k-means clustering

[imago.git] / imago.py

diff --git a/imago.py b/imago.py
index 136574a..33e7c69 100755 (executable)
--- a/imago.py
+++ b/imago.py
@@ -86,7 +86,7 @@ def main():
             lines, l1, l2, bounds, hough, im_h = linef.find_lines(image, show_all, do_something, verbose)
 
         grid, lines = gridf.find(lines, image.size, l1, l2, bounds, hough,
-                                 do_something, im_h)
+                                 show_all, do_something)
         if show_all:
             im_g = image.copy()
             draw = ImageDraw.Draw(im_g)
@@ -94,18 +94,7 @@ def main():
                 draw.line(l, fill=(64, 255, 64), width=1)
             do_something(im_g, "grid", name="grid")
 
-    board, board_raw = intrsc.board(image, lines, show_all, do_something)
-
-    ### Show color distribution
-    #import matplotlib.pyplot as pyplot
-    #luma = [(0.30 * s[0] + 0.59 * s[1] + 0.11 * s[2]) / 255.
-    #             for s in sum(board_raw, [])]
-    #pyplot.scatter(luma,
-    #            [(max(s) - min(s)) / (255 - abs(max(s) + min(s) - 255))
-    #             for s in sum(board_raw, [])],  
-    #               color=[(s[0]/255., s[1]/255., s[2]/255., 1.) for s in sum(board_raw, [])])
-    #pyplot.show()
-    ###
+    board = intrsc.board(image, lines, show_all, do_something)
 
     #simple ASCII output:
     for line in board: