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Optical Character Recognition (OCR) MasterClass in Python

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1: Optical Character Recognition (OCR) MasterClass in Python

Learn OCR in Python using OpenCV, Pytesseract, Pillow and Machine Learning

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Welcome to Course "Optical Character Recognition (OCR) MasterClass in Python" 

Optical character recognition (OCR) technology is a business solution for automating data extraction from printed or written text from a scanned document or image file and then converting the text into a machine-readable form to be used for data processing like editing or searching.

BENEFITS OF OCR:

  • Reduce costs

  • Accelerate workflows

  • Automate document routing and content processing

  • Centralize and secure data (no fires, break-ins or documents lost in the back vaults)

  • Improve service by ensuring employees have the most up-to-date and accurate information

Some Key Learning Outcomes of this course are:

  • Recognition of text from images using OpenCV and Pytesseract.

  • Learn to work with Image data and manipulate it using Pillow Library in Python.

  • Build Projects like License Plate Detection, Extracting Dates and other important information from images using the concepts discussed in this course.

  • Learn how Machine Learning can be useful in certain OCR problems.

  • This course covers basic fundamentals of Machine Learning required for getting accurate OCR results.

  • Build Machine Learning models with text recognition accuracy of above 90%.

  • You will learn about different image preprocessing techniques such as grayscaling, binarization, erosion, dilation etc... which will help to improve the image quality for better OCR results.

Optical Character Recognition (OCR) MasterClass in Python | Udemy

Who this course is for:

  • Python developers who are curious about Optical Character Recognition (OCR).
  • People from Data Science and Machine Learning background who want add a new skill of OCR in their resume.
  • Anyone who wants to learn about OCR.

What you'll learn

Learn about Pillow Library in Python which is used for working with image data and perform various image manipulation steps.
OpenCV for image preprocessing in Python.
Learn about Pytesseract which is an Optical Character Recognition (OCR) tool for python. It will read and recognize the text in images, license plates, etc.
You will learn to use Machine Learning for different OCR use cases and build ML models that perform OCR with over 90% accuracy.
Build different OCR projects like License Plate Detection, Reading text from images etc...

Requirements

Basic understanding of Python Programming Language.

Optical Character Recognition (OCR) with Document AI (Python)
  1. Overview.
  2. Setup and Requirements.
  3. Enable the Document AI API.
  4. Create and Test a Processor.
  5. Authenticate API requests.
  6. Install the client library.
  7. Download the Sample PDF.
  8. Make an Online Processing Request.

Optical Character Recognition (OCR) MasterClass in Python | Udemy

Python OCR is a technology that recognizes and pulls out text in images like scanned documents and photos using Python. It can be completed using the open-source OCR engine Tesseract. We can do this in Python using a few lines of code. One of the most common OCR tools that are used is the Tesseract

Optical Character Recognition (OCR) is the process that converts an image of text into a machine-readable text format. For example, if you scan a form or a receipt, your computer saves the scan as an image file. You cannot use a text editor to edit, search, or count the words in the image file.

Tesseract can be called in python by installing its python wrapper called “pytesseract” using pip. The command goes like - 'pip install pytesseract'. This can be used with OpenCV in python to read images, perform operations, and display outputs.

Building your own Attention OCR model
  1. Gather annotated training data.
  2. Get crops for each frame of each video where the number plates are.
  3. Generate tfrecords for all the cropped files.
  4. Place them in models/research/attention_ocr/python/datasets as required (in the FSNS dataset format). ...
  5. Train the model using Attention OCR.

Pytesseract or Python-tesseract is an OCR tool for python that also serves as a wrapper for the Tesseract-OCR Engine. It can read and recognize text in images and is commonly used in python ocr image to text use cases.

Optical Character Recognition (OCR) MasterClass in Python | Udemy

11 OCR Libraries and Projects
  • 1- Tesseract. Tesseract is a free open-source OCR engine for building OCR apps. ...
  • 2- EasyOCR. ...
  • 3- Kraken. ...
  • 4- Ocrd. ...
  • 5- GOCR. ...
  • 6- Ocular. ...
  • 7- Attention-based OCR. ...
  • 8- Calamari OCR.

Not only is Python an easy (and forgiving) language to code in, but it's also used by many computer vision and deep learning practitioners, lending itself nicely to OCR.

The OpenCV OCR function stands for optical character recognition, which is designed to read an image file provided by the user and then recognize the text given within the image to be displayed to the user.

Optical Character Recognition (OCR) is the process of detecting and reading text in images through computer vision. Detection of text from document images enables Natural Language Processing algorithms to decipher the text and make sense of what the document conveys.

INSTRUCTOR
Raj Chhabria

Online Course CoupoNED based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.