Learn Practical Approach to OpenCV using Kotlin

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Pravin Tripathi

26:28:29

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1. Introduction to the course

1. Introduction to course - 1.mp4

02:01

2. Introduction to course - 2.mp4

02:29

3. Requirement to develop in this course.mp4

03:25

2. Setup your machine for OpenCV

1. Project GitHub project link for the course.html

2. Windows OpenCV installation - 1.mp4

02:55

3. Windows OpenCV installation - 2.mp4

04:19

4. Windows OpenCV installation - 3.mp4

07:01

5. Linux OpenCV installation from official documentation.html

6. Linux OpenCV installation - 1.mp4

02:08

7. Linux OpenCV installation - 2.html

8. Mac OpenCV installation.html

9. Project Modification in build.gralde file of the project.mp4

01:09

10. Project Take checkout of the project and start playing on it.mp4

11:47

3. Image Filters

1. Introduction.mp4

01:52

2. Negative change image to negative image - 1.mp4

07:53

3. Negative change image to negative image - 2.mp4

09:39

4. Negative change image to negative image - 3.mp4

10:59

5. Thresholding Introduction of Threshold API.mp4

05:29

6. Thresholding Binary Thresholding (convert image to black and white).mp4

17:09

7. Thresholding OTSU thresholding (convert image to black and white).mp4

07:05

8. Thresholding Fixing image for thresholding.mp4

05:49

9. Thresholding trying different parameters and code refactoring.mp4

07:23

10. Grayscale Filter.mp4

11:50

11. Denoising FastNL Mean Denoise API (remove noise from image) - 1.mp4

04:18

12. Denoising FastNL Mean Denoise API (remove noise from image) - 2.mp4

11:34

13. Denoising FastNL Mean Denoise API (remove noise from image) - 3.mp4

06:22

14. Sharpening difference between gaussian blur and Laplacian filter - 1.mp4

28:00

15. Sharpening implementation using Laplacian filter - 2.mp4

04:01

16. Sharpening sharpen color image using Laplacian and Gaussian in YUV - 3.1.mp4

08:37

17. Sharpening sharpen color image using Laplacian and Gaussian in YUV - 3.2.mp4

05:55

18. Sharpening Code refactoring - 5.mp4

04:05

19. Smoothing Introduction.mp4

11:32

20. Smoothing Gaussian filter implementation.mp4

18:49

21. Smoothing Bilateral filter implementation.mp4

09:31

22. Smoothing smoothing to specific region in the image.mp4

25:04

23. Smoothing Test code refactoring.mp4

15:58

24. Crisper Image Intro to unsharp masking.mp4

07:25

25. Crisper Image unsharp masking implementation.mp4

50:30

26. Section Summary.mp4

01:49

4. Image Transformations

1. Introduction of Transformations.mp4

02:39

2. Rotation Introduction of rotation API.mp4

03:47

3. Rotation Implementation of rotation.mp4

20:17

4. Rotation Refactoring code.mp4

06:27

5. Rotation Understanding rotation matrix 2d and warp affine.mp4

07:15

6. Rotation Enhancement of rotation code for any angle rotation.mp4

20:51

7. Scaling Understanding scaling transformation.mp4

10:38

8. Scaling Scaleing up image using inter linear and inter cubic.mp4

18:03

9. Scaling Scaling down.mp4

16:01

10. Scaling scaling differently in x and y direction.mp4

11:54

11. Translation Understanding translation.mp4

05:06

12. Translation Implementation of translation.mp4

17:18

13. Perspective Understanding perspective transformation.mp4

06:18

14. Perspective Implementation of perspective transformation.mp4

21:40

15. Perspective Refactoring and enhancing perspective transform.mp4

23:45

16. Section Summary.mp4

02:29

5. Contrast Enhancements

1. Histogram Introduction to histogram equalization.mp4

10:15

2. Histogram Histogram equalization for gray image.mp4

13:02

3. Histogram Histogram equalization for color image.mp4

13:29

4. Gamma Correction Introduction.mp4

08:56

5. Gamma Correction Gamma correction implementation grayscale image - 1.mp4

05:40

6. Gamma Correction Gamma correction implementation grayscale image - 2.mp4

13:35

7. Gamma Correction Gamma correction on color image.mp4

03:10

8. Adaptive Histogram Histogram CLAHE introduction.mp4

09:23

9. Adaptive Histogram Applying Histogram CLAHE on grayscale image.mp4

15:24

10. Adaptive Histogram Applying Histogram CLAHE on color image.mp4

12:21

11. Saturation correction Adjusting Contrast and brightness.mp4

08:38

12. Saturation correction Applying on gray and color image.mp4

21:17

13. Comparison of different algorithms Introduction.mp4

02:22

14. Comparison of different algorithms with imadjust algorithm (from matlab).mp4

18:16

15. Custom enhancement Introduction.mp4

12:14

16. Custom enhancement algorithm explaination.mp4

15:27

17. Custom enhancement imadjust for gray image implementation.mp4

30:23

18. Custom enhancement code refactoring.mp4

13:23

19. Custom enhancement Add test for color image before coding.mp4

02:05

20. Custom enhancement 4. run test 1 continue and implement for color image.mp4

23:28

21. Custom enhancement Refactoring and testing color image.mp4

25:18

22. Section Summary.mp4

01:15

6. Text and Complex Operations

1. Introduction.mp4

01:02

2. Text Operation Add text task to do.mp4

02:18

3. Text Operation OpenCV documentation walkthrough.mp4

04:59

4. Text Operation add text to image.mp4

49:50

5. Text Operation add rectangle enclosing text.mp4

22:45

6. Text Operation add rotated text in image.mp4

21:50

7. Text Operation fix text intensity issue for rotated text added.mp4

09:04

8. Advanced Text Operation explanation of refactored code.mp4

07:25

9. Advanced Text Operation Implementation for add text with perspective transform.mp4

26:57

10. Advanced Text Operation refactoring code.mp4

23:00

11. Section Summary.mp4

00:52

7. [Advanced] Building image editor application using learnt concepts

1. Intro.mp4

02:06

2. design explanation.mp4

05:11

3. Snapshot(memento design pattern).mp4

06:14

4. Command (command design pattern).mp4

03:20

5. Code refactoring.mp4

13:17

6. Implementation - editor and state manager - 1.mp4

10:01

7. Implementation - editor and state manager - 2.mp4

18:15

8. Implementation - editor and state manager - 3.mp4

27:31

9. Implementation - editor and state manager - 4.mp4

15:22

10. Implementaion of snapshot class.mp4

32:07

11. Implementation editor and backup manager - 1.mp4

13:42

12. Implementation editor and backup manager - 2.mp4

26:55

13. Implementation editor and backup manager - 3.mp4

14:19

14. Implementation editor and backup manager - 4.mp4

08:55

15. Implementation editor and client Introduction.mp4

02:25

16. Implementation editor and client 1.mp4

20:24

17. Implementation editor and client 2.mp4

12:47

18. Implementation editor and client 3.mp4

23:10

19. Implementation editor and client 4.mp4

05:45

20. Implementation editor and client 5.mp4

31:30

21. Refactoring code 1.mp4

06:27

22. Refactoring code 2.mp4

19:33

23. Refactoring code 3.mp4

29:35

24. Section Summary.mp4

01:28

8. Publishing image editor code as library

1. Introduction.mp4

02:57

2. add publishing and publish manually.mp4

31:02

3. fix publishing issue.mp4

03:33

4. access the published library in different project.mp4

11:32

5. recap of what done and how to test.mp4

03:33

6. add GitHub action for publishing package - 1.mp4

24:13

7. add GitHub action for publishing package - 2.mp4

14:01

8. refactor Gradle build and library publish workflow.mp4

15:52

9. fix workflow issue.mp4

06:29

10. add caching 1.mp4

04:35

11. add caching 2.mp4

07:05

12. successful running of publish library workflow.mp4

01:33

13. add CI test pipeline.mp4

15:40

14. recap and summary.mp4

05:45

9. [Advanced] Building document scanner app for Android using our library

1. Android app introduction.mp4

04:15

2. Android Project setup.mp4

08:17

3. Steps to import OpenCV SDK.mp4

04:31

4. Code review and fix dependency issue.mp4

15:28

5. Code walkthrough.mp4

13:25

6. summary.mp4

01:17

10. [Advanced] [Extra] Automatic document detection in image

1. Intro to auto detection feature.mp4

04:29

2. Algorithm walkthrough.mp4

14:22

3. Understanding each step using OpenCV API.mp4

26:23

4. Detect region of interest code walkthrough.mp4

14:17

5. summary.mp4

01:13

11. Wrap up

1. Ending note.mp4

02:40

Description

Less theory but more code to build complex OpenCV applications

What You'll Learn?

Become proficient enough to do complex opencv operation on the image
Able to understand and use core API of the OpenCV library
Apply image processing concepts to create better image using OpenCV
Sharing OpenCV code across different platform as library dependency
Learn TDD and clean coding approach in OpenCV application
Applying design pattern to known coding problems while building apps
Practical examples of the commonly used features in popular apps mobile or desktop
Developing complex feature in Android app that uses OpenCV

Who is this for?

Someone who has an interest in learning about Image processing.

Someone who wants to explore the power of the OpenCV library.

Someone who wants to learn and build OpenCV complex functions.

What You Need to Know?

Object Oriented Programming knowledge

Understanding of Kotlin or Java program code

Laptop

Opencv library

Android phone (Optional) for some project

Basic knowledge of Algebra and Geometry

More details

Description
OpenCV is a widely used library for developing complex applications on various devices like Mobile, Desktop, Raspberry Pi, backend applications, etc.

There are many courses and books available that provide a good theoretical understanding of image processing concepts. If you are someone who has no understanding of image processing, I would suggest you take some basic level course or book to gain a high-level understanding to better understand this course.

This course is primarily designed for someone who wants to see the power of the OpenCV library and also to learn by coding. In this course, we will first learn the basic concept and later implement the code to visually understand the same using code.

If you are a beginner or intermediate-level learner, you will learn a lot for sure. There are many skills you will learn as you progress with the course. Skills like TDD, clean coding, identifying the problem, and using appropriate design patterns to simplify the code which is something many developers in big MNCs give very less emphasis on.

If you are an expert-level learner, It will be a refreshing course for you.

In this course, we have covered complex-level application that uses the advanced-level concept to achieve interesting results.

Happy learning !!

Who this course is for:
Someone who has an interest in learning about Image processing.
Someone who wants to explore the power of the OpenCV library.
Someone who wants to learn and build OpenCV complex functions.

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I have a good (5+ years) experience in backend software development. Also, I like sharing my experiences and knowledge in the form of text and video blog posts to my community and the internet over LinkedIn, Twitter, and personal blogs.My technical focus is on distributed systems, including Microservices and CI/CD.

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