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This article will discuss my approach to creating an OCR pipeline, which can be vital to your machine-learning system.

11 min read12 hours ago

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Due to the importance of textual information, an OCR pipeline is critical for many machine-learning systems. The text extracted using an OCR engine can be used for various purposes, like document classification or in an RAG system. The output quality from the OCR is critical for the performance of the machine learning models on downstream tasks, which is why this article will discuss how to create a high-quality OCR pipeline.

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Learn how you can develop an OCR pipeline. Image by ChatGPT. “can you make a similar image but avoid having text in the image” prompt. ChatGPT, 4, OpenAI, 14 Mar. 2024. https://chat.openai.com.

Motivation

My motivation for this article is that I am developing an app that can take images of receipts, extract useful information from them, and deliver value to the consumer. Implementing OCR for this purpose poses a variety of problems, however, which I have spent countless hours researching and solving. I am therefore writing this article to explain how I approached the problem and to provide essential notes to keep in mind when developing the OCR pipeline.

This article will follow a series of steps in developing the OCR pipeline. First, we will look into the data you are working on. The data type will significantly impact…