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This tutorial provides a practical guide to deploying Baidu's Unlimited-OCR model within an end-to-end pipeline capable of handling high-resolution documents and multi-page PDFs. It details specific configurations for balancing inference speed against recognition accuracy on dense layouts, offering actionable insights for engineers integrating advanced vision-language models into document processing workflows.

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How to Build an End-to-End OCR Pipeline with Baidu’s Unlimited-OCR for High-Resolution Images and Multi-Page PDF Parsing

MarkTechPostJuly 24, 20264 min read

In this tutorial, we build a complete workflow for running Baidu’s Unlimited-OCR model on document images and multi-page PDFs. From configuring the GPU environment to comparing high-detail tiled Gundam inference and faster Base modes, you'll learn how to process dense layouts, tables, and cross-page content in a reproducible, end-to-end pipeline. The post How to Build an End-to-End OCR Pipeline with Baidu’s Unlimited-OCR for High-Resolution Images and Multi-Page PDF Parsing appeared first on MarkTechPost.

In this tutorial, we build a complete workflow for running Baidu’s Unlimited-OCR model on document images and multi-page PDFs. We configure the GPU environment, install the required dependencies, load the 3B-parameter vision-language model with automatic selection of bfloat16 or float16, and generate structured sample documents for testing. We then evaluate both the tiled Gundam inference mode and the faster…

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