Extract text from images and PDFs using Surya with Python APIs and CLI.
npx skills add https://github.com/aktsmm/Agent-Skills --skill ocr-super-surya
Please help me install this Agent Skill. Skill: ocr-super-surya Source: https://github.com/aktsmm/Agent-Skills/tree/main/ocr-super-surya Command: npx skills add https://github.com/aktsmm/Agent-Skills --skill ocr-super-surya
OCR Super Surya streamlines text extraction from images and PDFs by leveraging Surya's GPU-accelerated OCR, enabling fast, accurate digitization of documents.
Install surya-ocr and dependencies, then run ocr_image, ocr_pdf, or ocr_batch on your documents. Example: ocr_image('invoice.png') or ocr_pdf('report.pdf').
High-intent search queries and answers about installing and using this skill.
To extract text from scanned PDFs and images in multiple languages, you can use Surya's GPU-accelerated OCR. It supports 90+ languages and processes mixed documents using Python APIs or a CLI.
Yes, GPU OCR with Surya requires PyTorch with CUDA support for GPU-accelerated inference. You also need the Surya library and optionally pypdfium2 for PDF handling.
Yes, you can run batch processing for high-resolution image to text extraction using the ocr_batch API. PyTorch and CUDA optimizations handle large batches efficiently.
The best way to convert scanned invoices into searchable text is using Surya OCR. It achieves roughly 2x accuracy over traditional OCR tools across 90+ languages, digitizing documents for structured data analytics.
Multi-language OCR handles Japanese text extraction from images with high accuracy using Surya. It is specifically noted for strong performance across 90+ languages, including complex scripts like Japanese.
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