Computer Vision - OCR using Python - Become a Computer Vision expert and learn optical character recognition - OCR using Tesseract, OpenCV and Deep Learning
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Description
** A comprehensive course for people who would like to become Computer Vision - Optical Character Recognition (OCR) Specialist. This course contains 33 downloadable Source Code Resources and Projects on Invoice Processing, KYC Digitization, Business Card Recognition and Automatic Number Plate Recognition **
Top 3 Reasons on why this course Computer Vision: OCR using Python stands-out among other courses:
· Inclusion of 5 in-demand projects of Computer Vision that have been explained through detailed code walkthrough and work seamlessly
· Dedicated In-Course Support is provided within 24 hours for any issues faced
· Comprehensive Coverage inclusive of theory and practical implementation of 2 Deep learning-based Text Detection models (CTPN and EAST)
Optical Character Recognition commonly called as OCR is the new buzzword in Artificial Intelligence 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 where we are using OCR to convert image to text.
Here are just few of the topics we will be learning:
· OCR Architecture
· Text Detection from Image
· Text Recognition from Image
· Pixels and Image Basics
· Image Properties
· Kernel and Feature Map
· Preprocessing Techniques (Binarisation, Thresholding, Rescaling)
· Noise Removal Techniques (Morphology, Dilation, Erosion, Blurring, Orientation, Deskewing, Borders, Perspective Transformation)
· Image Segmentation
· EasyOCR
· PyTesseract Operations
· Tesseract
· Named Entity Recognition
· Spacy for Named Entity Recognition
· Regular Expression for Text and Dates
· Training of CTPN and EAST Deep Learning Model on SIROE Dataset
· 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
