Inspired by Jeff Thompson’s GitHub (https://github.com/jeffThompson/PixelSorting), I’ve made my own tryings.
Firstly, I selected a video and automated it into a gif file through terminal. (Not necessary for this project, just did it for fun)
The original gif file is like this (yeah this is my friend Jade):
Based on what Jeff said:
This particular script loops through both the columns and the rows of the image, but it doesn’t pixel sort the entire column or row, if it did, the result would look more like a blank gradient than anything interesting. Instead for each column and row it looks for a pixel to start sorting on and then it looks for a pixel to stop sorting on — this makes the algorithm somewhat intelligent resulting in identifiable elements of the image being left untouched.
So I tried different mode to decide which pixel to start sorting on, and which to stop.
Inspiration and Intention
As a foreigner, when I talk with people in English, it’s sometimes a little bit embarrassing. Like when people ask me:”How’s going?” I’m always not if I should answer like “good”/”fine”, or answer it with more details or emotions to show my respect – cuz in China, people never greet by asking questions.
So we are wondering if we can build up a specific structure for questions and answers, based on different people’s styles.
What We Do
I combined these two assignments together (API and function).
for line in sys.stdin:
line = line.strip()
words = line.split(” “)
for word in words:
api_key = “a2a73e7b926c924fad7001ca3111acd55af2ffabf50eb4ae5”
for kWord in kWords:
# print kWord
# print type(kWord)
url = “http://api.wordnik.com:80/v4/word.json/”+kWord+”/relatedWords?useCanonical=true&relationshipTypes=synonym&limitPerRelationshipType=10&api_key=”+api_key
doc_str = urllib.urlopen(url).read()
doc_data = json.loads(doc_str)
# except IndexError:
# print “error”
So the course description is changed to be like this:
Based on my last homework, I used “set” function to collect the words in the same length: