Section 1

Image Range-Loop Problems

You might find nested y,x range loops helpful in solving these. Problems like this are well suited to making a drawing first to think through the algorithm before coding, and especially to get the arithmetic for each coordinate exactly right. These algorithms are a magnet for off-by-one errors.

A good first step, as in lecture, is to sketch out the pixel grid x,y coordinates as in lecture to plan how your algorithm will access the pixels.

Implement the following functions, each of which takes an image's filename and returns a SimpleImage. You might find the SimpleImage documentation useful to consult.

1. double_left(filename): Takes the left half of the image, and copies it on top of the right half.

   

2. double_left_up(filename): Takes the left half of the image, and copies it on the right half as before, except it is flipped upside-down as it is copied.

   

3. copies_2(filename): Create a new image twice as wide as the original, and place two copies of the original image, in it, side by side.

   

4. squeeze_width(filename, n): A funhouse mirror effect governed by the int parameter n. Create a new image with the same height as the original, but with a width that is n times smaller than the original's. Copy the original image such that it is squeezed horizontally.

   

   For example, if n = 4, the pixels in the output image with an x coordinate of 0 would be copies of the input pixels with an x coordinate of 0 * 4 = 0, while pixels in the output image with an x coordinate of 1 would be copies of the input pixels with an x coordinate of 1 * 4 = 4, and so on.

Test your solutions here.

Image Puzzles

This is a lab-style problem. You may want to work on this in groups on your laptop and test your programs as you write them.

Photo Editor programs are often used for color correcting digital images, that is, modifying the color components in images to alter the relative 'redness', 'greenness' or 'blueness' of the image. In this problem, we'll give you three exaggerated examples of images that need color correction-as well as what exactly is wrong with each of them-and you'll figure out how to alter each pixel in order to correct the image. For these problems, you should be able to use the plain 'foreach' to solve each of them without needing to work with x and y coordinates.

Specifically, implement the following functions, each of which takes in an image filename and returns a SimpleImage. You might find the SimpleImage documentation useful to consult.

Reproductions of images themselves are not reproduced on printed copies of this handout. You can find the images on the digital version of this handout, linked on the course website.

For the benefit of students who are color-blind or otherwise unable to identify issues with the colors of these images, we list the issues with each of the images below, so you'll be able to implement them anyway. This table is available on the digital version of this handout, linked on the course page.

1. fix1(filename): This function takes in the filename of an image wherein across all its pixels, one of the red/green/blue components has been divided by 2, one by 4, and one by 8. Write code to reverse this to fix the image and then return it.

   

   The divide/multiply cycle introduces some small glitches in the image which can be ignored.

2. fix2(filename): This function takes in the filename of an image wherein across all its pixels, two of the colors have been swapped. Figure out which two colors and write code to fix it.

   

   This does not suffer from divide/multiply glitches. Swapping is perfectly reversible!

3. fix3(filename): This function takes in the filename of an image wherein across all its pixels, two of the colors have been swapped. In addition, the third color has been divided by 4. Write code to fix all this.

   

Test your solutions here.