cross-stitch

commit b8948bc4acd8107a723b6c23b5b417120b7813d9
parent 38af9a0714c260b0ed50af24ce635a17d301c87c
Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
Date:   Fri, 14 Feb 2014 15:17:59 +0100

added k-means clustering to reduce the number of colors

Diffstat:
M
README.rst
 | 
3
+++
M
cross-stitch.py
 | 
16
++++++++++++----
M
fisker-pattern.png
 | 
0

3 files changed, 15 insertions(+), 4 deletions(-)
diff --git a/README.rst b/README.rst
@@ -30,6 +30,7 @@ Usage
 -----
 
   usage: cross-stitch.py [-h] --infile file --outfile file [--width WIDTH]
+                       [--ncolors NCOLORS]
 
 Downsamples and modifies an image in order to create a pattern for cross
 stitching.
@@ -42,6 +43,8 @@ optional arguments:
                         save processed image as file
   --width WIDTH, -w WIDTH
                         canvas width, default value = 20
+  --ncolors NCOLORS, -c NCOLORS
+                        number of colors in output image, default value = 10
 
 Example
 -------
diff --git a/cross-stitch.py b/cross-stitch.py
@@ -4,6 +4,7 @@ import sys
 import argparse
 import scipy.ndimage
 import scipy.misc
+import scipy.cluster
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -19,12 +20,13 @@ parser.add_argument('--outfile', '-o', metavar='file', type=str, nargs=1,
         required=True, help='save processed image as file')
 parser.add_argument('--width', '-w', type=int, nargs=1, default=20,
         help='canvas width, default value = 20')
-#parser.add_argument('--n-colors', '-c', type=int, nargs=1, default=10,
-        #help='number of colors in output image, default value = 10')
+parser.add_argument('--ncolors', '-c', type=int, nargs=1, default=10,
+        help='number of colors in output image, default value = 10')
 args = parser.parse_args()
 infile = args.infile[0]
 outfile = args.outfile[0]
 width = args.width[0]
+ncolors = args.ncolors
 
 ## Read image ##################################################################
 try:
@@ -39,11 +41,17 @@ new_size = (int(round(hw_ratio*width)), width)
 im_small = scipy.misc.imresize(im, new_size)
 
 ## Process image colors ########################################################
-
+ar = im_small.reshape(scipy.product(im_small.shape[:2]), im_small.shape[2])
+colors, dist = scipy.cluster.vq.kmeans(ar, ncolors)
+c = ar.copy()
+vecs, dist = scipy.cluster.vq.vq(ar, colors)
+for i, color in enumerate(colors):
+    c[scipy.r_[scipy.where(vecs==i)],:] = color
+im_small_reduced = c.reshape(new_size[0], new_size[1], 3)
 
 ## Generate output plot ########################################################
 fig = plt.figure()
-imgplot = plt.imshow(im_small)
+imgplot = plt.imshow(im_small_reduced)
 imgplot.set_interpolation('nearest')
 plt.grid()
 plt.savefig(outfile)
diff --git a/fisker-pattern.png b/fisker-pattern.png
Binary files differ.