Gain insights into OpenCV with C++. Delve into image editing, machine learning functions, and practical applications like object detection. Discover real-world projects to elevate your programming skills.

open_cv_cpp.tar.gz

OpenCV

OpenCV-GUI

OpenCV is extensively used in the business world for various applications, including facial recognition, object detection, and image and video manipulation. 

In this course, you'll learn the basics of OpenCV—an open-source machine learning library. You'll begin with an overview of the OpenCV library before moving on to practical applications like viewing images, videos, and webcam input. Next, you'll learn how to edit images with tools like decolorizing, cropping, resizing, and captioning. You'll dive into machine learning functions like edge detection, contour detection, corner detection, and face detection. Finally, you'll work on practical projects like document scanners and object trackers. 

By the end of this course, you’ll have a solid understanding of OpenCV and machine learning with C++. You'll be able to create functional applications using computer vision principles, preparing you for real-world projects. Taking this course will allow you to take your programming skills to the next level.

Learning OpenCV from Scratch with C++

Masking is another essential tool used to edit images in OpenCV. **Masking** is an image editing technique used to highlight a specific part of an image. It's used to combine different images, as well as highlight the required portion in the combined images.

We can use bitwise operators to mask images. This lesson will explain how the process is carried out. 

To start off, we create a blank image using the `Mat::zeros()` function of the OpenCV library. We'll create the mask in a blank image and later use it to mask an image.

```
cv::Mat circleA = cv::Mat::zeros(cv::Size(600,600), CV_8UC3);
```
> **Note:** While masking, the size of the mask image should be the same as the image being masked. We need to read an image as `img` before creating the blank image.


# Create the mask
First, we’ll create a crescent-shaped mask for our image. We create two different blank images, one with a circle and one with a rectangle. Next, we use the `AND` bitwise operator to combine them.









Introduction to C++ OpenCV

Reading Media

Editing Images

Reading and Editing Images with OpenCV

Advanced Editing

Detection

Assessment on Advanced Editing and Detection

Real-Life Projects

Conclusion

Appendix

Masking Images