Mastering Python OpenCV: With 38 Real-World Projects

Learn how to read images and videos with OpenCV, display them using imshow, and manage windows with waitKey and destroyAllWindows, then capture video from files or webcam.

Translate images in OpenCV by building a translation matrix with numpy to shift along the x and y axes, then display the result with cv2.imshow.

Learn to rotate images with Python OpenCV by building a rotate function that finds the center, creates a rotation matrix, applies warp, and displays results for 45 and -45 degrees.

Master OpenCV image transformations by resizing, flipping, and cropping, using cv2.resize with cubic interpolation, cv2.flip with 0, 1, or -1, and precise cropping.

Learn how to blur images in OpenCV using averaging, Gaussian, median, and bilateral filters, with kernel sizes like 3x3 and 7x7 to reduce noise while exploring edge preservation.

Master bitwise operations in OpenCV, including and, or, xor, and not, for pixel-level blending and masking between images or with a mask, illustrated using a rectangle and circle.

learn to extract and visualize color image histograms using OpenCV and matplotlib, analyzing blue, green and red channels from a color image with 0–255 intensity bins.

Apply thresholding to convert a color image to a binary image by first converting to grayscale, then comparing pixels to a threshold, using simple thresholding, binary inverse, and adaptive thresholding.

Count black dots on white surface and white dots on black surface using Python OpenCV, applying grayscale conversion, binary thresholding, and contour area filtering to detect and count dots.

Learn to display x and y coordinates of points clicked on an image using python open cv by handling left and right mouse events and printing coordinates.

Track objects by color using OpenCV in Python. Convert frames from BGR to HSV, create a color mask with inRange, and apply bitwise operations to isolate the target.

Detect pedestrians in video frames with OpenCV's hog descriptor and a pre-trained SVM model, resizing with imutils and drawing red bounding boxes on the output.

Explore a real-world OpenCV project that creates an invisible t-shirt by capturing the background, detecting red color cloth, generating masks, and applying bitwise operations for a magical effect.

Build a live privacy filter with phase blur using OpenCV and Haar cascade face detection; blur detected faces with Gaussian blur in real time.

Process real-time webcam frames with Python OpenCV to detect guns using a pre-trained haarcascade gun cascade XML. The code converts frames to grayscale, runs detectMultiScale, and draws rectangles around detections.

Develop a car detection program in Python using OpenCV, loading cars.xml, reading cars.mp4 video, converting frames to grayscale, applying cascade classifier detectMultiScale, and drawing red rectangles around detected cars.

Learn to replace a green screen with OpenCV in Python by isolating the person using an HSV mask, removing the green background with bitwise operations, and overlaying a background image.

Explore an OpenCV drawing app using a blue color tracker via webcam to draw in real time, switching to green, red, and yellow strokes across live, paint, and mask windows.

Create an interactive color detector in OpenCV by building HSV trackbars for upper and lower hue, saturation, and value to detect blue objects in Python.

Set up a paint canvas with numpy and opencv, define blue, green, red, and yellow colors, draw color buttons with cv2 rectangles, and display the window for webcam frame processing.

Create a binary mask from HSV ranges using inRange, then refine with erosion, morphology open, and dilation. This isolates a blue pointer and sets up future contour detection.

Define a function count_finger that uses Mediapipe hand landmarks to detect an extended thumb by x comparisons and other fingers by y comparisons, returning the extended finger count.