1. Intro CS and Media Computation1 Barb Ericson Georgia Institute of Technology Feb 2010 Introduction to Computer Science and Media Computation

2. 06-Intro-Object-Oriented-Prog2 Learning Goals What is Computer Science? What are programming languages? What do computers understand? What is Media Computation?

3. 06-Intro-Object-Oriented-Prog3 What is Computer Science? The study of process, how to specify what is to be done and define the stuff being processed. You can say that is the study of computational recipes –Ones that can be executed on a computer –A recipe that runs on a computer is called a program

4. 06-Intro-Object-Oriented-Prog4 What do Computer Scientists do? Study if there are better ways to write recipes –Algorithms – textual description of how to solve a problem Study how to structure the data in the recipes –Data structures and databases Determine if there are recipes that can't be written? That make machines intelligent? –Theory, artificial intelligence Study how to make computers easier for people to use –Human-computer interface Study how computers communicate with each other –Networking Study how to create 3D models and simulations –Graphics and scientific computing

5. 06-Intro-Object-Oriented-Prog5 Multimedia CS1 in Python Focus: Learning programming and CS concepts within the context of media manipulation and creation – Converting images to grayscale and negatives, splicing and reversing sounds, writing programs to generate HTML, creating movies out of Web-accessed content. – Computing for communications, not calculation

6. 06-Intro-Object-Oriented-Prog6 Python as the programming language Used in commercial contexts –IL&M, Google, Nextel, etc. Minimal syntax Looks like other programming languages –Potential for transfer Actually using Jython which is Python with Java underneath

7. 06-Intro-Object-Oriented-Prog7 Some Computer Science Topics inter-mixed algorithms across media –Sampling a picture (to scale it) is the same algorithm as sampling a sound (to shift frequency) –Blending two pictures (fading one into the other) and two sounds is the same algorithm. representations and mappings (Goedel) –From samples to numbers (and into Excel), through a mapping to pixel colors

8. 06-Intro-Object-Oriented-Prog8 We will program in JES JES: Jython Environment for Students A simple editor (for entering in our programs or recipes): the program area A command area for entering in commands for Python to execute.

9. 06-Intro-Object-Oriented-Prog9 Using JES – Try the following >>> print 3 + 5 >>> print 23.2 / 3 >>> print 1 / 3 >>> print 1.0 / 3 >>> print 10 % 3 >>> print "Hello" >>> print "Hello" + "Barb" >>> print 10 > 3 >>> print 3 > 10 Print will print out the result from the following expression

10. 06-Intro-Object-Oriented-Prog10 Did any answer surprise you? Integer division results in an integer answer 1 / 3 = 0 –The values after the decimal point are thrown away –If you want a floating point result using a floating point value in the expression (1.0 / 3) You can append strings one after the other, but this doesn't add any spaces >>> print "Hello" + "Barb" HelloBarb Python uses 0 for false and 1 for true >>> print 10 > 3 1 >>> print 3 > 10 0

11. 06-Intro-Object-Oriented-Prog11 Command Area Editing Up/down arrows walk through command history You can edit the line at the bottom –and then hit Return/Enter –that makes that last line execute

12. 06-Intro-Object-Oriented-Prog12 Demonstrating JES for files and sounds >>> print pickAFile() c:/ip-book/mediasources/barbara.jpg >>> print makePicture(pickAFile()) Picture, filename c:/ip-bookmediasources/barbara.jpg height 294 width 222 >>> show(makePicture(pickAFile())) None >>> print pickAFile() C:/ip-book/mediasources/hello.wav >>> print makeSound(pickAFile()) Sound of length 54757 >>> print play(makeSound(pickAFile())) None

13. 06-Intro-Object-Oriented-Prog13 Naming parts – declaring variables You can name the result from a function call –And then use the name as input to other functions myFile = pickAFile() # name the picked file myPict = makePicture(myFile) # name the picture show(myPict) The value associated with that name is used –= doesn't mean equals here but assign the value for myFile to the result of pickAFile()

14. 06-Intro-Object-Oriented-Prog14 Quick Calculation What if an item is 30% off and you also have a coupon for an additional 20% off the sale price? –If the original cost was $45.00, how much is the price after the 30% and then how much do you pay with the additional 20% off? –Use the python command area to figure it out Name the result of each calculation

15. 06-Intro-Object-Oriented-Prog15 Making our own functions To make a function, use the command def Then, the name of the function, and the names of the input values between parentheses (“(input1)”) End the line with a colon (“:”) The body of the recipe is indented (Hint: Use three spaces) –That’s called a block

16. 06-Intro-Object-Oriented-Prog16 Making functions the easy way Get something working by typing commands in the command window (bottom half of JES) Enter the def command in the editing window (top part of JES) Copy-paste the right commands up into the recipe

17. 06-Intro-Object-Oriented-Prog17 A recipe for playing picked sound files def pickAndPlay(): myFile = pickAFile() mySound = makeSound(myFile) play(mySound) Note: myFile and mySound, inside pickAndPlay(), are completely different from the same names in the command area. We say that they are in a different scope.

18. 06-Intro-Object-Oriented-Prog18 Blocking is indicated for you in JES Statements that are indented the same, are in the same block. Statements in the same block as the cursor are enclosed in a blue box. What happens when you type pickAndShow is that all statements in the block will be executed.

19. 06-Intro-Object-Oriented-Prog19 Image Processing Goals: –Give you the basic understanding of image processing, including psychophysics of sight, –Identify some interesting examples to use

20. 06-Intro-Object-Oriented-Prog20 We perceive light different from how it actually is Color is continuous –Visible light is in the wavelengths between 370 and 730 nanometers That’s 0.00000037 and 0.00000073 meters But we perceive light with color sensors that peak around 425 nm (blue), 550 nm (green), and 560 nm (red). Our brain figures out which color is which by figuring out how much of each kind of sensor is responding One implication: We perceive two kinds of “orange” — one that’s spectral and one that’s red+yellow (hits our color sensors just right) Dogs and other simpler animals have only two kinds of sensors –They do see color. Just less color.

21. 06-Intro-Object-Oriented-Prog21 Luminance vs. Color We perceive borders of things, motion, depth via luminance –Luminance is not the amount of light, but our perception of the amount of light. –We see blue as “darker” than red, even if same amount of light. Much of our luminance perception is based on comparison to backgrounds, not raw values. Luminance is actually color blind. Completely different part of the brain.

22. 06-Intro-Object-Oriented-Prog22 Digitizing pictures We digitize pictures into lots of little dots Enough dots and it looks like a continuous whole to our eye –Our eye has limited resolution –Our background/depth acuity is particularly low Each picture element is referred to as a pixel Pixels are picture elements –Each pixel object knows its color –It also knows where it is in its picture

23. 06-Intro-Object-Oriented-Prog23 Exploring Pictures >>> file = pickAFile() >>> beachPict = makePicture(file) >>> explore(beachPict) Zoom in to see individual pixels Move the cursor to see the x and y values Look at the red, green, and blue values

24. 06-Intro-Object-Oriented-Prog24 Encoding color Each pixel encodes color at that position in the picture Lots of encodings for color –Printers use CMYK: Cyan, Magenta, Yellow, and blacK. –Others use HSB for Hue, Saturation, and Brightness (also called HSV for Hue, Saturation, and Value. We’ll use the most common for computers –RGB: Red, Green, Blue

25. 06-Intro-Object-Oriented-Prog25 Encoding Color: RGB In RGB, each color has three component colors: –Amount of redness –Amount of greenness –Amount of blueness Each does appear as a separate dot on most devices, but our eye blends them. In most computer-based models of RGB, a single byte (8 bits) is used for each –So a complete RGB color is 24 bits, 8 bits of each

26. 06-Intro-Object-Oriented-Prog26 Making Colors with Light Type >>> myColor = pickAColor() Try to create –White –Black –Yellow –Red –Brown –Purple

27. 06-Intro-Object-Oriented-Prog27 Basic Picture Functions makePicture(filename) creates and returns a picture object, from the JPEG file at the filename show(picture) displays a picture in a window explore(picture) makes a copy of the picture and shows it in the explorer window We’ll learn functions for manipulating pictures like getColor, setColor, and repaint

28. 06-Intro-Object-Oriented-Prog28 Writing a recipe: Making our own functions To make a function, use the command def Then, the name of the function, and the names of the input values between parentheses (“(input1)”) End the line with a colon (“:”) The body of the recipe is indented (Hint: Use two spaces) Your function does NOT exist for JES until you load it

29. 06-Intro-Object-Oriented-Prog29 Saving Functions in Files Click on File and then Save Program –Name it with some file name and.py at end You can define more than one function in a file –Maybe call these pictureFunctions.py You can later open these files up –And use the Load Program button to load all functions in the file You can build a library of python functions for working with pictures, sounds, movies, etc

30. 06-Intro-Object-Oriented-Prog30 Modifying a Pixel Color You can get the amount of red, green, or blue –redValue = getRed(pict) –greenValue = getGreen(pict) –blueValue = getBlue(pict) You can change the amount of red, green, or blue –setRed(pict,value) –setGreen(pict,value) –setBlue(pictValue)

31. 06-Intro-Object-Oriented-Prog31 Modifying Colors You can also get the color from a pixel –myColor = getColor(pixel) You can create a new color by giving values for red, green, and blue from 0 to 255 –newColor = makeColor(255,0,0) You can set a color using –setColor(pixel,newColor)

32. 06-Intro-Object-Oriented-Prog32 How to change lots of pixels? If we want to change all the pixels in a picture how can we do that? –In a 640 x 480 picture that is 307,200 pixels –That sounds too long to do one at a time Computers are very fast and can process billions of instructions per second –But we wouldn't want to name each pixel or modify the color on each one by typing in the commands 307,200 times We can get an array of pixels to process –Using getPixels(picture) and loop through the pixels in the array –It gets the first row of pixels followed by the second row and so on

33. 06-Intro-Object-Oriented-Prog33 What is an array? Space in memory for many values of the same type –Numbers, pictures, pixels, etc You can refer to the elements of an array using an index –Starting with 0 for the first element –And length – 1 for the last element

34. 06-Intro-Object-Oriented-Prog34 Processing Pixels in an Array >>> file="C:/ip -book/mediasources/barbara.jpg" >>> pict=makePicture(file) >>> show(pict) >>> pixels = getPixels(pict) >>> setRed(pixels [0], getRed(pixels [0]) * 0.5) >>> setRed(pixels [1], getRed(pixels [1]) * 0.5) >>> setRed(pixels [2], getRed(pixels [2]) * 0.5) >>> setRed(pixels [3], getRed(pixels [3]) * 0.5) >>> setRed(pixels [4], getRed(pixels [4]) * 0.5) >>> setRed(pixels [5], getRed(pixels [5]) * 0.5) >>> repaint(pict)

35. 06-Intro-Object-Oriented-Prog35 Use a loop! Our first picture recipe def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5) Used like this: >>> file="c:/ip-book/mediasources/katie.jpg" >>> picture=makePicture(file) >>> explore(picture) >>> decreaseRed(picture) >>> explore(picture)

36. 06-Intro-Object-Oriented-Prog36 It’s not iteration—it’s a set operation Research in the 1970’s found that people are better at set operations than iteration. –For all records, get the last name, and if it starts with “G” then… => HARD! –For all records where the last name starts with “G”… => Reasonable! Because the Python for loop is a forEach, we can start out with treating it as a set operation: –“For all pixels in the picture…”

37. 06-Intro-Object-Oriented-Prog37 How do you make an omelet? Something to do with eggs… What do you do with each of the eggs? And then what do you do? All useful recipes involve repetition - Take four eggs and crack them…. - Beat the eggs until… We need these repetition (“iteration”) constructs in computer algorithms too - Today we will introduce one of them

38. 06-Intro-Object-Oriented-Prog38 Decreasing the red in a picture Recipe: To decrease the red Ingredients: One picture, name it pict and pass it to the function where we will call it picture Step 1: Get all the pixels of picture. For each pixel p in the set of pixels… Step 2: Get the value of the red of pixel p, and set it to 50% of its original value

39. 06-Intro-Object-Oriented-Prog39 Use a for loop! Our first picture recipe The loop - Note the indentation! def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

40. 06-Intro-Object-Oriented-Prog40 How for loops are written for is the name of the command An index variable is used to hold each of the different values of a sequence The word in A function that generates a sequence –The index variable will be the name for one value in the sequence, each time through the loop A colon (“:”) And a block (the indented lines of code) def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

41. 06-Intro-Object-Oriented-Prog41 What happens when a for loop is executed The index variable is set to an item in the sequence The block is executed –The variable is often used inside the block Then execution loops to the for statement, where the index variable gets set to the next item in the sequence Repeat until every value in the sequence was used.

42. 06-Intro-Object-Oriented-Prog42 getPixels returns a sequence of pixels Each pixel knows its color and place in the original picture Change the pixel and you change the picture So the loops here assign the index variable p to each pixel in the picture picture, one at a time. def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

43. 06-Intro-Object-Oriented-Prog43 Do we need the variable value? No –We can calculate the original red amount right when we are ready to change it. –It’s a matter of programming style. The meanings are the same. def decreaseRed(pict): for p in getPixels(pict): setRed(p, getRed(p) * 0.5) def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

44. 06-Intro-Object-Oriented-Prog44 Let’s walk that through slowly… Here we take a picture object in as a parameter to the function and call it pict pict def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

45. 06-Intro-Object-Oriented-Prog45 Now, get the pixels We get all the pixels from the picture, then make p be the name of each one one at a time Pixel, color r=135 g=131 b=105 Pixel, color r=133 g=114 b=46 Pixel, color r=134 g=114 b=45 … p getPixels() pict def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

46. 06-Intro-Object-Oriented-Prog46 Get the red value from pixel We get the red value of pixel p and name it value … value = 135 pict Pixel, color r=135 g=131 b=105 Pixel, color r=133 g=114 b=46 Pixel, color r=134 g=114 b=45 … p getPixels() def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

47. 06-Intro-Object-Oriented-Prog47 Now change the pixel Set the red value of pixel p to 0.5 (50%) of value pict Pixel, color r=67 g=131 b=105 … p value = 135 getPixels() Pixel, color r=133 g=114 b=46 Pixel, color r=134 g=114 b=45 def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

48. 06-Intro-Object-Oriented-Prog48 Then move on to the next pixel Move on to the next pixel and name it p pict … p value = 135 getPixels() Pixel, color r=67 g=131 b=105 Pixel, color r=133 g=114 b=46 Pixel, color r=134 g=114 b=45 def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

49. 06-Intro-Object-Oriented-Prog49 Get its red value p Set value to the red value at the new p, then change the red at that new pixel. p pict … p value = 133 getPixels() Pixel, color r=67 g=131 b=105 Pixel, color r=133 g=114 b=46 Pixel, color r=134 g=114 b=45 def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

50. 06-Intro-Object-Oriented-Prog50 And change this red value Change the red value at pixel p to 50% of value pp pict … p value = 133 getPixels() Pixel, color r=67 g=131 b=105 Pixel, color r=66 g=114 b=46 Pixel, color r=134 g=114 b=45 def decreaseRed(pict): for p in getPixels(pict): value=getRed(p) setRed(p,value*0.5)

51. 06-Intro-Object-Oriented-Prog51 And eventually, we do all pixels We go from this…to this!

52. 06-Intro-Object-Oriented-Prog52 “Tracing/Stepping/Walking through” the program What we just did is called “stepping” or “walking through” the program –You consider each step of the program, in the order that the computer would execute it –You consider what exactly would happen –You write down what values each variable (name) has at each point. It’s one of the most important debugging skills you can have. –And everyone has to do a lot of debugging, especially at first.

53. 06-Intro-Object-Oriented-Prog53 Challenges Create an increaseRed function –Start with the decreaseRed funciton –Modify it to change the red value to 2 * the original red value Create a clearBlue function –Start with the decreaseRed function –Modify it to change the blue value to 0

54. 06-Intro-Object-Oriented-Prog54 How does increaseRed differ from decreaseRed? Well, it does increase rather than decrease red, but other than that… –It takes the same parameter input –It can also work for any picture It’s a specification of a process that’ll work for any picture There’s nothing specific to any particular picture here. Practical programs = parameterized processes

55. 06-Intro-Object-Oriented-Prog55 Can we modify more than one value? How do we turn this beach scene into a sunset? What happens at sunset? –At first, we tried increasing the red, but that made things like red specks in the sand REALLY prominent. Wrap-around –New Theory: As the sun sets, less blue and green is visible, which makes things look more red.

56. 06-Intro-Object-Oriented-Prog56 A Sunset-generation Function def makeSunset(picture): for p in getPixels(picture): value = getBlue(p) setBlue(p, value * 0.7) value = getGreen(p) setGreen(p, value * 0.7)

57. 06-Intro-Object-Oriented-Prog57 Creating a negative Let’s think it through –R, G, B go from 0 to 255 –Let’s say Red is 10. That’s very light red. What’s the opposite? LOTS of Red! –The negative of that would be 245: 255-10 So, for each pixel, if we negate each color component in creating a new color, we negate the whole picture.

58. 06-Intro-Object-Oriented-Prog58 Creating a negative def negative(picture): for px in getPixels(picture): red = getRed(px) green = getGreen(px) blue = getBlue(px) negColor = makeColor( 255-red, 255-green, 255-blue) setColor(px, negColor)

59. 06-Intro-Object-Oriented-Prog59 Original, negative, double negative (This gives us a quick way to test our function: Call it twice and see if the result is equivalent to the original) We call this a lossless transformation.

60. 06-Intro-Object-Oriented-Prog60 Converting to grayscale We know that if red=green=blue, we get gray –But what value do we set all three to? What we need is a value representing the darkness of the color, the luminance There are many ways, but one way that works reasonably well is dirt simple—simply take the average:

61. 06-Intro-Object-Oriented-Prog61 Converting to grayscale def grayscale(picture): for p in getPixels(picture): sum = getRed(p) + getGreen(p) + getBlue(p) intensity = sum / 3 setColor(p, makeColor(intensity, intensity, intensity)) Does this make sense?

62. 06-Intro-Object-Oriented-Prog62 Why can’t we get back again? Converting to grayscale is different from computing a negative. –A negative transformation retains information. With grayscale, we’ve lost information –We no longer know what the ratios are between the reds, the greens, and the blues –We no longer know any particular value. Media compressions are one kind of transformation. Some are lossless (like negative); Others are lossy (like grayscale)

63. 06-Intro-Object-Oriented-Prog63 But that’s not really the best grayscale In reality, we don’t perceive red, green, and blue as equal in their amount of luminance: How bright (or non-bright) something is. –We tend to see blue as “darker” and red as “brighter” –Even if, physically, the same amount of light is coming off of each Photoshop’s grayscale is very nice: Very similar to the way that our eye sees it –B&W TV’s are also pretty good

64. 06-Intro-Object-Oriented-Prog64 Building a better grayscale We’ll weigh red, green, and blue based on how light we perceive them to be, based on laboratory experiments. def grayscaleNew(picture): for px in getPixels(picture): newRed = getRed(px) * 0.299 newGreen = getGreen(px) * 0.587 newBlue = getBlue(px) * 0.114 luminance = newRed + newGreen + newBlue setColor(px, makeColor(luminance, luminance, luminance))

65. 06-Intro-Object-Oriented-Prog65 Summary Name = expression creates a name (a variable) that has a value You can create your own functions in python –Using def name (params): You can execute functions using the function name and passing in any required values –decreaseRed(picture) You can modify pictures by modifying the pixels red, green, and blue values You can use an array to hold many values of the same type You can loop through all the values in an array using a for variable in array: Blocks in Python are shown by indention