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README.md
colormaps.py
colormaps.txt
fill_contour_shape.py
fill_contour_shape_multi_threaded.py
opencv-blur-canny-console.py
xkcd-color-browser.py

README.md

pythoncode

My python code (currently mostly gtk3 / opencv)


XKCD Color Browser

Color Browser for xkcd color survey. You can see a sample of ~200 named colors from the survey conducted by Randall.

See xkcd.com/color/rgb for details.

You need a json file with the color descriptions. Get it from here: https://github.com/charlesreid1/xkcd-colors/blob/master/xkcd-colors.json


  • opencv-blur-canny-console.py *

What is it? A simple frontend for opencv blur and canny edge detection. It can open images from the command line, through a file browser, and can even take snapshots from a webcam (!)

Requirements:

  • python 2.7
  • opencv 2.4 python bindings
  • gtk3 python bindings
  • Mountain Dew™
  • Important Note: Mountain Dew is for drinking purposes only. Do not use on electronic equipment!

  • Important Note 2: If you break something, don't sue me! See License! This is my first major contribution to the Open CV project. Actually it's not really a contribution yet, although I will try my best to get this concept and code incorporated into the project. It would be a big achievement (!) for me. Still, the code is open source (GPL 3 or later) and everyone is free to use it.


  • Colormaps *

To begin with, the purpose here is to extract shape and object information from an image. A colormap essentially falls somewhere between a contour and a "shape." The hierarchy is built like this:


| Contour | -> | Colormap | -> | Color Cluster |


A colormap consists of a single (semi) closed regin, along with its contour and color information (mean) (b,g,r). A Color Cluster contains many colormaps, which are grouped together by proximity and similarity of color information.

The public (!) API is simple to use. a high level function is provided, which takes an image and contours as argument, and returns a list of color clusters. For each colormap in the cluster, the get_mat () method builds an intelligent reproduction of the original shape.

Basic classes:

class ColorCluster: colormaps = [list of colormaps] mean = (b ,g ,r)

def generate_mat ()

def populate (self, colormap)
# you have to call this function after first creating a color cluster object with a valid colormap.

def append (self, colormap)
# adding a colormap to the cluster

def match_color (self, color)
# matching color

def match_geometry (self, contour)
# yep

class ColorMap: area = [[x,y]] # list of coordinates inside contour contour = contour passed during intialization mean = (b, g, r) mat = passed during intialization

color_range = 50 # 0 ~ 255
proximity_range = 50 # pixels

def populate (self, area = None, contour = None, mean = None, mat = None)
# to be called after object creation with relevant arguments

def match_color (self, color)
def match_geometry (self, contour)

In most cases, the high level function contour_to_color_cluster () will be convenient.

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