Description
Short answer problems [45 points]
Read through the provided Python, NumPy and Matplotlib introduction code and comments: http://cs231n.github.io/python-numpy-tutorial/ or https://filebox.ece.vt.edu/~F15ECE5554ECE4984/resources/numpy.pdf. Open an interactive session in Python and test the commands by typing them at the prompt. (Skip this step if you are already familiar with Python and NumPy.)
After reading the required documentation in the above section, to test your knowledge ensure that you know the outputs of the following commands without actually running them.
We start counting at Red. Each step to a point on the hexagon counts as 1 unit distance. The distance between points is given by the relative ratios of the secondary colors. We can use the following formula from Wikipedia:
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8
GCB
if V = R
>
undefined
C = 0
H0 =
B R
>
+ 2
if V = G
C
>
<
>
RCG +4
if V = B
>
>
:
H0
+ 1
if H’ < 0
H =
6
H0
(
otherwise
6
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There is no “correct” Hue if C = 0 because all of the channels are equal so the color is a shade of gray, right in the center of the cylinder. However, for now let’s just set H = 0 if C = 0 because then your imple-mentation will match ours. (Use function prob_4_2 and return HSV.)
Deliverable Checklist
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1.1-1.4 (answer sheet) code snippets for each question.
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2.1-2.5 (code/files) PS1Q2.py, (answer sheet) corresponding plot for 2.1 & 2.2.
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3.1-3.6 (code/files) PS1Q3.py, noise.npy, (answer sheet) 6 images.
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4.1 (answer sheet) display the 2 plots (RGB, LAB)
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4.2 (code/files) PS1Q4.py, (answer sheet) outputPS1Q4.png
This assignment is adapted from the following 3 sources:
PS0 assignment of Kristen Grauman’s CS 376: Computer Vision at UT Austin
HW1 assignment of David Fouhey’s EECS 442: Computer Vision at University of Michigan.
HW0 assignment of Joseph Redmon’s CSE 455: Computer Vision at University of Washington.
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