Thread

1. postalcoder · 1791122276 · focus · HN ↗

   Since this is for the mac you really should be using apple's vision framework for OCR. It smokes tesseract in both speed and accuracy.

   Edit: I'm curious which LLM was used to generate the code. I fed the title of your post to claude/deepseek/qwen/codex asking to recommend a stack for this project, expecting to frown thinking that they still recommend tesseract. However, I found that they all recommend apple's vision framework. In fact the latest model to recommend Tesseract is gpt-4.1.

   1. allenleee · 1791128537 · focus · HN ↗

      Hey author here! :) Great point.

      You're totally right. Apple Vision is generally way faster and more accurate on Apple Silicon. Pure Mac-only, I'd use it. (also smaller)

      Main reason I went Tesseract: I want SCM to stay portable easily. It's ARM Mac for now, but the inference layer is all JS end-to-end — Transformers.js + ONNX for CLIP/SigLIP + Whisper, Tesseract.js WASM for OCR, all in plain Node workers.

      A bit of background: I'm actually an iOS/macOS dev and I really love SwiftUI and AppKit — I just wanted v1 to stay portable by construction. Exploring a native Swift + MLX v2 track separately for speed.

      1. novok · 1791144145 · focus · HN ↗

         If you look at the apple photos db you'll see that there is a bunch of cached pre-analysis you can leverage for items in apple photos.

         1. allenleee · 1791179257 · focus · HN ↗

            thanks for this! will do some research on it

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