Learn OpenCV with Python by Exercises: Build Computer Vision Algorithms by OpenCV with Python for Image Processing

Python is of the most popular and versatile programming languages in the tech industry. However, despite their popularity and versatility, mastering them can be challenging, especially for beginners. Technical challenges such as debugging and tight deadlines can cause stress and anxiety, and career advancement and staying up to date with the latest developments in the field can be daunting.Here what you'll learn after downloading this book:✓Introduction to OpenCV✓Install OpenCV for Python✓Reading an image in OpenCV using Python✓Color Spaces in OpenCV✓Arithmetic Operations on Images using OpenCV✓Image Resizing using OpenCV✓Image blurring using OpenCV✓Grayscaling of Images using OpenCV✓Erosion and Dilation of images using OpenCV✓OpenCV Python Program to analyze an image using Histogram✓Histograms Equalization in OpenCV✓Thresholding techniques using OpenCV✓OpenCV: Segmentation using Thresholding✓Filter Color with OpenCV✓Denoising of colored images using opencv✓Visualizing image in different color spaces✓Image Registration using OpenCV✓Find and Draw Contours using OpenCV✓Draw a triangle with centroid using OpenCV✓Play a video using OpenCV✓Create video using multiple images using OpenCV✓Extract images from video in PythonAnd more...This Book Is Perfect For:• New or experienced programmers looking to enhance their career opportunities with an in-demand programming language• Job seekers who want to supercharge their resumes and increase their value in the job marketplace• Students or recent college grads who have their sights set on a lucrative position in the tech industry• Anyone who wants to explore the world of programming, use Python to automate tedious tasks, or enhance their resume and future-proof their skills! About the Authors Table of Contents Learn OpenCV with Python by Exercises PART 1: Introduction Chapter 1: Introduction to OpenCV Chapter 2: Install OpenCV for Python on Windows Downloading and Installing OpenCV: Chapter 3: Install OpenCV for Python in Linux Downloading and Installing OpenCV: Chapter 4: Set up Opencv with anaconda environment Requirements for OpenCV and Anaconda ANACONDA OPENCV Creating Anaconda Environment : Install OpenCV Reading an image PART 2: Working with Images Chapter 1: Reading an image in OpenCV using Python Chapter 2: Python OpenCV | cv2.imshow() method Python3 Python3 Python3 Chapter 3: Python OpenCV | cv2.imwrite() method Chapter 4: OpenCV | Saving an Image Code : C++ code for saving an image to any location in OpenCV. Explanation : Chapter 5: Color Spaces in OpenCV Chapter 6: Arithmetic Operations on Images using OpenCV | Set-1 (Addition and Subtraction) Addition of Image: Subtraction of Image: Chapter 7: Arithmetic Operations on Images using OpenCV | Set-2 (Bitwise Operations on Binary Images) Bitwise AND operation on Image: Bitwise OR operation on Image: Bitwise XOR operation on Image: Bitwise NOT operation on Image: PART 3: Image Processing Chapter 1: Image Resizing using OpenCV Chapter 2: Python OpenCV | cv2.erode() method Chapter 3: Image blurring using OpenCV Chapter 4: Python OpenCV | cv2.copyMakeBorder() method Chapter 5: Grayscaling of Images using OpenCV Importance of grayscaling Method 1: Using the cv2.cvtColor() function Python3 Method 2: Using the cv2.imread() function with flag=zero Python3 Method 3: Using the pixel manipulation (Average method) Python3 Chapter 6: Erosion and Dilation of images using OpenCV in python Chapter 7: OpenCV Python Program to analyze an image using Histogram Chapter 8: Histograms Equalization in OpenCV Chapter 9: Thresholding techniques using OpenCV | Set-1 (Simple Thresholding) Simple Thresholding Chapter 10: Thresholding techniques using OpenCV | Set-2 (Adaptive Thresholding) Chapter 11: Thresholding techniques using OpenCV | Set-3 (Otsu Thresholding) Chapter 12: OpenCV: Segmentation using Thresholding Chapter 13: Python OpenCV | cv2.cvtColor() method Chapter 14: Filter Color with OpenCV Chapter 5: Denoising of colored images using opencv Chapter 6: Visualizing image in different color spaces Chapter 7: Find Co-ordinates of Contours using OpenCV Chapter 8: Image Inpainting using OpenCV Chapter 9: Intensity Transformation Operations on Images Log Transformations – Power-Law (Gamma) Transformation – Piecewise-Linear Transformation Functions – Chapter 10: Image Registration using OpenCV Python Chapter 11: Background subtraction using OpenCV Chapter 12: Background Subtraction in an Image using Concept of Running Average Chapter 13: Foreground Extraction in an Image using Grabcut Algorithm Chapter 14: Morphological Operations in Image Processing (Opening) | Set-1 Chapter 15: Morphological Operations in Image Processing (Closing) | Set-2 Chapter 16: Morphological Operations in Image Processing (Gradient) | Set-3 Chapter 17: Image segmentation using Morphological operations in Python Chapter 18: Image Translation using OpenCV Chapter 19: Image Pyramid using OpenCV PART 4: Feature Detection and Description Chapter 1: Line detection in python with OpenCV | Houghline method Chapter 2: Circle Detection using OpenCV Chapter 3: Detect corner of an image using OpenCV Chapter 4: Corner Detection with Shi-Tomasi Corner Detection Method using OpenCV Shi-Tomasi Corner Detection – Mathematical Overview – Chapter 5: Corner detection with Harris Corner Detection method using OpenCV Chapter 6: Find Circles and Ellipses in an Image using OpenCV Chapter 7: Document field detection using Template Matching Python3 Chapter 8: Smile detection using OpenCV PART 5: Drawing Functions Chapter 1: Python OpenCV | cv2.line() method Implementation: Chapter 2: Python OpenCV | cv2.arrowedLine() method Chapter 3: Python OpenCV | cv2.ellipse() method Chapter 4: Python OpenCV | cv2.circle() method Chapter 5: Python OpenCV | cv2.rectangle() method Chapter 6: Python OpenCV | cv2.putText() method Chapter 7: Find and Draw Contours using OpenCV Chapter 8: Draw a triangle with centroid using OpenCV Chapter 9: Play a video using OpenCV Below is the complete implementation Chapter 10: Create video using multiple images using OpenCV Chapter 11: Extract images from video in Python