Lab 06

Due date: Oct 26, 2008 at 20:00

Making an image smaller

def scaledownby2(filename):
  barb = makePicture(filename)
  canvas = makePicture("640x480.jpg")
  for targetX in range(0,222/2):
    for targetY in range(0,294/2):
      color = getColor(getPixel(barb,targetX * 2,targetY * 2))
      setColor(getPixel(canvas,targetX,targetY),color)
  return canvas

1. Instead of using makePicture to open an existing empty picture as canvas, use makeEmptyPicture(), a pre-defined function that takes the width and height of the picture to be created as arguments.
2. Moreover, modify the code so that it doesn't use magic constants (such as 222 and 294). Instead use the size of the original picture instead.
3. If you execute show(scaledownby2("barbara.jpg")), it should result in this picture at this point.

   

4. Now modify the function so that it can scale down by arbitrary integer factors, not just by two. Rename the function to "scaledown" and add an additional argument for the scale factor. In other words, you should be able to execute show(scaledown("barbara.jpg",2)).
   If the scale factor passed as argument is either zero, or negative you should print an error message stating that "Cannot scale by this factor". Use the print command for that purpose and don't forget to do a return immediately afterwards (e.g. to prevent a division by zero error).
   If the scale factor is too large, i.e. the result gets smaller than a single pixel, print an error message "Result too small" and return, similar to the previous diagnostic message.
5. Finally, note that the scaled down version has some pixelation artefacts, due to the fact that lot's of the pixels are "thrown away". You can see this e.g. on the jagged appearance of the vertical wood pieces in the top right part of the version that is scaled down by 2. To fix this, you have to modify the program so that each pixel of the new, smaller image is set to the average of all pixels that are scaled down into that pixel. E.g. assuming a scale factor of two, the top left pixel of the new image is the average of the four top left pixels in the old image. More precisely a square area of two by two in the old image (where two is the scale factor). To achive this, do the following:
   • First, review how to compute an average: You first have to initialize a variable to zero, add up all items in that variable, and finally divide it by the number of items.
   • The area corresponding to a pixel in the new image is an area of "scale factor" by "scale factor" pixels in the original image. To compute an average over that, you will need two loops that iterate over those pixels.
   • You already know the top left pixel of that area! It is the pixel that is read by the original code segment shown above.

Lab Questions and What to Turn in

How to submit the lab

submit 1710 lab06 lab06.py

Note: You must do all the above steps correctly for receiving full credit for this lab.

Common Problems

• Input errors were not caught: Division by 0 was not avoided
• Did not rename the function
• Did not run (unfinished program but effort is shown)
• If the code had small problems (e.g input errors were generally handled but not perfectly) but a great effort was shown in de-pixelation section, +0.25 was awarded.