Published 11/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.04 GB | Duration: 4h 6m
Using Python Learn Computer Vision Course on OpenCV in Python from Basic to Advance
What you’ll learn
Images and Video read in Python using OpenCV.
Resizing, Cropping of images and videos in Python using OpenCV.
Draw shapes on images such as circle, rectangle, ellipse, line.
Adding text message on images.
Hide a portion of images using XOR, NOT and AND operation.
Image manipulation such as smoothing, blurring.
Read different type of images with (single channel, 3 channel, 4 channel images).
Image splitting
Saving Images and Videos files using OpenCV on our PC.
Color conversation of images (BGR to gray), (BGR to RGB).
Reading images from different package using PILLOW.
Most important: contour and its properties for analyzing the shape of the object in an image.
Detect line on the image with canny algorithm.
Feature detection on images and matching between the images.
Common problem student face while working on OpenCV.
Requirements
Basic understanding of Python Language.
Windows or MacOS or Ubuntu machine.
Description
Welcome to the OpenCV course. If you are interested in the field of Computer Vision or Deep Learning? Then this course is for you. Nowadays, Computer Vision is used in Automation in every domain such as self-driving cars, warehouses, security, object tracking, feature matching, and many more. Moreover, in this course, we are covering the basic to advance level core concepts for image and video processing. We have taken a practical approach to explain the core concept of image and video processing. This course is best for students who want to start their career as Computer Vision Engineer.We have divided this course into Chapters. In each chapter, you will learn the core concept of Image And Video Processing. These are some of the topics that we will be covering in this course:Image ReadImage CropImage ResizedImage RotateImage SplitImage SaveVideo ReadVideo ResizingVideo SaveDraw a Circle on the ImageAdding Text Messages to ImagesDraw Line Segment on ImageDraw a Rectangle on the ImageDraw an Ellipse on the ImageArithmetic OperationImage BlendingThreshold and BlurringArea and Perimeter of ContoursFind Contours in an ImageFitting Shape on the ContoursCheckpoint if inside, outside, or on the ContoursSIFT – (Scale – Invariant Feature Transform)Feature Matching and much more! Feel free to message me on the Udemy Q&A board, if you have any queries about the course! Thanks for checking the course page, and I hope to see you in my Course!!!Pooja
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 What is OpenCV ?
Lecture 3 Getting Setup for Course
Lecture 4 what is Image and Type of Imgaes ?
Section 2: OpenCV – Image Operation
Lecture 5 Image Read
Lecture 6 Image Crop
Lecture 7 Image Resized
Lecture 8 Image Rotate
Lecture 9 Image Split
Lecture 10 Image Save
Section 3: OpenCV – Video Operation
Lecture 11 Video Read
Lecture 12 Video Resized
Lecture 13 Video Save
Section 4: OpenCV – Draw Shape
Lecture 14 Draw Circle
Lecture 15 Adding Text Message
Lecture 16 Draw Line Segment
Lecture 17 Draw Rectangle
Lecture 18 Draw Eclipse
Section 5: OpenCV – Arithmetic Operation
Lecture 19 Not Arithmetic Operation
Lecture 20 AND Arithmetic Operation
Lecture 21 OR Arithmetic Operation
Lecture 22 Image Blending
Section 6: OpenCV – Threshold and Blurring
Lecture 23 Global Threshold
Lecture 24 Adaptive Thresholding
Lecture 25 Canny Edge Detection
Lecture 26 Image Blurring
Section 7: OpenCV – Contours and its Properties
Lecture 27 Area And Perimeter of Counters
Lecture 28 Find Contours in an Image
Lecture 29 Fitting Shape on the Contours
Lecture 30 Check Point if Inside, Outside or on the Contours
Section 8: OpenCV – Image feature and Matcher
Lecture 31 SIFT – (Scale-Invariant Feature Transform)
Lecture 32 Feature Matching
Section 9: OpenCV – Common Problem
Lecture 33 Save Images From Videos
Lecture 34 Make Video From Images
Lecture 35 Image from Pillow to OpenCV
Section 10: Conclusion
Lecture 36 Thank You
Python developer who is interested in Computer Vision and Deep Learning to learn how image and video processing is done using OpenCV.
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