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 (!)
- 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.
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.