figure - our two sample color images we can clearly see from figure - that we have two images of cat and dog having dimensions pixels where each row and column denotes specific pixel of the image the third dimension indicates these are color images having three color channels let' now try to use numpy indexing to slice out and extract the three color channels separately for the dog image in [ ]dog_r dog copy(red channel dog_r[:,:, dog_r[:,:, set , pixels dog_g dog copy(green channel dog_g[:,:, dog_r[:,:, set , pixels dog_b dog copy(blue channel dog_b[:,:, dog_b[:,:, set , pixels plot_image np concatenate((dog_rdog_gdog_b)axis= plt figure(figsize ( , )plt imshow(plot_imagefigure - extracting redgreenand blue channels from our color rgb image we can clearly see from figure - how we can easily use numpy indexing and extract out the three color channels from the sample image you can now refer to any of these channel' raw image pixel matrix and even flatten it if needed to form feature vector in [ ]dog_r[:,:, out[ ]array([[ ][ ]