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About This Course

Who this course is for:

  • Those who want to dive into Optical Character Recognition, Image Recognition and Object Detection using Python without having to deal with all the complexities and mathematics associated with the typical Deep Learning process.

What you’ll learn: 

  • The techniques that enable computers to recognize and classify either a whole image or multiple objects inside a single image
  • To predict the class of the objects with the percentage accuracy score 
  • How to recognize and convert texts in images to machine readable format like text or a document

Requirements: 

  • No prior knowledge is required to take this course

Welcome to the third course from my Computer Vision series – Python Optical Character Recognition And Object Detection.

Image Recognition, Object Detection, Object Recognition and also Optical Character Recognition (OCR) are among the most used applications of Computer Vision.

These techniques enable computers to recognize and classify either a whole image or multiple objects inside a single image, predicting the class of the objects with the percentage accuracy score. Using OCR, computers can also recognize and convert texts in images to machine readable format like text or a document.

Object Detection and Object Recognition, on the other hand, are widely used not only in many simple applications but also complex ones like self driving cars.

This course will be a quick starter for people who want to dive into Optical Character Recognition, Image Recognition and Object Detection using Python without having to deal with all the complexities and mathematics associated with the typical Deep Learning process.

For those of you who may not be coming from a Python-based programming background, there are lectures which will help you get the basic Python programming skill to follow the course. 

The code, images, and libraries used are included inside this course. You are free to use them in your projects with no questions asked.

Our Promise to You

By the end of this course, you will have learned more about OCR and object detection.

30 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today and learn more about Computer Vision.

Course Curriculum

Section 1 - Introduction
Course Introduction And Table of Contents 00:00:00
Introduction To OCR Concepts 00:00:00
Setting Up The Environment – Anaconda 00:00:00
Downloadable Materials – Codes And Images 00:00:00
Section 2 - Python Basics
Python Basics – Part 1 – Assignment 00:00:00
Python Basics – Part 2 – Flow Control 00:00:00
Python Basics – Part 3 – Data Structures 00:00:00
Python Basics – Part 4 – Functions 00:00:00
Section 3 - Tesseract OCR Setup
Tesseract OCR Setup – Part 1 00:00:00
Tesseract OCR Setup – Part 2 00:00:00
OpenCV Setup 00:00:00
Tesseract Image OCR Implementation – Part 1 00:00:00
Tesseract Image OCR Implementation – Part 2 00:00:00
ImShow Not Responding Issue Fix 00:00:00
Section 4 - CNN - Convolutional Neural Networks
Introduction To CNN – Convolutional Neural Networks 00:00:00
Installing Additional Dependencies For CNN 00:00:00
Introduction To VGGNet Architecture 00:00:00
Image Recognition Using Pre-Trained VGGNet16 Model – Part 1 00:00:00
Image Recognition Using Pre-Trained VGGNet16 Model – Part 2 00:00:00
Image Recognition using Pre-Trained VGGNet19 Model 00:00:00
Image Recognition using Pre-Trained ResNet Model 00:00:00
Image Recognition using Pre-Trained Inception Model 00:00:00
Image Recognition using Pre-Trained Xception Model 00:00:00
Introduction to MobileNet-SSD Pretrained Model 00:00:00
Mobilenet SSD Object Detection – Part 1 00:00:00
Mobilenet SSD Object Detection – Part 2 00:00:00
Mobilenet SSD Realtime 00:00:00
Mobilenet SSD Video 00:00:00
Mask RCNN Introduction 00:00:00
MaskRCNN Box Implementation – Part 1 00:00:00
MaskRCNN Box Implementation – Part 2 00:00:00
MaskRCNN Mask Implementation – Part 1 00:00:00
MaskRCNN Mask Implementation – Part 2 00:00:00
MaskRCNN Realtime – Part 1 00:00:00
MaskRCNN Realtime – Part 2 00:00:00
MaskRCNN Video 00:00:00
YOLO Introduction 00:00:00
YOLO Implementation – Part 1 00:00:00
YOLO Implementation – Part 2 00:00:00
YOLO Realtime 00:00:00
YOLO Video 00:00:00
Tiny YOLO Video 00:00:00
Tiny Yolo Realtime 00:00:00
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