COMPSCI 101 S1 2014 Principles of Programming

1. COMPSCI 101 S1 2014Principles of Programming 30 Image processing

2. Recap • Some Key Image Functions • pickAFile() • writePictureTo(picture, filename) • makeEmptyPicture(height,width) • show(picture) • getPixel(picture,x,y) • getPixels(picture) • getHeight(picture) • getWidth(picture) • makeColor(r, g, b) • makeLighter(color) • makeDarker(color) • getColor(pixel) • setColor(pixel, color) • getRed(pixel) • setRed(pixel, r) • getGreen(pixel) • setGreen(pixel, r) • getBlue(pixel) • setBlue(pixel, r) COMPSCI101

3. Recap: Using the ImageLibrary Module • The ImageLibraryModule • The module allows students to load, transform, and save digital images. • You must install pygamein order to use this module. • http://www.lfd.uci.edu/~gohlke/pythonlibs/#pygame • How to use it? • Download the file (ImageLibrary.py) from compsci101 course website and save it in your working directory • Add an import statement in your py file. • Download our sample images to your working directory • Picture class represents a picture as a two-dimensional grid of RGB values We have installed pygame only to the machines in room 279! from ImageLibrary import * COMPSCI101

4. Learning outcomes • At the end of this lecture, students should be able to: • Manipulate images using a provided image library • Using a list of Pixels • Using a nested loop structure • Examples and Exercises: • Case Study 1: Reducing the Red Colour • Case Study 2: Eliminating Colours • Exercise 1: Lightening an Image • Case Study 3: Mirroring an Image horizontally • Case Study 4: Adding Borders • Exercise 2: Mirroring an Image vertically COMPSCI101

5. A Loop Pattern for Traversing a Grid • There are two approaches to move through the pixels • Using a list of Pixel objects • Using one pixel at a time based on a row and column value in a nested loop structure • Many image-processing algorithms use a nested loop structure to traverse a two-dimensional grid of pixels • Why are you learning both approaches? • To "flip" an image, it is easier to access individual pixels in specific rows and columns. • If you are making global changes in colourto your entire image, you can grab all of the pixels (in a list). COMPSCI101

6. Simple Manipulation of Images for pixel in getPixels(pict): apply_a_function(pixel) • Using a list of Pixels • Case Study 1: Reducing the Red Colour • Apply a global change in colourto the entire image • E.g. reduce the red component by half • Exercise 1: Lightening • Apply a global change in colourto the entire image • E.g. add “40” to all colour components • Using a nested loop structure • Case Study 3: Mirroring an Image horizontally • The left-hand side of the image is mirrored onto the right-hand side. • i.e. We are taking half the picture and flipping it. • Exercise 2: Mirroring an Image vertically for x in range(width): for y in range(height): pixel = getPixel(pict, x, y) apply_a_function(pixel) COMPSCI101

7. Case Study 1Reducing the Red Colour • Task: • Complete the reduce_red() function which takes a pixel as a parameter and reduces the red component by half. • Arguments: pixel • Example: pict = makePicture("caterpillarSmall.jpg") for pixel in getPixels(pict): reduce_red(pixel) COMPSCI101

8. Case Study 1Reducing the Red Colour Demo 1 • Algorithm COMPSCI101

9. Case Study 2Eliminating Colours • Task: • Complete the to_red() function which takes a pixel as a parameter and eliminates all colour components except red • Arguments: pixel • Example: • RGB of the first pixel (113, 123, 60) pict = makePicture("caterpillarSmall.jpg") for pixel in getPixels(pict): to_red(pixel) • (113, 0, 0) COMPSCI101

10. Case Study 2Eliminating Colours Demo 2 • Algorithm COMPSCI101

11. Exercise1Lightening • Task: • Complete the following main() function which lightens the picture. • The image library has a function called makeLighter(color) that lightens each part of the colour- in fact what it does is subtractadd 40 to the red, green and blue values • Example: • (153, 163, 100) • (113, 123, 60) def main(): pict = makePicture("caterpillarSmall.jpg") for pixel in getPixels(pict): show(pict) COMPSCI101

12. Exercise1Lightening Ex 1 • Algorithm COMPSCI101

13. Case Study 3Mirroring an Image horizontally • Task: • Complete the mirror_horizontally() function which takes a picture as a parameter. The left-hand side of the picture is mirrored onto the right-hand side. • Arguments: A picture • Example: pict = makePicture("caterpillarSmall.jpg") mirror_horizontally(pict) COMPSCI101

14. Case Study 3Mirroring an Image horizontally • The left-hand side is mirrored onto the right-hand side. The pixel is "flipped" to look like a reflection. COMPSCI101

15. Case Study 3Mirroring an Image horizontally • Algorithm How? COMPSCI101

16. Case Study 3Mirroring an Image horizontally Demo 3 • Algorithm COMPSCI101

17. Exercise 2Mirroring an Image Vertically • Can you adapt the mirror_horizontally() to mirror a picture vertically? • Task: • Complete the mirror_vertically() function which takes a picture as a parameter. The top side of the picture is mirrored onto the bottom side. • Arguments: A picture COMPSCI101

18. Case Study 4Adding Borders • Task: • Complete the add_two_borders() function which takes a picture as a parameter. The function should add a top and bottom 5-pixel thick borders to the image • Arguments: A picture • Example: pict = makePicture("caterpillarSmall.jpg") add_two_borders(pict) COMPSCI101

19. Case Study 4Adding Borders Demo 4 • Adding a top border: Adding a bottom border COMPSCI101

20. Summary • Some Key Image Functions • pickAFile() • writePictureTo(picture, filename) • makeEmptyPicture(height,width) • show(picture) • getPixel(picture,x,y) • getPixels(picture) • getHeight(picture) • getWidth(picture) • makeColor(r, g, b) • makeLighter(color) • makeDarker(color) • getColor(pixel) • setColor(pixel, color) • getRed(pixel) • setRed(pixel, r) • getGreen(pixel) • setGreen(pixel, r) • getBlue(pixel) • setBlue(pixel, r) COMPSCI101