使用 Core ML 與 dots.ocr 實現 Apple 平台上的 SOTA 本地端 OCR
Original: SOTA OCR with Core ML and dots.ocr
This technical article from Hugging Face introduces how to deploy a state-of-the-art (SOTA) optical character recognition (OCR) model…
本文介紹了 dots.ocr 模型與 Apple Core ML 框架的結合。透過將 SOTA 等級的 OCR 模型轉換為 Core ML 格式，開發者可以在 iPhone、iPad 和 Mac 上實現高效能的本地端文字辨識。這不僅大幅降低了延遲，還能完全在裝置端運行以保護用戶隱私，是 iOS 與 macOS 開發者整合 AI 視覺功能的新利器。
This technical article from Hugging Face introduces how to deploy a state-of-the-art (SOTA) optical character recognition (OCR) model called dots.ocr using Apple's Core ML framework.
Free shows the 3-line summary; Pro unlocks the full deep summary (~300 words) so you never have to click through.
See Pro plans →Want the original English / full article?
Read on Hugging Face Blog →Summaries are AI-generated; the original article is authoritative.