OpenCV: Manipulating Images

OpenCV 4.5    |    Beginner
  • 10 videos | 1h 20m 47s
  • Includes Assessment
  • Earns a Badge
Images often require to be manipulated to extract meaningful portions of an image or prepare them for a machine learning pipeline. OpenCV can help with this. In this course, you'll investigate a variety of image manipulation operations using OpenCV. You'll begin by recognizing how to filter certain portions of an image using bitwise operations. Next, you'll explore the concept of masks and how to use them while extracting parts of an image. You'll then outline how to apply geometrical operations by resizing an image to specific dimensions and discover challenges that such operations present. You'll finish the course by examining image transformations such as rotations and translations to help orient an image to your requirements. Finally, you'll discover how to flip and warp images to present them from a different perspective.


  • Discover the key concepts covered in this course
    Outline the applications of bitwise and, or, not, and xor operations on images
    Create masks and inverted masks from a grayscale image
    Transform a color image to grayscale and then generate a mask from it
    Use the cv2.resize() function to reduce the size of a color image
  • Apply cv2.resize() function to scale up an image along individual dimensions
    Perform translations and rotations in increments of 90 degrees to orient an image
    Rotate images by a specific angle around a specific center by generating a rotation matrix and applying an affine transformation
    Flip images vertically and horizontally and warp them using a specified perspective
    Summarize the key concepts covered in this course


  • 2m 25s
    In this video, you’ll learn more about your instructor and this course. In this course, you’ll learn about the image manipulation operations that can be carried out in OpenCV. You’ll learn how to perform bitwise operations on images. Learn how some parts of an image can be extracted using masks, and then learn about geometrical operations on images. You’ll also learn about other transformations such as image rotations and image translations. FREE ACCESS
  • 10m 50s
    In this video, you’ll watch a demo about BitwiseOperations on images. You’ll begin by importing cv2 and then from matplotlib, you’ll import pyplot with the alias plt. You’ll display these images in your Jupyter notebook. The first image you’ll use is fullmoon.jpg. You’ll read this in using cv2.imread and save it in a variable called fullmoon_ image. Now you’ll use the shape property on this ndarray, and you’ll get three dimensions. FREE ACCESS
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    3.  Generating Masks with OpenCV
    10m 7s
    In this video, you’ll watch a demo using masks. You’ll learn that masks can be thought of as auxiliary images, which can be used to influence the portions of the input images that should be ignored while performing operations on those images. You’ll start by importing cv2 and pyplot with the alias plt. Then, you’ll read in the images you’ll need, bluewall.jpg, neonsign.jpg, and circle.png. Each of these three images is read in using cv2.imread. FREE ACCESS
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    4.  Creating a Mask from a Color Image in OpenCV
    5m 34s
    In this video, you’ll watch a demo that teaches you to generate a mask from an input image. You’ll start by reading in the image you’ll need for the mask. You’ll discover the code that's used to read this image in is standard cv2.imread, and you’ll specify the file path. Next, you’ll plot it using I plot, and convert it from BGR2RGB. Then, you’ll convert this from a BGR image to a gray scale image. FREE ACCESS
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    5.  Using OpenCV's Resize Function to Downscale an Image
    8m 14s
    In this video, you’ll watch a demo about scaling images. Scaling images involves changing the number of pixels, which changes the shape of the NumPy ndarray used to represent that image. You’ll start by importing cv2 and pyplot with the alias plt. Then you’ll read in the image, and find its height, width, and color information. OpenCV will read the image into BGR representation. You’ll convert it to RGB and display it using pyplot. FREE ACCESS
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    6.  Using OpenCV's Resize Function to Upscale an Image
    10m 55s
    In this video, you’ll watch a demo about upscaling images. Then, you will learn to skew them. In the last demo, you performed a downscale operation. You’ll pick up there and perform an upscaling operation on the same input image. You’ll find the upscale percent is 300. The original had dimensions 500, 500, and the new upscaled image will be 1500, 1500. FREE ACCESS
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    7.  Translating and Rotating Images with OpenCV
    9m 7s
    In this video, you’ll watch a demo about geometric transformations such as rotations, translations, perspective transformations, and scaling. You’ll begin by importing cv2, pyplot with the alias plt, and NumPy as np. You’re going to transform the image from BGR to RGB. Then you’ll need the width and the height of this image in the form of tuple. You’ll extract that from the shape of the water_image in NumPy ndarray. FREE ACCESS
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    8.  Rotating Images with a Rotation Matrix in OpenCV
    10m 42s
    In this video, you’ll watch a demo. You’ll learn how to rotate by any angle and around center of rotation. Anytime a rotation is applied to a set of points in an xy plane, the new x coordinate is = x cos theta- y sine theta and the new y coordinate is = x sine theta + y cos theta. With this in mind, you’ll reexamine the 180-degree rotation. FREE ACCESS
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    9.  Flipping and Warping Images with OpenCV
    11m 10s
    In this video, you’ll watch a demo. In this demo, you’ll learn about other types of transformations, notably flips and perspective transformations. You’ll start by looking at the code required to flip an image around the x-axis. You’ll learn this is an OpenCV function which takes in an input image, as well as a flip code. FREE ACCESS
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    10.  Course Summary
    1m 44s
    In this video, you’ll summarize what you’ve learned in the course. In this course, you learned to perform bitwise operations on images to filter out certain portions of an image. You learned some parts of an image can be extracted using masks. You learned several geometrical operations, including resizing an image. You also explored transformations such as image rotations and image translations. FREE ACCESS


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