# coding: utf-8

# In[1]:

import cv2

import numpy as np

import imutils

import argparse

# In[2]:

img = cv2.imread('./datasets/flower3.jpg')

cv2.imshow("Original_Image", img)

cv2.waitKey(0)

# In[3]:

#Splitting RGB components of an image

#Individual channel investigation hepls in understanding edge detection and thresholding

(B, G, R) = cv2.split(img) # as RGB image is stored in reverse channel order

#Showing individual channels in grayscale format

cv2.imshow("Red_Component", R)

cv2.imshow('Blue_Component', B)

cv2.imshow('Green_Component', G)

cv2.waitKey(0)

# In[4]:

#Merging the channels back

merged = cv2.merge([B, G, R])

cv2.imshow("Merged_Image", merged)

cv2.waitKey(0)

# In[5]:

#Merging the channels in reverse order - changes the color component of original image

cv2.imshow("Merged_Image2", cv2.merge([R, G, B]))

cv2.waitKey(0)

# In[8]:

#Visualize each channel in its corresponding color

zeros = np.zeros(img.shape[:2], dtype='uint8')

cv2.imshow("Red", cv2.merge([zeros, zeros, R]))

cv2.imshow("Green", cv2.merge([zeros, G, zeros]))

cv2.imshow("Blue", cv2.merge([B, zeros, zeros]))

cv2.waitKey(0)

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