Learn X in Y minutes

# 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 arguement is the title of the window and second parameter is image
# If you are getting error, Object Type None, your image path may be wrong. Please recheck the pack to the image
cv2.waitKey(0)
# waitKey() is a keyboard binding function and takes arguement in milliseconds. For GUI events you MUST use waitKey() function.

# Writing an image
cv2.imwrite('catgray.png',img)
# first arguement 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 camera, 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.