Mastering OCR using Deep Learning and OpenCV-Python

[mitsumi]

Mastering OCR using Deep Learning and OpenCV-Python
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 23 lectures (2h 27m) | Size: 770.2 MB
A complete guide to optical character recognition pipeline using Deep Learning, python and OpenCV

What you'll learn:
What is Optical Character Recognition (OCR)?
A general OCR pipeline used by most industries.
Different Image Pre-processing techniques used in OCR pipeline.
Different Text Detection techniques used in OCR pipeline such as EAST and CTPN.
Different Text Recognition techniques used in OCR pipeline such as CRNN (CNN+RNN+CTC)
Implementing OCR on real-life examples

Requirements
A little knowledge about OpenCV-Python and Deep Learning is sufficient.

Description
Hi There!

Welcome to the course 'Mastering OCR using Deep Learning and OpenCV-Python'. This is the first course of my OCR series.

In this course we will start from the very basics. We will first discuss what is Optical Character Recognition and why you should invest your time in learning this.

Then we                                                                                                                                                                                                          will move to the general pipeline used by most of the OCR systems available.

After this we will start learning each pipeline component in detail. We will start by learning some image pre-processing techniques commonly used in OCR systems.

Then we will learn some deep learning based text detection algorithms such as EAST and CTPN. We will also implement the EAST algorithm using OpenCV-Python.

Next we will learn the crux of the CTC which is widely used in developing text recognition systems. We will implement very famous text recognition algorithm that is CRNN.

Finally we will learn the last component of the OCR pipeline that is restructuring. In this we will discuss why is restructuring important for any OCR systems.

We will also discuss an open source end-to-end OCR engine which is pytesseract.

Finally we will run the complete OCR pipeline to extract the data from identification document using pytesseract.

So that's all for this course, see you soon in the class room. Happy learning and have a great time.

Stay safe, stay healthy.

Who this course is for
People who have no experience with OCR and wants to learn about it.
People who have little experience of OCR and wants to master it.
People who want to make their career in OCR field.

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