What you'll learn:
Understand the Image Basics and apply it for Image Processing
Learn to implement OCR - Text Detection with OpenCV and Deep Learning Models
Use Tesseract and EasyOCR to implement OCR - Text Recognition
Work with OCR - Text Labelling using Spacy and Regular Expression
Use OpenCV and Tesseract to apply Noise Removal Techniques including Thresholding, Rescaling, Dilation, Erosion and Deskewing
Executable Code of CTPN and EAST Model implementation for Text Detection and Text Recognition
Build OCR Solutions for Invoice Processing, Vehicle Nameplate, Business Card Recognition and KYC Digitization
A quick starter on OCR Architecture, Commercial Solutions and Use Cases in Industry

Requirements
Basic Programming skills in Python

Description
**** This course is a quick starter for people who would like to become Computer Vision - Optical Character Recognition (OCR) Specialist ****

Optical Character Recognition commonly called as OCR is the new buzzword in industry which is driving digitization in the enterprises. Every enterprise wants to adopt OCR to achieve easier and quicker access to their streams of data in digital format. An OCR implementation not only speed up the workflow of Text processes across various industries but also help in providing better customer experience. In fact, as per a recent research report, OCR market which was around 7.2 billion US Dollar is expected to see a huge growth in market size and will reach 13.4 billion US dollar by 2025.

Enroll in this course to get a complete understanding of Optical Character Recognition (OCR) for Data Extraction from Images and PDF using Python. The course explains the theory of concepts followed by code demonstration to make you an expert in computer vision OCR. It provides hands-on guidance on Text Detection with OpenCV and Deep Learning Models, Text Recognition with Tesseract and OCR along with Text Labelling through Spacy and Regular Expression. It guides you to create technical solutions on most relevant OCR uses cases in the industry

Here are just few of the topics we will be learning:

OCR Architecture

Pixels and Image Basics

Kernel and Feature Map

Preprocessing Techniques (Binarisation, Thresholding, Rescaling)

Noise Removal Techniques (Morphology, Dilation, Erosion, Blurring, Orientation, Deskewing, Borders, Perspective Transformation)

EasyOCR

PyTesseract Operations

Tesseract

Named Entity Recognition

Regular Expression for Text and Dates

CTPN Model for Text Detection & Text Recognition

EAST Model for Text Detection & Text Recognition

Invoice Processing OCR Solution with python code

Invoice Structured Output in XML Format Solution with python code

Vehicle Nameplate OCR Solution with python code

Business Card Recognition OCR Solution with python code

KYC Digitization OCR Solution with python code

Who this course is for
Beginners to Computer Vision
OCR Engineer
OCR Specialist
Machine Learning Professionals
Anyone looking to become more employable as a Computer Vision Expert

Citación :

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