Unlocking Text - OCR with Supervisely
Discover how to make the most of Optical Character Recognition (OCR) capabilities within Supervisely.
Table of Contents
Optical Character Recognition (OCR) is a transformative technology with applications spanning across diverse industries. It enables machines to recognize and convert printed or handwritten text from images into machine-encoded text.
In this blog post we'll explore what OCR is, its wide-ranging applications, and how Supervisely empowers users with an integrated OCR solution.
In our tutorial, we demonstrate how to:
Utilize MMOCR Inference app to acquire model predictions for text within images.
Modify tag values directly within the labeling interface or employ a specialized app Object tags editor for efficient tag management.
What is OCR?
OCR, or Optical Character Recognition, is a technology that converts printed or handwritten text into machine-readable text. It's a crucial tool in the digital age, allowing computers to recognize and extract text from images, scanned documents, or other visual sources. OCR software and systems use complex algorithms to analyze the shapes, patterns, and arrangements of characters within an image, translating them into editable and searchable text.
At its core, OCR technology bridges the gap between physical text and digital data. It's a sophisticated system that takes an image containing text, whether it's a scanned document, a photograph, or a screenshot, and converts the text within it into a machine-readable format. This technology has found a home in numerous industries, including:
- Document Management: OCR is a cornerstone in digitalizing paper-based documents. It allows organizations to quickly convert stacks of paperwork into searchable, editable, and easily retrievable digital files.
- Healthcare: OCR plays a vital role in digitizing patient records, prescription labels, and medical reports. It helps streamline healthcare processes and enhance patient care.
- Finance: In the financial sector, OCR is instrumental in automating data extraction from invoices, receipts, and financial documents. This speeds up financial operations and reduces errors.
- Legal: Legal professionals use OCR to efficiently scan and index legal documents, making them searchable and easily accessible.
- Retail: OCR enables inventory management, price tracking, and stock analysis by extracting data from shelf labels and product packaging.
- Education: OCR assists in converting textbooks and handwritten notes into digital formats, making learning materials accessible to a wider audience.
- Transportation and Logistics: OCR is used for reading package labels, sorting mail, and tracking shipments, ensuring efficient logistics operations.
OCR Integration in Supervisely: MMOCR toolbox
Supervisely team has integrated the powerful MMOCR library, a leading open-source OCR Toolbox. This integration brings the capability to harness the potential of OCR directly within the Supervisely platform.
MMOCR Toolbox is a powerful open-source toolbox designed for OCR and text extraction tasks. It serves as a comprehensive toolkit for researchers, developers, and data scientists working in the fields of computer vision, natural language processing, and document analysis.
MMOCR Toolbox provides a wide range of functionalities, including text detection and text recognition. It leverages state-of-the-art deep learning models, making it capable of handling various languages and fonts, and can be employed across numerous applications, such as digitizing documents, automating data entry, and aiding in content analysis.
Output of MMOCR
How to Use OCR in Supervisely
In the abovementioned video tutorial , we illustrate how to utilize the MMOCR Toolbox to obtain model predictions for text within images and efficiently manage associated tags. To reproduce this tutorial, you'll need to run the following two apps within the Supervisely Ecosystem:
MMOCR InferenceSupervisely App
Text Detection and Recognition on images
This app provides outputs including recognized text, bounding boxes and tags with values of the recognised text for efficient text analysis within images.
As evident from the results, the model's predictions exhibit a remarkable level of accuracy, which has the potential to significantly expedite the labeling process. This heightened precision can greatly enhance the efficiency and effectiveness of your labeling tasks.
Object tags editorSupervisely App
Object tags editor
Edit tags of each object on image
This application provides a convenient means to edit object tags within images. You can seamlessly iterate through images and objects within your dataset or project, streamlining the process of modifying tags to suit your specific needs.
Ready to unlock the power of OCR in Supervisely? Register on our community edition and experience the transformative capabilities for yourself for free here!
OCR is a game-changer in the digital era, offering a wide range of applications across industries. Supervisely's integration with MMOCR makes it accessible and user-friendly, empowering users to harness the full potential of OCR technology. With the ability to achieve high accuracy, efficiency, and customization, Supervisely's OCR solution is a valuable addition to any workflow.
Supervisely for Computer Vision
Supervisely is online and on-premise platform that helps researchers and companies to build computer vision solutions. We cover the entire development pipeline: from data labeling of images, videos and 3D to model training.
The big difference from other products is that Supervisely is built like an OS with countless Supervisely Apps — interactive web-tools running in your browser, yet powered by Python. This allows to integrate all those awesome open-source machine learning tools and neural networks, enhance them with user interface and let everyone run them with a single click.