01-IntroToMediaComp1 Barb Ericson Georgia Institute of Technology Feb 2010 Introduction to Computer Science and Media Computation
01-IntroToMediaComp2 Learning Goals What is Computer Science? What is Media Computation? What are the standard math operators? What is a variable? What is a function? How do digital pictures work? How can you manipulate a digital picture? What is an array? What is a loop?
01-IntroToMediaComp3 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
01-IntroToMediaComp4 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
01-IntroToMediaComp5 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
01-IntroToMediaComp6 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. Editor or Program Area Command Area
01-IntroToMediaComp7 Using JES – Try the following >>> print >>> 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 Type these expressions after the >>> in the command area
01-IntroToMediaComp8 Did any answer surprise you? Integer division results in an integer answer –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
01-IntroToMediaComp9 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
01-IntroToMediaComp10 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 >>> print play(makeSound(pickAFile())) None
01-IntroToMediaComp11 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()
Try the following in JES >>> x = 3 >>> y = 2 >>> z = x * y >>> print z >>> message = "Bye" >>> print message >>> message = "Go away" >>> print message 01-IntroToMediaComp12
Variables Can hold values like integers (3) and strings of characters "Bye" Can be printed –The value in them is printed Can be used in calculations (like x * y) –The values in them is used Can be changed to new values –The values in them can vary 01-IntroToMediaComp13
01-IntroToMediaComp14 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
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 01-IntroToMediaComp15
01-IntroToMediaComp16 Making functions the easy way Get something working by typing commands in the command area (bottom half of JES) Enter the def command in the editing window (top part of JES) Copy-paste the tested commands up into the recipe
01-IntroToMediaComp17 A recipe for showing a picture def pickAndShow(): myFile = pickAFile() myPict = makePicture(myFile) show(myPict) Note: myFile and myPict, inside pickAndShow(), are completely different from the same names in the command area. We say that they are in a different scope. Type this in the program area (editor)
01-IntroToMediaComp18 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. Type pickAndShow in the command area and all statements in the block will be executed.
Image Processing Goals: –Give you the basic understanding of image processing, including psychophysics of sight, –Identify some interesting examples to use 01-IntroToMediaComp19
01-IntroToMediaComp20 Light perception 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.
01-IntroToMediaComp21 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. –Contrast also plays a role Luminance is actually color blind. Completely different part of the brain.
01-IntroToMediaComp22 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
01-IntroToMediaComp23 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
01-IntroToMediaComp24 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
01-IntroToMediaComp25 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
01-IntroToMediaComp26 Making Colors with Light Type >>> myColor = pickAColor() Try to create –White –Black –Yellow –Red –Brown –Purple
01-IntroToMediaComp27 Basic Picture Functions makePicture(filename) creates and returns a picture object, from the JPEG file at the filename pict = makePicture("c:/ip-book/mediasources/barbara.jpg") show(picture) displays a picture in a window show(pict) explore(picture) makes a copy of the picture and shows it in the explorer window explore(pict) We’ll learn functions for manipulating pictures like getColor, setColor, and repaint
01-IntroToMediaComp28 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
01-IntroToMediaComp29 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
01-IntroToMediaComp30 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)
01-IntroToMediaComp31 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)
01-IntroToMediaComp32 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 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 one at a time
01-IntroToMediaComp33 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
01-IntroToMediaComp34 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)
01-IntroToMediaComp35 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)
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…” 01-IntroToMediaComp36
01-IntroToMediaComp37 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
01-IntroToMediaComp38 Decreasing the red in a picture Recipe: To decrease the red Ingredients: One picture, name it picture and pass it to the function where we will call it pict Step 1: Get all the pixels of pict. 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
01-IntroToMediaComp39 More about for each loops 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)
01-IntroToMediaComp40 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 usually 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 is used.
01-IntroToMediaComp41 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)
01-IntroToMediaComp42 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)
01-IntroToMediaComp43 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)
01-IntroToMediaComp44 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)
01-IntroToMediaComp45 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)
01-IntroToMediaComp46 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)
01-IntroToMediaComp47 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)
01-IntroToMediaComp48 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)
01-IntroToMediaComp49 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)
01-IntroToMediaComp50 And eventually, we do all pixels We go from this…to this!
01-IntroToMediaComp51 Tracing/Stepping/Walking 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.
01-IntroToMediaComp52 Challenges Create an increaseRed function –Copy the decreaseRed function and rename it –Modify it to change the red value to 2 * the original red value Create a clearBlue function –Copy the decreaseRed function and rename it –Modify it to change the blue value to 0
01-IntroToMediaComp53 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 didn't work very well –New Theory: As the sun sets, less blue and green is visible, which makes things look more red.
01-IntroToMediaComp54 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)
01-IntroToMediaComp55 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: So, for each pixel, if we negate each color component in creating a new color, we negate the whole picture.
01-IntroToMediaComp56 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)
01-IntroToMediaComp57 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.
01-IntroToMediaComp58 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:
01-IntroToMediaComp59 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?
01-IntroToMediaComp60 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)
01-IntroToMediaComp61 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
01-IntroToMediaComp62 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) * newGreen = getGreen(px) * newBlue = getBlue(px) * luminance = newRed + newGreen + newBlue setColor(px, makeColor(luminance, luminance, luminance))
01-IntroToMediaComp63 Summary Name = expression creates a name (a variable) that has a value You can create your own functions in python 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