Page 476 - AI Ver 3.0 class 10_Flipbook
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It means that the above image has a minimum pixel value as 0 and maximum pixel value as 255.

                 •  The  pixel value  by  its row  and  column coordinates of  an  image can  be  accessed  by  using  img[y
                 coordinate,x,coordinate,channels]. For the BGR image, it returns an array of Blue, Green, Red values.
                 For grayscale images, just corresponding intensity is returned. For example:
                  ✶  [B,G,R]= img[25, 40]
                     print(‘R=’, R, ‘G=’, G, ‘B=’,B)
                                                                                                th
                      It will display the Blue, Green, Red colour code between 0 to 255 of pixel at 25  row and 40 column of
                     an image taken with imread().
                  ✶  blue=img[25,40,0]             #traps only blue code

                     green=img[25,40,1]            #traps only green code

                     red=img[25,40,2]              #traps only red code
                     print(“Blue colour code at this pixel :”,blue)

                     print(“Green colour code at this pixel :”,green)
                     print(“Red colour code at this pixel :”,red)

                                                                                                        th
                                                                                            th
                      It will display the Blue, Green, Red colour code between 0 to 255 pixel at 25  row and 40  column of an
                                   rd
                     image using 3  parameter as 0,1,2.
              Let us now see how the above discussed functions will affect the code of displaying an image:
                 [1]:   import cv2 # import OpenCV
                        from matplotlib import pyplot as plt # import matplotlib
                        import numpy as np # import numpy
                        img = cv2. imread( 'D:/RGB.png' )
                        plt. imshow(cv2.cvtColor(img, cv2. COLOR_BGR2RGB) );
                        plt. axis( 'on');
                        plt. title( 'RGB - Display' )
                        plt. show()
                        print (img. shape)
                        [B,G,R]= img[25, 40]
                        print( 'Red=', R, 'Green=', G, 'Blue=', B)























              Cropping an Image


              Sometimes we need to remove the unwanted parts of the image to make it appear in a frame and help us focus
              on certain areas of the image. This can be done by cropping an image.



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