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‎Codes/Converting_RGB_to_GreyScale.py

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# File: Converting_RGB_to_GreyScale.py
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# Description: Opening RGB image as array, converting to GreyScale and saving result into new file
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# Environment: PyCharm and Anaconda environment
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#
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# MIT License
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# Copyright (c) 2018 Valentyn N Sichkar
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# github.com/sichkar-valentyn
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#
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# Reference to:
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# Valentyn N Sichkar. Image processing in Python // GitHub platform. DOI: 10.5281/zenodo.1343603
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# Opening RGB image as array, converting to GreyScale and saving result into new file
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# Importing needed libraries
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import numpy as np
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from PIL import Image
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import matplotlib.pyplot as plt
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from skimage import color
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from skimage import io
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import scipy.misc
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# Creating an array from image data
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image_RGB = Image.open("images/eagle.jpg")
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image_np = np.array(image_RGB)
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# Checking the type of the array
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print(type(image_np)) # <class 'numpy.ndarray'>
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# Checking the shape of the array
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print(image_np.shape)
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# Showing image with every channel separately
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channel_R = image_np[:, :, 0]
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channel_G = image_np[:, :, 1]
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channel_B = image_np[:, :, 2]
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# Creating a figure with subplots
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f, ax = plt.subplots(nrows=2, ncols=2)
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# ax is (2, 2) np array and to make it easier to read we use 'flatten' function
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# Or we can call each time ax[0, 0]
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ax0, ax1, ax2, ax3 = ax.flatten()
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# Adjusting first subplot
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ax0.imshow(channel_R, cmap='Reds')
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ax0.set_xlabel('')
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ax0.set_ylabel('')
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ax0.set_title('Red channel')
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# Adjusting second subplot
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ax1.imshow(channel_G, cmap='Greens')
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ax1.set_xlabel('')
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ax1.set_ylabel('')
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ax1.set_title('Green channel')
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# Adjusting third subplot
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ax2.imshow(channel_B, cmap='Blues')
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ax2.set_xlabel('')
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ax2.set_ylabel('')
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ax2.set_title('Blue channel')
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# Adjusting fourth subplot
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ax3.imshow(image_np)
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ax3.set_xlabel('')
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ax3.set_ylabel('')
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ax3.set_title('Original image')
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# Function to make distance between figures
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plt.tight_layout()
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# Giving the name to the window with figure
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f.canvas.set_window_title('Eagle image in three channels R, G and B')
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# Showing the plots
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plt.show()
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# Converting RGB image into GrayScale image
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# Using formula:
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# Y' = 0.299 R + 0.587 G + 0.114 B
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image_RGB = Image.open("images/eagle.jpg")
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image_np = np.array(image_RGB)
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image_GreyScale = image_np[:, :, 0] * 0.299 + image_np[:, :, 1] * 0.587 + image_np[:, :, 2] * 0.114
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# Checking the type of the array
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print(type(image_GreyScale)) # <class 'numpy.ndarray'>
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# Checking the shape of the array
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print(image_GreyScale.shape)
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# Giving the name to the window with figure
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plt.figure('GreyScaled image from RGB')
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# Showing the image by using obtained array
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plt.imshow(image_GreyScale, cmap='Greys')
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plt.show()
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# Preparing array for saving - creating three channels with the same data in each
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# Firstly, creating array with zero elements
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# And by 'image_GreyScale.shape + tuple([3])' we add one more element '3' to the tuple
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# Now the shape will be (1080, 1920, 3) - which is tuple type
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image_GreyScale_with_3_channels = np.zeros(image_GreyScale.shape + tuple([3]))
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# Secondly, reshaping GreyScale image from 2D to 3D
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x = image_GreyScale.reshape((1080, 1920, 1))
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# Finally, writing all data in three channels
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image_GreyScale_with_3_channels[:, :, 0] = x[:, :, 0]
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image_GreyScale_with_3_channels[:, :, 1] = x[:, :, 0]
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image_GreyScale_with_3_channels[:, :, 2] = x[:, :, 0]
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# Saving image into a file from obtained 3D array
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scipy.misc.imsave("images/result_1.jpg", image_GreyScale_with_3_channels)
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# Checking that image was written with three channels and they are identical
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result_1 = Image.open("images/result_1.jpg")
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result_1_np = np.array(result_1)
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print(result_1_np.shape)
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print(np.array_equal(result_1_np[:, :, 0], result_1_np[:, :, 1]))
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print(np.array_equal(result_1_np[:, :, 1], result_1_np[:, :, 2]))
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# Showing saved resulted image
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# Giving the name to the window with figure
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plt.figure('GreyScaled image from RGB')
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# Here we don't need to specify the map like cmap='Greys'
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plt.imshow(result_1_np)
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plt.show()
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# Another way to convert RGB image into GreyScale image
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image_RGB = io.imread("images/eagle.jpg")
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image_GreyScale = color.rgb2gray(image_RGB)
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# Checking the type of the array
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print(type(image_GreyScale)) # <class 'numpy.ndarray'>
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# Checking the shape of the array
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print(image_GreyScale.shape)
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# Giving the name to the window with figure
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plt.figure('GreyScaled image from RGB')
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# Showing the image by using obtained array
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plt.imshow(image_GreyScale, cmap='Greys')
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plt.show()
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# Saving converted image into a file from processed array
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scipy.misc.imsave("images/result_2.jpg", image_GreyScale)
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# One more way for converting
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image_RGB_as_GreyScale = io.imread("images/eagle.jpg", as_gray=True)
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# Checking the type of the array
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print(type(image_RGB_as_GreyScale)) # <class 'numpy.ndarray'>
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# Checking the shape of the array
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print(image_RGB_as_GreyScale.shape)
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# Giving the name to the window with figure
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plt.figure('GreyScaled image from RGB')
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# Showing the image by using obtained array
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plt.imshow(image_RGB_as_GreyScale, cmap='Greys')
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plt.show()
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# Saving converted image into a file from processed array
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scipy.misc.imsave("images/result_3.jpg", image_RGB_as_GreyScale)

‎Codes/Opening_png_jpg.py

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# File: Opening_png_jpg.py
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# Description: Testing to open images of different format
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# Environment: PyCharm and Anaconda environment
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#
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# MIT License
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# Copyright (c) 2018 Valentyn N Sichkar
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# github.com/sichkar-valentyn
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#
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# Reference to:
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# Valentyn N Sichkar. Image processing in Python // GitHub platform. DOI: 10.5281/zenodo.1343603
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# Testing to open images of different format
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import tkinter as tk
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from PIL import Image, ImageTk
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# Option 1 - opening .png images
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# Establishing 'root' as the 'Tk' window
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root = tk.Tk()
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# Uploading image from file
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image_1 = tk.PhotoImage(file="images/eagle.png")
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# Creating a 'Label' object that contains uploaded image
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label = tk.Label(root, image=image_1)
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# Packing 'Label' into 'Tk' window
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label.pack()
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# Setting the title
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root.title('Opening .png image')
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# root.geometry("800x600")
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# Starts loop with event
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root.mainloop()
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# Option 2 - opening .jpg images
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# Establishing 'root' as the 'Tk' window
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root = tk.Tk()
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# Uploading image from file
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image_2 = Image.open("images/eagle.jpg")
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# Creating a 'Label' object that contains uploaded image
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label = tk.Label(root)
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label.image = ImageTk.PhotoImage(image_2)
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label['image'] = label.image
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# Packing 'Label' into 'Tk' window
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label.pack()
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# Setting the title
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root.title('Opening .jpg image')
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# Starts loop with event
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root.mainloop()

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