Python and OpenCV for Computer Vision – Quick Starter

Learn Python coding language and OpenCV algorithms to build your own Computer Vision and Deep Learning Solutions

This is the best course to quickly grasp the knowledge of Python and OpenCV and become proficient to design Computer Vision and Deep Learning solutions.

What you’ll learn

  • Learn Python for practical usage to build your solutions and become expert.
  • Understand Python with Data Types, Operators, Loops, Functions, Modules, File Handling along with best coding practices.
  • Work with Advanced Python concepts – Lambda, Object Oriented Programming, Decorator and Generator.
  • Learn to use Built-in Libraries of Python – DateTime, Math, Random, Statistics, Sys, OS.
  • Build expertise on Numpy, Pandas, Matplotlib and OpenPyXL.
  • Understand the basics of OpenCV to work on images and videos.
  • Use OpenCV to apply Simple Thresholding, Adaptive Thresholding and Otsu’s Binarization.
  • Work with Noise Removal techniques including Morphological Operations, Small Dots and Noise, Image Blurring, Dilation and Erosion.
  • Become proficient in Image Cropping & Rotation, Image Annotation and Image Detection.
  • Learn how to use OpenCV for LIVE webcam and recorded video.
  • Build Python Solutions for Web Scraping, Sending Email using Flask App and Text Extraction from PDF Document.
  • Build OpenCV Solutions for Template Matching and Tracking Object by Marking in LIVE Camera.

Course Content

  • Course Starter –> 1 lecture • 6min.
  • Introduction to Python –> 4 lectures • 10min.
  • Python Setup –> 4 lectures • 19min.
  • Data Types and Operators –> 9 lectures • 1hr 17min.
  • Loops – If-Else, For, While –> 3 lectures • 17min.
  • Functions, Modules & File Handling –> 4 lectures • 30min.
  • Popular Coding Practices and Exception Handling –> 3 lectures • 13min.
  • Advanced Functions – Lambda, Map, Filter, Reuse –> 2 lectures • 10min.
  • Object Oriented Programming, Decorator and Generator –> 5 lectures • 28min.
  • Built-in Modules – DateTime, Math, Random, Statistics, Sys, OS –> 4 lectures • 18min.
  • External Libraries – Numpy, Pandas, Matplotlib, OpenPyXL –> 5 lectures • 51min.
  • Introduction to OpenCV –> 6 lectures • 19min.
  • Image Thresholding –> 2 lectures • 7min.
  • Image Noise Removal –> 2 lectures • 14min.
  • Image Cropping & Rotation Techniques –> 2 lectures • 5min.
  • Image Annotation –> 2 lectures • 6min.
  • Image Detection Techniques –> 2 lectures • 15min.
  • OpenCV for Videos –> 2 lectures • 10min.
  • LIVE Projects –> 5 lectures • 40min.
  • More Learnings –> 1 lecture • 3min.

Python and OpenCV for Computer Vision - Quick Starter

Requirements

  • Basic understanding of computer science.

This is the best course to quickly grasp the knowledge of Python and OpenCV and become proficient to design Computer Vision and Deep Learning solutions.

With the AI-fueled organization trend getting momentum, the industry is in dire need of Computer Vision experts who are proficient in Python and OpenCV. This course has been designed to start with the basics of Python coding language comprising of Data Types, Operators, Loops, Functions, Modules, File Handling, Exception Handling along with Popular Coding Practices and then slowly take you through the advanced Python concepts such as Lambda, Map, Filter, Object Oriented Programming, Decorator, Generator, DateTime, Math, Random, Statistics, Sys, OS, Numpy, Pandas, Matplotlib and OpenPyXL in detail.

Not only this, the course takes it one step further by providing comprehensive coverage of OpenCV topics including Image Thresholding, Image Noise Removal, Image Cropping & Rotation, Image Annotation, Image Detection and also OpenCV for Videos with 35+ supporting notebooks available for download that contain examples for practice. The quiz at the end of each key topic helps you to assess your knowledge and identify the improvement areas. In addition to this, the 5 LIVE projects towards the end of course are the most sought-after computer vision solutions in industry right now on which you get a detailed code walkthrough along with downloadable source code.

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

· Python and OpenCV Setup

· Python Data Types & Operators

· Python Loops – For, While, If-Else

· Python – Functions, Modules & File Handling

· Popular Coding Practices and Exception Handling

· Advanced Functions – Lambda, Map, Filter, Reuse

· Object Oriented Programming, Decorator and Generator

· Built-in Modules – DateTime, Math, Random, Statistics, Sys, OS

· External Libraries – Numpy, Pandas, Matplotlib, OpenPyXL

· Image Thresholding – Simple, Adaptive and Otsu’s Binarization

· Noise Removal Techniques – Morphological Operations, Small Dots and Noise, Image Blurring, Dilation, Erosion and Kernels for Image Processing

· Image Cropping & Rotation

· Image Annotation – Draw text, rectangle, circle and line on image

· Image Detection – Blob, Edge and Contour Detection

· OpenCV – Reading from a Recorded Video

· OpenCV – Reading and Writing from LIVE camera

· Python Web Scraping using BeautifulSoup and RegEx Solution

· Sending Email with Python (Flask) Solution

· Extract text from PDF using Python Solution

· Template matching using OpenCV Solution

· Track Object by Marking in Live Camera using OpenCV Solution

 

Enroll in this course and become a Computer Vision expert !!