jet_culprit.py

!pip install -Uqq fastbook
import fastbook
fastbook.setup_book()

#importing all the packages and functions from fastai's vision
from fastai.vision import *
from fastbook import 

#loading the color image
eye_img = Image.open("/content/eye.jpg")

#converting to numpy array
eye_arr = array(eye_img)

#A function that does color to grayscale conversion
def transf_RBG(image_arr, RBG_conv_met):
  """
  Takes an image array and a conversion method as inputs
  Transforms the color image to grayscale based on the specified method 
  """
  import cv2
  blue, green, red = cv2.split(image_arr)
  if RBG_conv_met == "Average":
    grayscale_im = (np.round(3**-1*blue + 3**-1*green + 3**-1*red)).astype('uint8')
    return grayscale_im
  elif RBG_conv_met == "Weighted_average":
    grayscale_im = (np.round(0.299*red + 0.587*green + 0.114*blue)).astype('uint8')
    return grayscale_im
  else:
    grayscale_im = (np.round(0.21*red + 0.72*green + 0.07*blue)).astype('uint8')
    return grayscale_im 
  
  
  #converting to grayscale and printing the outcomes
grayscale_avr, grayscale_w, grayscale_lu = [transf_RBG(eye_arr, RBG_conv_met) for RBG_conv_met in \
                                            ["Average", "Weighted_average", "Luminosity"] ]
show_images([grayscale_avr, grayscale_w, grayscale_lu], suptitle = \
            "Grayscale Images based on: Average, Weighted Average, and Luminosity methods", \
            titles = ["Average", "Weighted Average", "Luminosity"])