mateogianolio/ocr
Neural network OCR. observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4194
- days_rel: n/a
- days_push: 3709
- n_releases_24m: 0
Adoption not part of the score
1132 stars · 94 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A JavaScript library that trains a multi-layer perceptron neural network to perform optical character recognition on digits and characters. Training data is auto-generated from captchas or sourced from the MNIST handwritten digit database, and the trained network is exported as a standalone module.
Use cases
- recognize handwritten digits with a neural network
- train an OCR model in JavaScript
- classify characters from binary pixel arrays
- experiment with MNIST digit classification
- generate a standalone OCR prediction module
- learn how neural networks do character recognition
When to choose
- you want a small, dependency-light neural network OCR example in Node.js
- you need to train a simple MLP on MNIST or captcha-generated glyphs
- you want a trained model exported as a standalone require-able module
When to avoid
- you need production-grade OCR for documents or complex layouts
- you want actively maintained software or modern deep learning frameworks
- you need support for full alphabets, fonts, or image preprocessing pipelines
Facets
library · maturity abandoned
ocr machine-learning deep-learning machine-learning computer-vision image-processing cross-platform neural-network mlp mnist captcha character-recognition nodejs
1 source
- readme: https://github.com/mateogianolio/ocr · fetched 2026-08-28 · 9abb07549414
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| mateogianolio/ocr | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="mateogianolio/ocr")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem