Python-3.4.3/C3/Image-manipulation-using-Arrays/English-timed

Time	Narration
00:01	Welcome to the spoken tutorial on Image manipulation using arrays.
00:07	In this tutorial, you will learn to - Read images into arrays Perform processing on them using simple array manipulations
00:19	To record this tutorial, I am using Ubuntu Linux 16.04 operating system Python 3.4.3 and IPython 5.1.0
00:35	To practise this tutorial, you should know how to run basic Python commands on the ipython console and access parts of arrays.
00:46	If not, see the relevant Python tutorials on this website.
00:51	Please download the files Squares.png and Python.png from the Code files link of this tutorial.
01:00	Save the files in the current working directory.
01:04	First we will learn how to access parts of an array.
01:09	For this purpose, we shall use the image Squares.png present in the current working directory.
01:16	Let us start ipython. Open the terminal.
01:21	Type ipython3 and press Enter.
01:26	From here onwards remember to press the Enter key after typing every command on the terminal.
01:33	To read an image into an array, we use the imread command.
01:38	Let us now read the data in Squares.png into the array img.
01:44	Type, import matplotlib.pyplot as plt
01:51	Then type, img is equal to plt.imread inside brackets inside single quotes Squares.png
02:02	In the first line pyplot is imported from matplotlib module with plt as alias.
02:09	This is to make use of methods like imread which are part of pyplot.
02:15	We can see the image by using the functions imshow followed by show.
02:21	Type, plt.imshow inside brackets img Then type, plt.show open and close brackets
02:33	It displays the image in a separate popup window.The original image is in the black and white.
02:41	But here we do not see black and white, because imshow has mapped black and white to different colors.
02:49	This can be changed by using a different color map.
02:53	Close the image window to return to the IPython console.
02:58	In order to see the original black and white image type, plt.imshow inside brackets img comma cmap is equal to inside single quotes gray
03:13	Then type, plt.show open and close brackets. Now we can see the image in black and white.
03:22	Close the image now.
03:24	To see what has been read into img variable, type,img. We can see that an array is displayed.
03:34	To check the dimensions of any array, we can use shape function. Type, img.shape
03:44	As we can see, we got the dimensions of the image. The image Squares.png has the dimensions of 300 by 300.
03:54	Now, we wish to obtain the top left quarter of the image.
03:59	To do this, we need to access top half of the rows and left half of the columns of the array.
04:06	We know that the shape of the image is 300 by 300.
04:11	For top-left corner of the image we need first 150 rows and the first 150 columns.
04:19	So type, img inside square brackets colon 150 comma colon 150
04:27	This gives us the top-left corner of the image.
04:32	We use the imshow command to see the slice we obtained in the form of an image. Type as shown.
04:42	We got the required slice now. Close this image.
04:48	Pause the video. Try this exercise and then resume the video.
04:54	Obtain the square in the center of the image Squares.png with size 150 by 150.
05:02	Since we need to get center of the image, we take rows from one-fourth to three-fourth of the rows i.e. from 75 to 225 and columns from one-fourth to three-fourth of the columns, i.e. from 75 to 225
05:21	Switch to the terminal for the solution.
05:25	Type as shown. Hence, we get the center of the image. Close this image.
05:34	You can also save the sliced image array to a new variable.
05:39	Type, img1 is equal to img inside square brackets 75 colon 225 comma 75 colon 225] Then to see the image type as shown.
05:56	Close this image window
05:59	We also know how to stride over an array.
06:03	For that we can drop alternate rows and columns out of the image.
06:08	Type, img inside square brackets colon colon 2 comma colon colon 2
06:16	To see this image, type as shown. We can see that the scale has reduced.
06:24	We can observe some blurring near the edges if you scale it down further.
06:30	Close the image window to return to the IPython console.
06:35	To increase the step to 4, type as shown.
06:41	Close the image window to return to the IPython console.
06:45	We shall use the Python.png present in the current working directory.Now we have an RGB image.
06:54	Let us slice the image and see what happens.
06:58	Type as shown. We can see the image.
07:03	Close the image window to return to the IPython console.
07:07	To check the dimensions of img, we can use shape function.
07:12	Type, img.shape
07:16	The third number shows that there are 4 channels. These are corresponding to red, green, blue, and transparency value of the image.
07:28	The first number shows that the height of the image is 600. The second number shows that the width of the image is also 600.
07:39	Now we will slice the red channel of the array.
07:43	Type, plt.imshow inside brackets img inside square brackets colon comma colon comma 0
07:53	Then type, plt.show open and close brackets.
08:00	We got the required red channel of the array.
08:04	Close this image.
08:06	This brings us to the end of this tutorial. Let us summarize.
08:12	In this tutorial, we have learned to, Read images into arrays and manipulate them.
08:19	Here is a self assessment question for you to solve
08:23	The shape of the variable img is (600, 600, 4).
08:29	What will be the shape of img1 if img1 is equal to img inside brackets colon colon 2 comma colon colon 4
08:39	And the answer is, (300, 150, 4)
08:45	Please post your timed queries in this forum.
08:49	Please post your general queries on Python in this forum.
08:54	FOSSEE team coordinates the TBC project.
08:58	Spoken Tutorial Project is funded by NMEICT, MHRD, Govt. of India. For more details, visit this website.
09:07	This is Priya from IIT Bombay signing off. Thanks for watching.

Contributors and Content Editors

Pratik kamble