ESP32-S3 Bench Guide
ESP32-S3 N16R8 bench guide: live pinout, lessons, simulators and the bench log.
Learn Hiragana and Katakana, practice handwriting with Apple Pencil, and study categorized Japanese vocabulary words.
EducationTypeScript · PythonGitHub @tnson0708OnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
No updates detected yet. GitHub releases will appear here.
Owners of public repositories under a personal GitHub account can sign in to verify ownership and manage the introduction themselves. No administrator approval is needed.
Sign in, generate a verification file, and commit it to this repository’s default branch within 30 minutes. Files on other branches or forks do not count. Then check the file below to manage the project without administrator approval. Keep the file to retain your access.
If needed, you will go to sign-in. After signing in, return here and press your chosen verification button again.
Run /nomorevibe verify in your project folder to verify ownership and manage the introduction yourself.
Verify in one minuteAsk about other verification options
The maker's introduction consists of the line above. Read the repository README for more details. Repository README ↗
Loading the full README.
Read the full README ↗A personal Hiragana/Katakana learning app, built for handwriting practice with an iPad and Apple Pencil.
Handwriting dictation (play a word, write it, get scored) is planned as a follow-up phase and will reuse the same stroke-scoring engine.
pnpm install
pnpm dev
Open http://localhost:3000.
To regenerate the bundled kana stroke dataset (src/data/kana-strokes.json) from KanjiVG:
node scripts/generate-kana-data.mjs
npx vercel
Or connect the repo at vercel.com/new — no environment variables are required, everything runs client-side against the bundled kana dataset.
Stroke order data is from KanjiVG by Ulrich Apel, licensed under CC BY-SA 3.0.