Image Processing¶

This tutorial explains how images can be handled and transformed with the Image class.

Note

All operations on an Image return a new Image. The original Image will not be changed.

Load data into an Image:¶

In [1]:

from safeds.data.image.containers import Image

plane = Image.from_file("data/plane.png")
plane

from safeds.data.image.containers import Image plane = Image.from_file("data/plane.png") plane

Out[1]:

Process the image¶

1. Resize the Image to have the width 284 and height 160:

In [2]:

plane.resize(284, 160)

plane.resize(284, 160)

Out[2]:

2. Convert the Image to grayscale:

In [3]:

plane.convert_to_grayscale()

plane.convert_to_grayscale()

Out[3]:

3. Crop the Image to be 200x200 with the top-left corner being at (255, 30):

In [4]:

plane.crop(x=255, y=30, width=200, height=200)

plane.crop(x=255, y=30, width=200, height=200)

Out[4]:

4. Flip the Image horizontally (or vertically):

In [5]:

plane.flip_left_and_right()

plane.flip_left_and_right()

Out[5]:

5. Adjust the brightness of the Image.

Giving a factor below 1 will result in a darker Image, a factor above 1 will return a brighter Image.

In [6]:

plane.adjust_brightness(1.5)

plane.adjust_brightness(1.5)

Out[6]:

6. Adjust the contrast of the Image.

Giving a factor below 1 will decrease the contrast of the Image, a factor above 1 will increase the contrast of the Image.

In [7]:

plane.adjust_contrast(1.5)

plane.adjust_contrast(1.5)

Out[7]:

7. Adjust the color balance of the Image.

A factor of 0 will return a black and white Image, a factor of 1 will return a copy of the original Image.

In [8]:

plane.adjust_color_balance(0.5)

plane.adjust_color_balance(0.5)

Out[8]:

8. Blur the Image:

The higher the radius, the blurrier the Image gets. The radius defines the amount of pixels combined in each direction.

In [9]:

plane.blur(5)

plane.blur(5)

Out[9]:

9. Sharpen the Image:

The factor defines the sharpness of the returned Image.

In [10]:

plane.sharpen(5)

plane.sharpen(5)

Out[10]:

10. Invert the colors of the Image:

In [11]:

plane.invert_colors()

plane.invert_colors()

Out[11]:

11. Rotate the Image to the right (or the left):

In [12]:

plane.rotate_right()

plane.rotate_right()

Out[12]:

12. Convert the Image to grayscale and highlight the edges:

In [13]:

plane.find_edges()

plane.find_edges()

Out[13]:

13. Add noise to the Image. A higher standard_deviation will result in a noisier Image:

In [14]:

plane.add_noise(standard_deviation=0.1)

plane.add_noise(standard_deviation=0.1)

Out[14]: