERENCING: { fill: 'green', shape: 'ring', text: 'inferencing...' }, 37 | POSTPROCESSING: { fill: 'green', shape: 'ring', text: 'postprocessing...' }, 38 | RESULT: (text) => { return { fill: 'green', shape: 'dot', text } } 39 | }, 40 | ERROR: (text) => { node.error(text); return { fill: 'red', shape: 'dot', text } }, 41 | CLOSE: {} 42 | } 43 | 44 | class ModelManager { 45 | constructor () { 46 | this.ready = false 47 | this.labels = [] 48 | } 49 | 50 | async load (uri) { 51 | if (this.ready) { 52 | node.status(nodeStatus.MODEL.RELOADING) 53 | } else { 54 | node.status(nodeStatus.MODEL.LOADING) 55 | } 56 | 57 | this.model = await this.getModel(uri) 58 | this.labels = await this.getLabels(uri) 59 | 60 | this.input = { 61 | height: this.model.inputs[0].shape[1], 62 | width: this.model.inputs[0].shape[2], 63 | channels: this.model.inputs[0].shape[3] 64 | } 65 | 66 | this.ready = true 67 | return this.model 68 | } 69 | 70 | async getModel (uri) { 71 | throw new Error('getModel(uri) needs to be implemented') 72 | } 73 | 74 | async getLabels (uri) { 75 | throw new Error('getLabels(uri) needs to be implemented') 76 | } 77 | } 78 | 79 | class OnlineModelManager extends ModelManager { 80 | async getModel (uri) { 81 | return await tf.loadLayersModel(uri + 'model.json') 82 | } 83 | 84 | async getLabels (uri) { 85 | const response = await fetch(uri + 'metadata.json') 86 | return JSON.parse(await response.text()).labels 87 | } 88 | } 89 | 90 | class LocalModelManager extends ModelManager { 91 | async getModel (uri) { 92 | return await tf.loadLayersModel('file://' + uri + 'model.json') 93 | } 94 | 95 | async getLabels (uri) { 96 | const file = fs.readFileSync(uri + 'metadata.json') 97 | return JSON.parse(file).labels 98 | } 99 | } 100 | 101 | const modelManagerFactory = { 102 | online: new OnlineModelManager(), 103 | local: new LocalModelManager() 104 | } 105 | 106 | function nodeInit () { 107 | node.modelManager = modelManagerFactory[config.mode] 108 | if (config.modelUri !== '') { 109 | loadModel(config.modelUri) 110 | } 111 | } 112 | 113 | /** 114 | * Loads the Model trained from the Teachable Machine web. 115 | * @param uri where to load the model from 116 | */ 117 | async function loadModel (uri) { 118 | try { 119 | node.model = await node.modelManager.load(uri) 120 | node.status(nodeStatus.MODEL.READY) 121 | } catch (error) { 122 | node.status(nodeStatus.ERROR(error)) 123 | } 124 | } 125 | 126 | async function decodeImageBuffer (imageBuffer) { 127 | node.status(nodeStatus.MODEL.DECODING) 128 | const stream = new Readable({ 129 | read () { 130 | this.push(imageBuffer) 131 | this.push(null) 132 | } 133 | }) 134 | if (isPng(imageBuffer)) { 135 | return await PImage.decodePNGFromStream(stream) 136 | } else { 137 | return await PImage.decodeJPEGFromStream(stream) 138 | } 139 | } 140 | 141 | /** 142 | * Preprocess an image to be later passed to a model.predict(). 143 | * @param image image in a bitmap format 144 | * @param inputShape input shape object of the model that contains height, width and channels 145 | */ 146 | async function preprocess (image, inputShape) { 147 | node.status(nodeStatus.MODEL.PREPROCESSING) 148 | return tf.tidy(() => { 149 | // tf.browser.fromPixels() returns a Tensor from an image element. 150 | const resizedImage = tf.image.resizeNearestNeighbor( 151 | tf.browser.fromPixels(image).toFloat(), 152 | [inputShape.height, inputShape.width] 153 | ) 154 | 155 | // Normalize the image from [0, 255] to [-1, 1]. 156 | const offset = tf.scalar(127.5) 157 | const normalizedImage = resizedImage.sub(offset).div(offset) 158 | 159 | // Reshape to a single-element batch so we can pass it to predict. 160 | return normalizedImage.reshape([1, inputShape.height, inputShape.width, inputShape.channels]) 161 | }) 162 | } 163 | 164 | /** 165 | * Infers an image buffer to obtain classification predictions. 166 | * @param imageBuffer image buffer in png or jpeg format 167 | * @returns outputs of the model 168 | */ 169 | async function inferImageBuffer (imageBuffer) { 170 | let image 171 | try { 172 | image = await decodeImageBuffer(imageBuffer) 173 | } catch (error) { 174 | node.error(error) 175 | return null 176 | } 177 | const inputs = await preprocess(image, node.modelManager.input) 178 | node.status(nodeStatus.MODEL.INFERENCING) 179 | return await node.model.predict(inputs) 180 | } 181 | 182 | /** 183 | * Computes the probabilities of the topK classes given logits by computing 184 | * softmax to get probabilities and then sorting the probabilities. 185 | * @param logits Tensor representing the logits from MobileNet. 186 | * @param topK The number of top predictions to show. 187 | */ 188 | async function getTopKClasses (logits, topK) { 189 | const values = await logits.data() 190 | topK = Math.min(topK, values.length) 191 | 192 | const valuesAndIndices = [] 193 | for (let i = 0; i < values.length; i++) { 194 | valuesAndIndices.push({ value: values[i], index: i }) 195 | } 196 | valuesAndIndices.sort((a, b) => { 197 | return b.value - a.value 198 | }) 199 | const topkValues = new Float32Array(topK) 200 | const topkIndices = new Int32Array(topK) 201 | for (let i = 0; i < topK; i++) { 202 | topkValues[i] = valuesAndIndices[i].value 203 | topkIndices[i] = valuesAndIndices[i].index 204 | } 205 | 206 | const topClassesAndProbs = [] 207 | for (let i = 0; i < topkIndices.length; i++) { 208 | topClassesAndProbs.push({ 209 | class: node.modelManager.labels[topkIndices[i]], 210 | score: topkValues[i] 211 | }) 212 | } 213 | return topClassesAndProbs 214 | } 215 | 216 | /** 217 | * Post processes the outputs depending on the node configuration. 218 | * @param outputs 219 | * @returns a list of predictions 220 | */ 221 | async function postprocess (outputs) { 222 | const predictions = await getTopKClasses(outputs, node.modelManager.labels.length) 223 | 224 | const bestProbability = predictions[0].score.toFixed(2) * 100 225 | const bestPredictionText = bestProbability.toString() + '% - ' + predictions[0].class 226 | 227 | if (config.output === 'best') { 228 | node.status(nodeStatus.MODEL.RESULT(bestPredictionText)) 229 | return [predictions[0]] 230 | } else if (config.output === 'all') { 231 | let filteredPredictions = predictions 232 | filteredPredictions = config.activeThreshold ? filteredPredictions.filter(prediction => prediction.score > config.threshold / 100) : filteredPredictions 233 | filteredPredictions = config.activeMaxResults ? filteredPredictions.slice(0, config.maxResults) : filteredPredictions 234 | 235 | if (filteredPredictions.length > 0) { 236 | node.status(nodeStatus.MODEL.RESULT(bestPredictionText)) 237 | } else { 238 | const statusText = 'score < ' + config.threshold + '%' 239 | node.status(nodeStatus.MODEL.RESULT(statusText)) 240 | return [] 241 | } 242 | return filteredPredictions 243 | } 244 | } 245 | 246 | /* Main Node Logic */ 247 | 248 | nodeInit() 249 | 250 | node.on('input', async function (msg) { 251 | if (msg.reload) { await loadModel(config.modelUri); return } 252 | if (!node.modelManager.ready) { node.status(nodeStatus.ERROR('model not ready')); return } 253 | if (config.passThrough) { msg.image = msg.payload } 254 | const outputs = await inferImageBuffer(msg.payload) 255 | if (outputs === null) { node.status(nodeStatus.MODEL.READY); return } 256 | msg.payload = await postprocess(outputs) 257 | msg.classes = node.modelManager.labels 258 | node.send(msg) 259 | }) 260 | 261 | node.on('close', function () { 262 | node.status(nodeStatus.CLOSE) 263 | }) 264 | } 265 | RED.nodes.registerType('teachable machine', teachableMachine) 266 | } 267 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 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