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Data Sciences

Computer Vision with OpenCV-Master Class

ratings 

In this course you will understand about computer vision and will learn about its various applications across many industries. It helps in high-level understanding.

PRIVATE
Course Access

Unlimited Duration

Last Updated

July 29, 2021

Students Enrolled

20

Total Reviews

Posted by

Ernesto Lee

Certification

OpenCV has been a vital part in the development of software for a long time. It is closely linked with artificial intelligence as the computer must interpret what it sees and must act accordingly. Computer Vision is considered to be the important field in the era of Artificial intelligence. It is making great advances in self-driving cars, robotics, face detection etc. It is an scientific field that deals with how computers can be made to gain high-level understanding from digital images or videos. Computer vision is a field of deep learning that allows the machine to identify and process images just like humans do then provide appropriate output and a computer should be able to recognize objects like the face of a human being or even a statue.  It a rapidly expanding area and it is becoming very easy for developers to make use of this field.  

Course Curriculum

    • Loading, Displaying and Saving Images 00:00:00
    • Image Basics 00:00:00
    • Drawing 00:00:00
    • Hands on Practical Implementation 00:00:00
    • Translation 00:00:00
    • Rotation 00:00:00
    • Resizing 00:00:00
    • Flipping 00:00:00
    • Cropping 00:00:00
    • Hands on Practical Implementation 00:00:00
    • Image Arithmetic 00:00:00
    • Bitwise Operations 00:00:00
    • Masking 00:00:00
    • Splitting and Merging Channels 00:00:00
    • Hands on Practical Implementation 00:00:00
    • What are kernels 00:00:00
    • Morphological Operations 00:00:00
    • Smoothing and blurring 00:00:00
    • Lighting and color spaces 00:00:00
    • Thresholding 00:00:00
    • Gradients 00:00:00
    • Edge Detection 00:00:00
    • Hands on Practical Implementation 00:00:00
    • Finding and Drawing Contours 00:00:00
    • Simple Contour Properties 00:00:00
    • Advance Contour Properties 00:00:00
    • Contour Approximation 00:00:00
    • Sorting Contours 00:00:00
    • Hands on Practical Implementation 00:00:00
    • What is Histogram 00:00:00
    • Computer Histograms using OpenCV 00:00:00
    • Grayscale Histograms 00:00:00
    • Color Histograms 00:00:00
    • Histogram Equalization 00:00:00
    • Histograms and Masks 00:00:00
    • Hands on Practical Implementation 00:00:00
    • The classical approach 00:00:00
    • The first pass 00:00:00
    • The second pass 00:00:00
    • Applying connected-component analysis on Number plate images 00:00:00
    • Hands on Practical Implementation 00:00:00
    • What are image descriptors, feature descriptors, feature vectors? 00:00:00
    • Local Binary Patterns 00:00:00
    • Histogram of Oriented Gradients 00:00:00
    • Understanding local features 00:00:00
    • Local Invariant descriptors 00:00:00
    • Hands on Practical Implementation 00:00:00
    • What are binary descriptors 00:00:00
    • BRIEF 00:00:00
    • ORB 00:00:00
    • BRISK 00:00:00
    • FREAK 00:00:00
    • Binary feature extraction and matching 00:00:00
    • Hands on Practical Implementation 00:00:00
    • Face detection in images 00:00:00
    • Face detection in video 00:00:00
    • Hands on Practical Implementation 00:00:00

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