Difference between revisions of "Python-3.4.3/C3/Image-manipulation-using-Arrays/English"

Objectives

• Read images into arrays
• Perform processing on them using simple array manipulations

System Specifications

• Ubuntu Linux 16.04 operating system
• Python 3.4.3 and
• IPython 5.1.0

Prerequisite slide

• run basic Python commands on the ipython console and
• access parts of arrays.

If not, see the relevant Python tutorials on this website.

Download files

Save the files in the current working directory.

For this purpose, we shall use the image Squares.png present in the current working directory.

Open the terminal.

From here onwards remember to press the Enter key after typing every command on the terminal.

import matplotlib.pyplot as plt

img = plt.imread('Squares.png')

Highlight the first line

Highlight pyplot

Let us now read the data in Squares.png into the array img.

Type,

import matplotlib.pyplot as plt

Then type,

img is equal to plt.imread inside brackets inside single quotes Squares.png

In the first line pyplot is imported from matplotlib module with plt as alias.

This is to make use of methods like imread which are part of pyplot.

plt.imshow(img)

plt.show()

Type,

plt.imshow inside brackets img

Then type,

plt.show open and close brackets

It displays the image in a separate popup window.

The original image is in the black and white.

But here we do not see black and white, because imshow has mapped black and white to different colors.

This can be changed by using a different color map.

plt.imshow(img, cmap='gray')

plt.show()

plt.imshow inside brackets img comma cmap is equal to inside single quotes gray

Then type,

plt.show open and close brackets

Now we can see the image in black and white.

img

img

We can see that an array is displayed.

img.shape

Highlight 300x300

Type,

img.shape

As we can see, we got the dimensions of the image.

The image Squares.png has the dimensions of 300 by 300.

Squares.png

Point at top-left quadrant of the image

To do this, we need to access top half of the rows and left half of the columns of the array.

We know that the shape of the image is 300 by 300.

For top-left corner of the image we need first 150 rows and the first 150 columns.

img[:150, :150]

Highlight output

img inside square brackets colon 150 comma colon 150

This gives us the top-left corner of the image.

plt.imshow(img[:150,:150])

plt.show()

Type as shown.

We got the required slice now.

Try this exercise and then resume the video.

Exercise 1

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

plt.imshow(img[75:225, 75:225])

plt.show()

Hence, we get the center of the image.

img1 = img[75:225, 75:225]

plt.imshow(img1)

plt.show()

Type,

img1 is equal to img inside square brackets 75 colon 225 comma 75 colon 225]

Then to see the image type as shown.

img[::2, ::2]

For that we can drop alternate rows and columns out of the image.

Type,

img inside square brackets colon colon 2 comma colon colon 2

plt.imshow(img[::2, ::2])

plt.show()

We can see that the scale has reduced.

We can observe some blurring near the edges if you scale it down further.

plt.imshow(img[::4, ::4])

plt.show()

Now we have an RGB image.

img=plt.imread('Python.png')

plt.imshow(img)

plt.show()

Type as shown.

We can see the image.

img.shape

Highlilght the third number

Highlilght the first number

Type,

img.shape

The third number shows that there are 4 channels.

These are corresponding to red, green, blue, and transparency value of the image.

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.

plt.imshow(img[:,:,0])

plt.show()

Type,

plt.imshow inside brackets img inside square brackets colon comma colon comma 0

Then type,

plt.show open and close brackets.

We got the required red channel of the array.

Summary slide

In this tutorial, we have learned to,

• Read images into arrays and manipulate them.

The shape of the variable img is (600, 600, 4).

What will be the shape of img1 if img1 is equal to img inside brackets colon colon 2 comma colon colon 4

For more details, visit this website.