OpenCV with Python (Computer Vision)

OpenCV with Python (Computer Vision), available at $79.99, has an average rating of 4.35, with 36 lectures, based on 63 reviews, and has 280 subscribers.

You will learn about Images, 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. This course is ideal for individuals who are Python developer who is interested in Computer Vision and Deep Learning to learn how image and video processing is done using OpenCV. It is particularly useful for 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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Summary

Title: OpenCV with Python (Computer Vision)

Price: $79.99

Average Rating: 4.35

Number of Lectures: 36

Number of Published Lectures: 36

Number of Curriculum Items: 36

Number of Published Curriculum Objects: 36

Original Price: ?799

Quality Status: approved

Status: Live

What You Will Learn

Images, 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.

Who Should Attend

Python developer who is interested in Computer Vision and Deep Learning to learn how image and video processing is done using OpenCV.

Target Audiences

Python developer who is interested in Computer Vision and Deep Learning to learn how image and video processing is done using OpenCV.

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 Read

Image Crop

Image Resized

Image Rotate

Image Split

Image Save

Video Read

Video Resizing

Video Save

Draw a Circle on the Image

Adding Text Messages to Images

Draw Line Segment on Image

Draw a Rectangle on the Image

Draw an Ellipse on the Image

Arithmetic Operation

Image Blending

Threshold and Blurring

Area and Perimeter of Contours

Find Contours in an Image

Fitting Shape on the Contours

Checkpoint if inside, outside, or on the Contours

SIFT – (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

Course Curriculum

Chapter 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 ?

Chapter 2: OpenCV – Image Operation

Lecture 1: Image Read

Lecture 2: Image Crop

Lecture 3: Image Resized

Lecture 4: Image Rotate

Lecture 5: Image Split

Lecture 6: Image Save

Chapter 3: OpenCV – Video Operation

Lecture 1: Video Read

Lecture 2: Video Resized

Lecture 3: Video Save

Chapter 4: OpenCV – Draw Shape

Lecture 1: Draw Circle

Lecture 2: Adding Text Message

Lecture 3: Draw Line Segment

Lecture 4: Draw Rectangle

Lecture 5: Draw Eclipse

Chapter 5: OpenCV – Arithmetic Operation

Lecture 1: Not Arithmetic Operation

Lecture 2: AND Arithmetic Operation

Lecture 3: OR Arithmetic Operation

Lecture 4: Image Blending

Chapter 6: OpenCV – Threshold and Blurring

Lecture 1: Global Threshold

Lecture 2: Adaptive Thresholding

Lecture 3: Canny Edge Detection

Lecture 4: Image Blurring

Chapter 7: OpenCV – Contours and its Properties

Lecture 1: Find Contours in an Image

Lecture 2: Area And Perimeter of Counters

Lecture 3: Fitting Shape on the Contours

Lecture 4: Check Point if Inside, Outside or on the Contours

Chapter 8: OpenCV – Image feature and Matcher

Lecture 1: SIFT – (Scale-Invariant Feature Transform)

Lecture 2: Feature Matching

Chapter 9: OpenCV – Common Problem

Lecture 1: Save Images From Videos

Lecture 2: Make Video From Images

Lecture 3: Image from Pillow to OpenCV

Chapter 10: Conclusion

Lecture 1: Thank You

Instructors

Pooja Dhouchak
Founder and CEO of FatheVision

FatheVision AI
Now Computer Vision is easy to learn

Rating Distribution

1 stars: 0 votes

2 stars: 1 votes

3 stars: 4 votes

4 stars: 10 votes

5 stars: 48 votes

Frequently Asked Questions

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