Aspire     Pythonista to Python Master     Python Master Track 5: Resource Optimization with Python

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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.

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Objectives

OpenCV: Manipulating Images 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