Nature of code Final: pixel sorting

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.

Black Mode:

Brightness Mode:

White Mode:

 

 

Subtraction Final Project

I built this project inspired by a segment from a film: A Chinese Odyssey.

In this segment, the faery enters the hero’s heart and finds who he really loved, then she leaves a tear in his heart.

Since this film is being re-shot recently, I strongly want to make something to show my respect to it.

So I decided to make a heart which can contain something like a tear.

RWET Final Documentation: Decent Dialogues

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

  • Select the most frequently-used words quoted from various celebrities;
  • Based on our source texts, re-construct the words and generate different questions;
  • Answer these special-style-questions with a fixed structure.

    Techniques We Use

  • Web scrapping using selenium
  • Enable user queries using Flask
  • Extract part-of-speech tagging using Spacy
  • Reform the sentence based on a certain structure

    Examples We’ve Got

    Final Results

    Final Performance

RWET Assignment 5 & 7

I combined these two assignments together (API and function).

import urllib
import json
import sys
import random
kWords=[]

for line in sys.stdin:
line = line.strip()
words = line.split(” “)
for word in words:
if len(word)>=1:
word=word.lower()
kWords.append(word)
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)

try:
synonyms=doc_data[0][“words”]
synonym=random.choice(synonyms)
except IndexError:
synonym=”universal”

# try:
# synonyms=doc_data[0][“words”]
# synonym=random.choice(synonyms)
# except IndexError:
# print “error”
# synonym=”universal”

# synonyms=doc_data[0][“words”]
# synonym=random.choice(synonyms)
print synonym

So the course description is changed to be like this:

Subtraction Assignment 10: 4 Axis 3D Part

At first I found a model of a high-heel shoe online.

Ben taught me how to set everything, but he told me this project is not qualified, since I’m supposed to build the model myself.

So I tried it in Rhino:


There’s a problem that the 4 Axis Mill asks us to use materials with long x-length (and I don’t know why), but then my classmate told me we can fake the data on the software.

Another problem is that it’s hard to carve characters or patterns on the shapes – it will leave very shallow marks, but hard to see it clearly.