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Train your own OCR models with NanoNets API.

Extract text from image by building a custom Nanonets OCR model.

Extract text from image using Nanonets pre trained OCR models.

Here are three ways in which you can use Nanonets OCR to detect and extract text from images, extract text from PDFs, extract data from PDFs or parse PDFs and other document types: Table of Contents Extracting text from an image using Nanonets Captured data can be presented as tables, line items, or any other format.

Nanonets is the only text recognition OCR that presents extracted text in neatly structured formats that are entirely customizable. Nanonets extracts data from images accurately, at scale, and in multiple languages. An AI-driven OCR like Nanonets can pull text from images and present the extracted data in a neat, organized & structured manner. While such tools do a good job, the extracted text/data is often presented in an unstructured manner that results in a lot of post processing. ( What is OCR? - here's a detailed explainer on OCR) And online converters like Workbench or img2text also extract text from images with OCR.

Tools like Snagit & OneNote among others, leverage basic OCR capabilities to extract text from images. Image to text converters, often in-built as a sub-feature in image/document processing programs, offer a neat way to extract text from images. Most people just retype the text/data from the image but this is both time-consuming and inefficient when you have a lot of images to deal with.

Extracting text from an image can be a cumbersome process.