#N canvas 642 52 632 594 10;
#X obj 20 190 #out window;
#X obj 20 63 #in babbage.jpg;
#X obj 20 46 bng 15 250 50 0 empty empty empty 17 7 0 10 -24198 -1
-1;
#X obj 20 102 #cast f;
#X obj 37 44 loadbang;
#X obj 20 171 #inner (1 3 # 85 51 15);
#X obj 42 150 #print;
#X obj 102 93 #out window;
#X msg 225 86 mode channels;
#X obj 20 121 cv/#KMeans 8 \, termcrit (8 nil);
#X obj 0 0 doc_h cv/;
#X obj 3 221 doc_c 1;
#X obj 3 283 doc_i 2;
#X obj 3 369 doc_o 1;
#X obj 14 313 doc_ii 0;
#X obj 14 335 doc_ii 1;
#X obj 14 399 doc_oo 0;
#X obj 14 251 doc_cc 0;
#X obj 3 540 doc_also;
#X obj 0 560 doc_f;
#X obj 103 540 #cluster_avg 1;
#X obj 97 251 doc_m c0 float;
#X text 232 251 number of clusters.;
#X obj 97 335 doc_m i1 float;
#X obj 232 335 doc_same 0;
#X obj 97 313 doc_m i0 grid;
#X text 232 313 grid to analyse. Dim(... \, channels);
#X obj 97 399 doc_m o0 grid;
#X text 232 399 grid analysed. Dim(... \, 1);
#X text 232 421 where each number is number from 0 to number of clusters
- 1 \, which is the id of a cluster.;
#X text 232 456 from there \, you may use [#cluster_avg] to find the
average of all values in a cluster. You may use [#store] to build again
a grid of size Dim(... \, channels) where each chunk (pixel or whatever)
has been replaced by the average of its cluster.;
#X connect 1 0 3 0;
#X connect 1 0 7 0;
#X connect 2 0 1 0;
#X connect 3 0 9 0;
#X connect 4 0 1 0;
#X connect 5 0 0 0;
#X connect 8 0 9 0;
#X connect 9 0 5 0;
#X connect 9 0 6 0;
#X connect 18 1 20 0;
#X connect 21 1 22 0;
#X connect 23 1 24 0;
#X connect 25 1 26 0;
#X connect 27 1 28 0;
#X connect 27 1 29 0;
#X connect 27 1 30 0;