--- category: framework name: OpenCV filename: learnopencv.py contributors: - ["Yogesh Ojha", "http://github.com/yogeshojha"] --- ### OpenCV OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage then Itseez (which was later acquired by Intel). OpenCV currently supports wide variety of languages like, C++, Python, Java, etc. #### Installation Please refer to these articles for installation of OpenCV on your computer. * Windows Installation Instructions: [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows](https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows) * Mac Installation Instructions (High Sierra): [https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a](https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a) * Linux Installation Instructions (Ubuntu 18.04): [https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv](https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv) ### Here we will be focusing on Python implementation of OpenCV ```python # Reading image in OpenCV import cv2 img = cv2.imread('cat.jpg') # Displaying the image # imshow() function is used to display the image cv2.imshow('Image', img) # Your first argument is the title of the window and second parameter is image # If you are getting an error, Object Type None, your image path may be wrong. Please recheck the path to the image cv2.waitKey(0) # waitKey() is a keyboard binding function and takes an argument in milliseconds. For GUI events you MUST use waitKey() function. # Writing an image cv2.imwrite('catgray.png', img) # The first argument is the file name and second is the image # Convert image to grayscale gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Capturing Video from Webcam cap = cv2.VideoCapture(0) # 0 is your camera, if you have multiple cameras, you need to enter their id while True: # Capturing frame-by-frame _, frame = cap.read() cv2.imshow('Frame', frame) # When user presses q -> quit if cv2.waitKey(1) & 0xFF == ord('q'): break # Camera must be released cap.release() # Playing Video from file cap = cv2.VideoCapture('movie.mp4') while cap.isOpened(): _, frame = cap.read() # Play the video in grayscale gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) cv2.imshow('frame', gray) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() # Drawing The Line in OpenCV # cv2.line(img, (x,y), (x1,y1), (color->r,g,b->0 to 255), thickness) cv2.line(img, (0, 0), (511, 511), (255, 0, 0), 5) # Drawing Rectangle # cv2.rectangle(img, (x,y), (x1,y1), (color->r,g,b->0 to 255), thickness) # thickness = -1 used for filling the rectangle cv2.rectangle(img, (384, 0), (510, 128), (0, 255, 0), 3) # Drawing Circle # cv2.circle(img, (xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness) cv2.circle(img, (200, 90), 100, (0, 0, 255), -1) # Drawing Ellipse cv2.ellipse(img, (256, 256), (100, 50), 0, 0, 180, 255, -1) # Adding Text On Images cv2.putText(img, "Hello World!!!", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255) # Blending Images img1 = cv2.imread('cat.png') img2 = cv2.imread('openCV.jpg') dst = cv2.addWeighted(img1, 0.5, img2, 0.5, 0) # Thresholding image # Binary Thresholding _, thresImg = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY) # Adaptive Thresholding adapThres = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2) # Blur Image # Gaussian Blur blur = cv2.GaussianBlur(img, (5, 5), 0) # Median Blur medianBlur = cv2.medianBlur(img, 5) # Canny Edge Detection img = cv2.imread('cat.jpg', 0) edges = cv2.Canny(img, 100, 200) # Face Detection using Haar Cascades # Download Haar Cascades from https://github.com/opencv/opencv/blob/master/data/haarcascades/ import cv2 import numpy as np face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') img = cv2.imread('human.jpg') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.3, 5) for x, y, w, h in faces: # Draw a rectangle around detected face cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2) roi_gray = gray[y : y + h, x : x + w] roi_color = img[y : y + h, x : x + w] eyes = eye_cascade.detectMultiScale(roi_gray) for ex, ey, ew, eh in eyes: # Draw a rectangle around detected eyes cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2) cv2.imshow('img', img) cv2.waitKey(0) cv2.destroyAllWindows() # destroyAllWindows() destroys all windows. # If you wish to destroy specific window pass the exact name of window you created. ``` ### Further Reading: * Download Cascade from [https://github.com/opencv/opencv/blob/master/data/haarcascades](https://github.com/opencv/opencv/blob/master/data/haarcascades) * OpenCV drawing Functions [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html](https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html) * An up-to-date language reference can be found at [https://opencv.org](https://opencv.org) * Additional resources may be found at [https://en.wikipedia.org/wiki/OpenCV](https://en.wikipedia.org/wiki/OpenCV) * Good OpenCV Tutorials * [https://realpython.com/python-opencv-color-spaces](https://realpython.com/python-opencv-color-spaces) * [https://pyimagesearch.com](https://pyimagesearch.com) * [https://www.learnopencv.com](https://www.learnopencv.com)