In this video we will explore how you can perform tasks like vehicle detection using a simple but yet an effective approach of background-foreground subtraction. You will be learning about using background-foreground subtraction along with contour detection in OpenCV and how you tune different parameters to achieve better results.
This video is the third and final part of our mini-series Contour Detection 101. Since we have already learned to detect and manipulate contours in previous parts, in this video, I’ve covered Contour Analysis which will make you capable of detecting and recognizing objects in images, and videos and build some interesting applications like Real-time Shape detection.
In our upcoming course named Building Applications with Contours in OpenCV, I am gonna teach you to build Computer Vision applications using the concepts you have learned in the mini-series. The course will be released soon on our site so stay tuned for it.
This video is part two of our mini-series Contour Detection 101. Detecting contours will not be enough to build contours based applications so, in this video, I’ve covered contours manipulations like extracting the largest contour, sorting contours according to their sizes, drawing rectangles and convex hulls around them and a lot more.
This mini-series is a part of our upcoming course named Building Vision Applications with Contours and OpenCV which will be released in a couple of weeks on our website.
This video is a part of our upcoming Building Vision Applications with Contours and OpenCV course. In this video, I’ve covered all the basics of contours you need to know. You will learn how to detect and visualize contours, the various image pre-processing techniques required before detecting contours, and a lot more.
The course will be released in a couple of weeks on our site and will contain quizzes, assignments, and walkthroughs of high-level Jupyter notebooks which will teach you a variety of concepts.