Skip to content

Instantly share code, notes, and snippets.

View ilyaUsoltsev's full-sized avatar
🚴

Ilya Usoltsev ilyaUsoltsev

🚴
  • Zurich, Switzerland
View GitHub Profile
@mugifly
mugifly / image-predict-on-tfjs-node.js
Last active January 7, 2024 16:11
Image Prediction on tfjs-node (with model made by Teachable Machine Image)
const tf = require('@tensorflow/tfjs-node');
const Jimp = require('jimp');
// Directory path for model files (model.json, metadata.json, weights.bin)
// NOTE: It can be obtained from [Export Model] -> [Tensorflow.js] -> [Download my model]
// on https://teachablemachine.withgoogle.com/train/image
const MODEL_DIR_PATH = `${__dirname}`;
// Path for image file to predict class
const IMAGE_FILE_PATH = `${__dirname}/example.jpg`;
@sindresorhus
sindresorhus / writing-eslint-rule.md
Last active February 26, 2023 03:01
Gettings started writing a ESLint rule

Gettings started writing a ESLint rule

First, take a look at the ESLint rule documentation. Just skim it for now. It's very long and boring. You can come back to it later.

ESLint rules works on the AST (Abstract Syntax Tree) representation of the code. In short, this is a tree structure that describes the code in a very verbose form. ESLint walks this tree and rules can subscribe to be notified when it hits a specific node type, like a Literal type, which could be the "hello" part of const welcome = "hello";.

Go ahead and play around with some code in AST Explorer (Make sure the parser is espree). It's a great tool!

Here are some good articles on the subject (ignore the scaffolding parts):