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douglasgoodwin / .block
Created Jul 2, 2022 — forked from mbostock/.block
Random Traversal III
View .block
license: gpl-3.0
View iris.csv
0.2 1.4 5.1 3.5 Iris-setosa
0.2 1.4 4.9 3 Iris-setosa
0.2 1.3 4.7 3.2 Iris-setosa
0.2 1.5 4.6 3.1 Iris-setosa
0.2 1.4 5 3.6 Iris-setosa
0.4 1.7 5.4 3.9 Iris-setosa
0.3 1.4 4.6 3.4 Iris-setosa
0.2 1.5 5 3.4 Iris-setosa
0.2 1.4 4.4 2.9 Iris-setosa
0.1 1.5 4.9 3.1 Iris-setosa
View towersofHanoi.pyde
h = 4
A = []
B = []
C = []
for i in range(1,h+1):
A.append(i)
A.reverse()
towers = {"A":A,"B":B,"C":C}
View iteration.pyde
size(400,400)
# white background
background(255)
textAlign(CENTER, CENTER)
i=0
chunk=40
# use range to specify the start, end, and chunk for each loop
# some inspiration from Shiffman
for y in range(0,height,chunk):
View tedium.pyde
size(400,400)
# white background
background(255)
textAlign(CENTER, CENTER)
# Extremely tedious sequence...
fill(100)
rect(0,0, 40,40)
fill(255)
View necker-grid.pyde
from random import randrange
size(600,600)
background(255)
strokeWeight(2)
rowheight = height/7
colwidth = width/6
for y in range(0,height+rowheight,rowheight):
View README.md

Simple image morphing - α-blending of two images using with a cross-dissolve from one image matrix to another.

This project is like the one on page 32 of your new book, "Hands-On Image Processing with Python".

The following code block shows how to start from one face image and end up with another image by using a linear combination of the two image numpy ndarrays.

PROCESS:

  1. Shoot two pictures (see below)
  2. Bring them into Colab
@douglasgoodwin
douglasgoodwin / README.md
Created Jan 30, 2020
For a lecture on Histograms and dynamic range
View README.md

Uses this file: Close-up of leaves, from directly above, In Glacier National Park, Montana

@douglasgoodwin
douglasgoodwin / frameanalysis.ipynb
Created Dec 9, 2019
Analysis of frames from the camera makes a coarse image
View frameanalysis.ipynb
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