A quiz on the first laboratory: Getting started with OpenCV

Adrian F. Clark

1. How are images represented in OpenCV?

   • in an opaque OpenCV-only format
   • as a list of unsigned bytes

   • as numpy arrays

   • as a list of lists

   The Python wrappers for OpenCV represent images as numpy arrays, 2D for monochrome ("black and white") images and 3D for colour ones.

2. What is sys.argv[1]?

   • The first space-separated word on the command line.

   • The program name.
   • All the words on the command line.
   • An image.

   sys.argv is a list of the space-separated words that were provided on the command line. The first element in it, element 0, is the program name and so element 1 is the first word that was given after the program name.

3. How many rows and columns are there in the image sx.jpg?

   • 1024 and 1024.
   • 480 and 640.

   • 512 and 512.

   • 640 and 480.

   This is something that was printed out when you ran hello.py on the image. You mean you didn't record the information...?

4. Where is the origin of an image in OpenCV?

   • the bottom left corner

   • the top left corner

   • the bottom right corner
   • the top right corner

   OpenCV images have the origin (row zero, column zero) at the top left corner of the image. This might seem obvious but is not always the case: for example if you program image operations using the 3D graphics package called OpenGL (note the similarity of the name to OpenCV), its image origin is at the bottom left corner of an image. Much confusion can result from this!

5. What do the three subscripts of a colour image represent in OpenCV?

   • column, row, colour.

   • row, column, colour.

   • colour, column, row.
   • colour, row, column.

   Images are stored as numpy matrices, so their first two subscripts are row and column respectively. Images are stored so that the colour values of a single pixel are next to each other in memory, so the third subscript selects the colour.

6. Why were you asked to store the routines you develop in sxcv.py?

   • So that you can see how to comment programs.
   • To give you practice at programming.
   • So you can record what you have done.

   • So that you can use them later in vision application programs.

   The underlying reason for getting you to store the routines you write (and hopefully test) in sxcv.py is so you can use them to extend the programs that appear in the lab experiments after the first progress test.

7. What is the standard deviation?

   • The median.

   • The average spread of values from the mean.

   • The same as the mean.
   • How different one image is from another.

   The standard deviation measures the average spread of value in an image.

8. How are the pixels of an image normally represented in OpenCV?

   • signed floats
   • unsigned ints
   • signed bytes

   • unsigned bytes

   Unless you take care to make them otherwise, the pixels of images are stored as unsigned bytes in OpenCV. It is possible to use the other representations listed in the answers but you have to go to some effort to do so when you create the image.

9. What underlying OpenCV routine does sxcv.display call to display an image?

   • cv2.waitKey

   • cv2.imshow

   • cv2.imread
   • cv2.display

   The underlying display routine in OpenCV is cv2.imshow, though the image is not posted onto the screen until cv2.waitKey is called.

10. What values did your extrema routine return for testimage?

    • 0, 10.
    • 0, 15.

    • 10, 15.

    • 0, 255.

    Your extrema routine should return the smallest and largest values in the image it is given. For testimage, these are 10 and 15 --- in fact, the doctest for this routine gives them.