Learn how to Use Webcam for real time Image Processing.
No Prerequisites. As python Crash Course is also embedded in the course.
Just need dedication to learn.
Welcome to the Complete Computer Vision Bootcamp Course With OpenCv Python 2020.
Highest Rated Course
This Course is will teach you Computer Vision and Image Processing Techniques From Basic to Advance Level.
This Course Provide all high quality content to learn and become Industry level Expert. We worked Really hard to explain the concepts of Computer Vision and Image Processing and the necessary mathematics behind each concept. You will get a Clear Idea about how computer understand and work with images and video Data.
We will Start with a Short Python course where you will learn to code in python and will have clear understanding of python syntax and some advance concepts like python generators along with Object Oriented Programming. So Even if Your are a complete Beginner, you are going to learn everything provided in this course.
After python Crash Course we will start with numpy and images basics, there we will learn how to read images as numpy array and to manipulate images with numpy.
Then we will move on to Image basics with openCV, there you willl learn how to open, create and to draw on the created blank image.
After that you will learn
Image Processing Techniques Using OpenCv like: Color Mapping, Image Blending, Image Thresholding, Morphology, Real Time Edge Detection Using Webcam and OpenCv in Python.
Then We will Make a Project which is in demand and you can directly put it in your resume.
Overall After Completing This Course You will be Expert in Computer Vision and Image Processing.
Who this course is for:
Beginner at Computer Vision. And want to learn advance concepts in Computer Vision.
Beginner at OpenCV. And want to learn advance concepts in OpenCV with Python.
Beginner in Image Processing. And want to learn advance concepts of Image Processing using Python.
Download 2021 Complete Computer Vision Bootcamp, Zero-Hero in Python™ from below links NOW!
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