Discover OpenCV to enhance AI in computer vision. Learn image/video processing, editing, and basic machine learning like edge, object, and face detection with real-world projects.

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OpenCV is an open-source machine learning library for Python that adds enhanced artificial intelligence capabilities in computer vision and image processing.

This course is a comprehensive introduction to building applications using OpenCV, including viewing, identifying, and editing image and video files using Python. You’ll start with an introduction to the library before immediately applying the framework to view images, video, webcam input, and text. You’ll then take your image captures and apply various edits, including decolorization, cropping, resizing, and captioning with layered text and objects. You’ll continue with basic machine learning functions, including edge, object, and face detection. With the basics in hand, you’ll wrap up with real-world projects to build document scanners and object trackers.

By the end of this course, you’ll have a working knowledge of OpenCV and machine learning. You’ll be prepared to build functional applications using the principles of computer vision in Python.

Mastering Computer Vision in Python with OpenCV

The image should have the same color space.

What are the necessary conditions of the images that are used for stacking? (You can choose multiple options.)

What are the necessary conditions of the images that are used for stacking? (You can choose multiple options.)

It gives only the non-intersecting regions of the images.

It gives both the intersecting as well as non-intersecting regions of the images.

It only gives the intersecting regions of the images.

It inverts the black and white pixel regions in the image.

What is the function of the `XOR` operator?

What is the function of the <code>XOR</code> operator?

(image, number of channels, mask, histSize, range of pixel value)

(image, range of pixel value, mask, histSize, number of channels)

(mask, histSize, image, number of channels, range of pixel value)

What are the parameters inside the `cv2.calcHist()` function in correct order?

What are the parameters inside the <code>cv2.calcHist()</code> function in correct order?

- `contourindex` is the index of the contour that we want to draw.
- `contourindex` value -1 will give the command to draw only one contour.


- `contourindex` is the total number of contours that we want to draw.
- `contourindex` value -1 will give the command to draw only one contour.


- `contourindex` is the total number of contours that we want to draw.
- `contourindex` value -1 will give the command to draw all the contours.


- `contourindex` is the index of the contour that we want to draw.
- `contourindex` value -1 will give the command to draw all the contours.


What is the `contourindex`? What is the meaning of `contourindex` value -1?

What is the <code>contourindex</code>? What is the meaning of <code>contourindex</code> value -1?

Introduction to Python OpenCV

Read Images, Videos, and Webcam

Editing Images

Reading and Editing Images with OpenCV

Advanced Editings

Detection

Assessment on Advanced Editing and Detection

Real-life projects

Conclusion

Quiz: Advanced Editing and Detection