Computer Vision Bootcamp with Python (OpenCV) - YOLO, SSD

About this course

This course is about the fundamental concept of image processing, focusing on face detection and object detection. These topics are getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to crime investigation. Self-driving cars (for example lane detection approaches) relies heavily on computer vision. With the advent of deep learning and graphical processing units (GPUs) in the past decade it's become possible to run these algorithms even in real-time videos. So what are you going to learn in this course?

Section 1 - Image Processing Fundamentals:computer vision theorywhat are pixel intensity valuesconvolution and kernels (filters)blur kernelsharpen kerneledge detection in computer vision (edge detection kernel)Section 2 - Serf-Driving Cars and Lane Detectionhow to use computer vision approaches in lane detection

Canny's algorithmhow to use Hough transform to find lines based on pixel intensities

Section 3 - Face Detection with Viola-Jones Algorithm:

• Viola-Jones approach in computer visionwhat is sliding-windows approachdetecting faces in images and in videos

Section 4 - Histogram of Oriented Gradients (HOG) Algorithmhow to outperform Viola-Jones algorithm with better approacheshow to detects gradients and edges in an imageconstructing histograms of oriented gradientsusing support vector machines (SVMs) as underlying machine learning algorithms

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