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After completing this lecture , the students will be able to read any image file on their computer and display it on a titled window on the screen.
This lecture introduces the 2 functions :
In this lecture the students learn how to convert a colour image into a gray image and write the gray image into a file on the computer for viewing later.
The following functions are introduced in this lecture :
In this lecture, the concept of channels is demystified. The 3 Channels of an RGB image are clearly explained and then the RGB image is decomposed into its constituent ( Red ,Green , & Blue ) channels respectively using the split() function. Next we merge the separate channels obtained using the merge() function, to reproduce the original image.
The key takeaways : To visualise that an RGB image (colour image) has 3 Channels , while a GrayscaleImage has just one channel.
This lecture introduces the concept of subplots and explains why they are so important. The video also explains the difference in conventions followed by matplotlib package and the cv2 library, when reading OR displaying an RGB image.
This video demonstrates, how to read and display a picture , from the provided url.
Histograms tell us a lot about an image. This lecture uses a grayscale picture as a sample and explains its histogram plot , detailing each aspect of the plot and the information it conveys.
After going through this lecture, the student will be more adept in analysing images solely based on its histograms.
This video will serve as an introduction for the Snipping utility project.
This fun project will help students experiment hands-on, utilising all the knowledge they have gained till this section.
In this video, the students will attempt to perform thresholding without using the cv2.threshold() function.
In this video the students will learn two superimpose one image on top of another image. This is a fun exercise , but the concept of this lesson is very important and is used in many applications.
Students can use this idea to make a photo watermarking tool in python.
This lecture contains a simple rudimentary code to have a nice trackbar to control the amount of superimposition of an image.
This is the introduction to the videos section. Students are taught, how to access the webcam using code, and how to release the webcam.
In this video we will learn how to change colourspaces in a live video feed using users choice of colourspace.
In this video we will show, how to track an object in realtime using the object's colour.
Shrobon is carrying his research in High Performance Computer Vision, and is well abreast with the latest developments in this field. Apart from computer vision, Shrobon has years of experience in developing system softwares, and working on embedded and web projects.
His growing interest in Computer Vision, Machine Learning and Medical imaging has led him to pursue a masters degree in Computing Science (specialization in multimedia) from University of Alberta, Canada. Prior to this, Shrobon completed his bachelors degree (B.Tech) in Computer Science & Engineering from West Bengal University of Technology, he where excelled as a student and contributed to several projects in domains of Computer Vision, Image Processing, Internet Of Things , and Cyber Security.
The quality of his research work, and his proficiency in articulating the very difficult concepts in a simple & easy to understand manner, makes him the instructor of choice where Computer Vision is concerned.