Draw Shapes,Text,Polygons,Blend,Blur images | Using OpenCV With Python | Easy code

 import cv2 #opencv library  import matplotlib.pyplot as plt # Matplotlib used for visualization  %matplotlib inline # Reading the jpeg formmatted image from its path to img1  img1=cv2.imread(r'./img/hp.JPG') # Reading the jpeg formatted image from its path to img2  img2=cv2.imread(r'./img/doc.JPG') # Converting from BGR(blue,green,red) color space to RGB using cvtColor  img1=cv2.cvtColor(img1,cv2.COLOR_BGR2RGB) img2=cv2.cvtColor(img2,cv2.COLOR_BGR2RGB) # Displaying the image 1  plt.imshow(img1) # Displaying the image 2  plt.imshow(img2) 

 #'1' Flips image to left side, '0' to upside down and '-1' to combination of both 0 and 1  flip_img=cv2.flip(img1,1) # Showing flipped image  plt.imshow(flip_img) 

 # Gives the shape (height,width, no.of color channels(RGB)) of image1  flip_img.shape 

(2093, 2652, 3) 

 # Gives the shape (height,width, no.of color channels(RGB)) of image2  img2.shape 

(2127, 3840, 3) 

 # Both images should be of same size to blend.  flip_img=cv2.resize(flip_img,(2652,2093)) img2=cv2.resize(img2,(2652,2093)) 

 # Increase in alpha increases img1 weightage,beta for img2  blended=cv2.addWeighted(src1=flip_img,alpha=0.9,src2=img2,beta=0.9,gamma=0) 

 # Saves the blended img under the name blended.JPG  cv2.imwrite('blended_img.png',blended) 

True 

 import cv2 # opencv library  import numpy as np # Matplotlib used for visualization purpose  import matplotlib.pyplot as plt %matplotlib inline # Array of size 512x512 filled with zero as values,  # to create an image with black color.  img=np.zeros(shape=(512,512,3),dtype=np.int16) # Displays the shape(Height,width,no.of color channels(RGB))  img.shape 

(512, 512, 3) 

 # To display the image  plt.imshow(img) 

 # cv2.rectangle(image, start_point, end_point, color, thickness)  cv2.rectangle(img,pt1=(0,0),pt2=(100,100),color=(0,0,255),thickness=10) 

array([[[ 0, 0, 255], [ 0, 0, 255], [ 0, 0, 255], ..., [ 0, 0, 0], [ 0, 0, 0], [ 0, 0, 0]],.. 

 plt.imshow(img) 

 # cv2.circle(image, center_coordinates, radius, color, thickness)  cv2.circle(img,center=(150,150),radius=100,color=(255,0,0),thickness=10) 

array([[[ 0, 0, 255], [ 0, 0, 255], [ 0, 0, 255], ..., [ 0, 0, 0], [ 0, 0, 0], [ 0, 0, 0]], [[ 0, 0, 255], [ 0, 0, 255], [ 0, 0, 255], ..., 

 plt.imshow(img) 

 # Negative values for thickness results in filled/solid circles  cv2.circle(img,center=(200,200),radius=100,color=(255,255,0),thickness=-10) 

array([[[ 0, 0, 255], [ 0, 0, 255], [ 0, 0, 255], ..., [ 0, 0, 0], [ 0, 0, 0], [ 0, 0, 0]], 

plt.imshow(img) 

 # cv2.line(image, start_point, end_point, color, thickness)  cv2.line(img,pt1=(275,275),pt2=(512,512),color=(0,255,0),thickness=10) 

array([[[ 0, 0, 255], [ 0, 0, 255], [ 0, 0, 255], ..., [ 0, 0, 0], [ 0, 0, 0], [ 0, 0, 0]], 

 plt.imshow(img) 

 # Font of the text  text_style=cv2.FONT_ITALIC # Syntax  #cv2.putText(image, text, org, font, fontScale, color[, thickness[, lineType[, bottomLeftOrigin]]])  cv2.putText(img,text='HAKUNA MATATA',org=(10,200),fontFace=text_style,fontScale=2,color=(0,0,255),thickness=3,lineType=cv2.LINE_AA) 

array([[[0, 0, 0], [0, 0, 0], [0, 0, 0], ..., [0, 0, 0], [0, 0, 0], [0, 0, 0]],.. 

 plt.imshow(img) 

 import cv2 import numpy as np # Matplotlib used for visualization purpose  import matplotlib.pyplot as plt %matplotlib inline # Array of size 512x512 filled with zero as values,  # to create an image with black color.  img=np.zeros(shape=(512,512,3),dtype=np.int16) # Assigning vertices to polygon  poly=np.array([[100,200],[200,100],[400,300],[200,400]],dtype=np.int32) poly.shape 

 (4, 2) 

 # Reshaping according to opencv format  poly_new=poly.reshape((-1,1,2)) poly_new.shape 

(4, 1, 2) 

 # cv2.polylines(img, pts, isClosed, color[, thickness[, lineType[, shift]]])  cv2.polylines(img,[poly_new],isClosed=True,color=(0,255,0),thickness=10) 

array([[[0, 0, 0], [0, 0, 0], [0, 0, 0], ..., 

 plt.imshow(img) 

 import cv2 # opencv library  # Matplotlib used for visualization  import matplotlib.pyplot as plt %matplotlib inline import numpy as np img=cv2.imread(r'./img/image.JPG') img=cv2.cvtColor(img,cv2.COLOR_BGR2RGB) plt.imshow(img) 

 kernel=np.ones((5,5),np.float)/25 # Default Blurring Technique  plt.imshow(cv2.blur(img,ksize=(5,5))) 

 # Gaussian Blurring Technique  plt.imshow(cv2.GaussianBlur(img,(5,5),0)) 

 # Smoothing Technique  plt.imshow(cv2.filter2D(img,-1,kernel)) 

 # Median Blurring Technique  # Reduces unwanted noise  plt.imshow(cv2.medianBlur(img,5)) 

 # Bilateral Filter Blurring Technique  # Reduces unwanted noise with sharp edges but slow  plt.imshow(cv2.bilateralFilter(img,9,75,75))