-
Notifications
You must be signed in to change notification settings - Fork 1
Expand file tree
/
Copy pathnegative.py
More file actions
35 lines (24 loc) · 15.8 KB
/
negative.py
File metadata and controls
35 lines (24 loc) · 15.8 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
//you can create anye images negative images
'''Note:Before running this code please check that your python compiler has image module installed and if you want to test it on online compiler use trinket.io'''
#This is doing negative of an image
import image
img = image.Image("data:image/jpeg;base64,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")
win = image.ImageWin(img.getWidth(), img.getHeight())
img.draw(win)
img.setDelay(1,15) # setDelay(0) turns off animation
for row in range(img.getHeight()):
for col in range(img.getWidth()):
p = img.getPixel(col, row)
newred = 255 - p.getRed()
newgreen = 255 - p.getGreen()
newblue = 255 - p.getBlue()
newpixel = image.Pixel(newred, newgreen, newblue)
img.setPixel(col, row, newpixel)
img.draw(win)
win.exitonclick()
#Description:
'''Let’s take a closer look at the code. After importing the image module, we create an image object called img that represents a typical digital photo. We will update each pixel in this image from top to bottom, left to right, which you should be able to observe. You can change the values in setDelay to make the program progress faster or slower.
Lines 8 and 9 create the nested iteration that we discussed earlier. This allows us to process each pixel in the image. Line 10 gets an individual pixel.
Lines 12-14 create the negative intensity values by extracting the original intensity from the pixel and subtracting it from 255. Once we have the newred, newgreen, and newblue values, we can create a new pixel (Line 15).
Finally, we need to replace the old pixel with the new pixel in our image. It is important to put the new pixel into the same location as the original pixel that it came from in the digital photo.
Try to change the program above so that the outer loop iterates over the columns and the inner loop iterates over the rows. We still create a negative image, but you can see that the pixels update in a very different order.'''