Slide 1

Today: parameters, start PyCharm, command line, bluescreen algorithm

These are all on HW2, due next Wed.

Slide 2

What is a Function Parameter?

A parameter to as function provides some extra data to use when the function runs.

Suppose we have a function like this

def darker_left(filename, left):
        ...

The function has two parameters, filename and left, which are values for it to use. It loads the image in that file, and sets a stripe down its left side to be dark, with the width of the stripe specified by the left parameter.

When the darker_left() function is called, the two parameters guide what it does. In this case the filename parameter gives the name of the file with the image to edit, e.g. poppy.jpg. The left parameter specifies the number of pixels at the left side of the image which should be darkened.

Here are three separate calls to the darker_left() function, showing the parameters at work:

For each call to the function, we say the parameters are "passed in" to the function. So above the first calls passes in 50 for the left parameter and the last call passes in 2.

Slide 3

How To Write a Function with Parameters

Look at the def again. The parameters are listed within the parenthesis.

def darker_left(filename, left):
    # write code in here

How to write this code: each parameter is like a variable. The value for the function to use has been set into the parameter (variable) already. The function code just uses the parameter, relying on the right value being in there. So in this case filename and left have the right values in them, the code here just uses it.

Slide 4

Write Code for darker_left()

> Darker Left

def darker_left(filename, left):
    # your code here
    # use filename and left
    ...

Q: How many pixels on the left to darken?

A: Whatever value is in the left parameter.

Key idea: just use the parameters, filename and left - they are already set up with the values to use. In this case, if left is 50, we want to darken a stripe 50 pixels wide. If left is 2, we darker the a stripe 2 pixels wide. Work out he for/x/range loop to hit that stripe. Note this problem does not create a separate "out" image, so that keeps it simpler.

Solution code

def darker_left(filename, left):
    image = SimpleImage(filename)
    for y in range(image.height):
        for x in range(left):
            pixel = image.get_pixel(x, y)
            pixel.red *= 0.5
            pixel.green *= 0.5
            pixel.blue *= 0.5
    return image

Slide 5

Where Do the Parameters Come From?

Well if we're going to take it on faith that the parameters have the right values .. where do those values come from? In one word: the parenthesis.

Slide 6

Function in Two Worlds: def and call

Each function has two forms, equally important. The def specifies the code of the function, usually with many lines of code. There is one def for a function.

A call of a function is one line, calling the function by name to run it. The call specifies the values for the parameters within the parenthesis. There can be many calls to a function.

Slide 7

Look in the Run Menu

Look at the Run Menu for darker_left() carefully. For each case, you can see the syntax of the function call - the name of the function and a pair of parenthesis. Look inside the parenthesis, and you will see the parameters passed in for each run. Click the Run button with different menu selections to see it in action.

Slide 8

foo(a, b) Example

What do you see here?

def foo(a, b):
   ...
   ...

It's a function named "foo" (traditional made-up name in CS). It has two parameters, named "a" and "b".

Each parameter is for extra information the caller "passes in" to the function when calling it. What does that look like? Which value goes with "a" and which with "b"?

A call of the foo() looks like this:

   ....
   foo(13, 100)
   ...

Parameter values match up by position within the parenthesis. The first value goes to "a", the second to "b". It is not required that the value has the same name a the parameter.

Slide 9

Little Foo Interpreter Exercise

Claim: the parameter values from from the function call line, within the parenthesis.

Let's do a little live exercise along these lines.

The hack mode "interpreter", has a ">>>" prompt. You type a line of python code here, hit return. What you typed is sent to python to run, the results are printed after the ">>>".

We'll use this more later, but for now we can do a little function/parameter exercise.

> Hack Mode Console

Here we'll enter a little two-line def of foo(a, b) in the interpreter, then try calling it with various values. It's very unusual to define a function within the interpreter like this, but here's one time we'll do it. Normally we define functions inside a .py file.

The most important thing is that at the function call line, the parameter values are pulled from within the parenthesis.

The parameters match by position. So the first value goes to "a", the second value goes to "b". The number of parameters must be exactly 2 or there's an error, since foo() takes 2 parameters. The word "argument" is another word for a parameter, which appears in the Python error messages.

Each parameter value can be an expression - Python computes the value if needed, then sends that value as the parameter.

>>> # Define foo
>>> def foo(a, b):
      print('a:', a, 'b:', b)
>>>
>>> # Call it with 2 param values
>>> foo(1, 2)
a: 1 b: 2
>>> foo(13, 42)
a: 13 b: 42
>>>
>>> # Call with expressions - passes computed value, e.g. 60
>>> foo(10 * 6, 33 + 2)
a: 60 b: 35
>>>
>>> # Show that number of parameters must be 2
>>> foo(12)
Error:foo() missing 1 required positional argument: 'b'
>>> foo(12, 13, 14)
Error:foo() takes 2 positional arguments but 3 were given
>>>
>>>
>>> # Parameters do not match by name
>>> # Parameters match by position - first to "a", second to "b"
>>> b = 10
>>> foo(b, b + 1)
a: 10 b: 11

Slide 10

The Command Line

The command line is how your computer works "under the hood", and we'll use it in CS106A. Not pretty, but very powerful. We'll use it with a free program called PyCharm - see the PyCharm instructions on the course page.

For details see Python Guide: Command Line

The above guide has instructions to download this example folder: hello.zip

Unzip that folder. Open the folder in PyCharm (not the hello.py, the folder). In PyCharm, select "Terminal" at lower left - that's the command-line area. Then try running the hello.py program ("python3" on the Mac, "py" on Windows).

% python3 hello.py Alice
Hello Alice
% python3 hello.py Bob
Hello Bob
% python3 hello.py -n 100 Alice
Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Al
ice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alic
e Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice 
Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Al
ice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alic
e Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice 
Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Al
ice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alice Alic
e Alice 

Slide 11

Image Grid Demo

Then we demo command lines from the image-grid homework. They look like this

% python3 image-grid.py -channels poppy.jpg
%
% python3 image-grid.py -grid poppy.jpg 2
%
% python3 image-grid.py -random yosemite.jpg 3

Those are described in detail in the image-grid homework handout, so you'll see explanations for those when you begin the homework.

Slide 12

Color If Logic

> Logic-Stop Examples

• Say we have this stop sign
• Detect areas of an image based on color, e.g. red
• Work out algorithm, Python code to detect a color area
• e.g. detect the red area of this stop sign
• Reminder for colors: rgb-explorer

Slide 13

Red Detect red >= 100

• Try on red_detect1 code example
• First try using red value with >
• Color detection - think about the "hurdle" in the if-test
• e.g. if pixel.red >= 100:
• Starts with hurdle value of 100
• Adjust value to get best results
• Q: To make this more selective, make 100 bigger or smaller?
• A: bigger. Look at < - think for a second to get the direction correct
• Does not work that great:
  Bright areas and red areas both have big red numbers
• redish pixel: 220, 50, 50
• white pixel: 220, 220, 220
• Best can do here is maybe hurdle of 160

Slide 14

Red Detect - Average

• Try on red_detect2 code example
• Improvement: compare red value to average of red/green/blue values
• "redish pixel"
  the red value is above the average of this pixel
• "blueish pixel"
  the blue value is above the average of this pixel
• red >= average * 1.0
• Adjust the 1.0 "hurdle" factor by eye, try 1.0 1.1 1.2 .. find a good value
• The average technique works great to select the red stop sign pixels
• Experiment: for detected pixels, reduce only red and green, leaving blue unchanged
  result is blue stop sign
• Experiment: for detected pixels, swap red and green values

Slide 15

Bluescreen Algorithm

• Demo Google search: blue screen movie image
• Also known as Chroma Key (wikipedia)
• Video is just a series of still images, 20-60 per second
• This is the "front" approach, replacing colored pixels in the front image
• Have image with special color
• Have back background image
• 1. Detect colored area in an image, e.g. the blue area
• 2. Replace colored pixels with pixels from back image
• 3. The final output is the front image with the replacements done

Slide 16

Bluescreen Algorithm Outline

• Two images we'll call image and back
• Detect, say, red pixels in image
• For each red pixel (make a drawing)
  Consider the pixel at the same x,y in back image
  Copy that pixel from back to image
  i.e. copy RGB numbers from back pixel to image pixel
• Result: for red areas, copy over areas from back image
• Adjacent pixels in back are still adjacent in new image, so it looks right

Diagram:

Slide 17

Bluescreen Stop Sign Example

This code is complete, look at the code then run it to see.

> Bluescreen Stop Sign

Solution code

def stop_leaves(front_filename, back_filename):
    """Implement stop_leaves as above."""
    image = SimpleImage(front_filename)
    back = SimpleImage(back_filename)
    for y in range(image.height):
        for x in range(image.width):
            pixel = image.get_pixel(x, y)
            average = (pixel.red + pixel.green + pixel.blue) // 3
            if pixel.red >= average * 1.4:
                # the key line:
                back_pixel = back.get_pixel(x, y)
                pixel.red = back_pixel.red
                pixel.green = back_pixel.green
                pixel.blue = back_pixel.blue
    return image

Before - the red stop sign before the bluescreen algorithm:

After:

Slide 18

Bluescreen Monkey

> Bluescreen Monkey

A favorite old example of Nick's.

Have monkey.jpg with blue background

The famous Apollo 8 moon image. At one time the most famous image in the world. Taken as the capsule came around the moon, facing again the earth. Use this as the background.

The bluescreen code is the same as before basically. Adjust the hurdle factor to look good. Observe: the bluescreen algorithm depends on the colors in the main image. BUT it does not depend on the colors of the back image - the back image can have any colors it in. Try the stanford.jpg etc. background-cases for the monkey.

The code is complete but has a 1.5 factor to start. Adjust it, so more blue gets replaced, figuring out the right hurdle value.