#N canvas 6 51 714 937 10;
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#X obj -464 330 pdp_1394L;
#X msg -407 230 open /dev/dv1394/0;
#X obj -484 205 tgl 15 0 empty empty empty 17 7 0 10 -262144 -1 -1
0 1;
#X obj -482 230 metro 40;
#X msg -364 296 norm PAL;
#X msg -394 259 close;
#X obj -274 211 tgl 15 0 empty empty empty 17 7 0 10 -262144 -1 -1
0 1;
#X obj -274 238 metro 40;
#X msg -184 265 close;
#X obj -254 336 pdp_v4l;
#X msg -197 233 open /dev/video0;
#X obj -73 213 tgl 15 0 empty empty empty 17 7 0 10 -262144 -1 -1 0
1;
#X obj -73 240 metro 40;
#X msg 8 259 close;
#X msg 4 235 open /dev/video0;
#X obj -53 338 pdp_v4l2;
#X obj -512 409 cnv 15 621 73 empty empty empty 20 12 0 14 -260801
-66577 0;
#X obj -464 444 pdp_convert bitmap/rgb/*;
#X text -300 438 COLORMODEL CONVERSION :: allways remember pdp_opencv
only works in RGB colormodel;
#X obj -508 592 cnv 15 621 313 empty empty empty 20 12 0 14 -258113
-66577 0;
#X text -484 176 FIRST OF ALL SETUP YOUR CAMERA;
#X obj -511 499 cnv 15 621 73 empty empty empty 20 12 0 14 -260801
-66577 0;
#X msg -313 525 set;
#X floatatom -313 549 5 0 0 0 - - -;
#X obj -464 549 pdp_opencv_bgsubstract;
#X text -275 548 threshold (default 13) to use when comparing pixel
colors;
#X text -278 524 set the background reference;
#X msg 13 314 format \$1;
#X obj 14 292 hradio 15 1 0 4 empty empty empty 0 -8 0 10 -262144 -1
-1 0;
#X text -513 43 This object considers a contour to be analyzed any
group of white pixels in a black background \, for this reason you
will find useful to use pdp_bgsubstract or pdp_threshold to obtain
a correct input for pdp_opencv_contours_boundingrect.;
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#X floatatom -230 772 5 0 0 0 - - -;
#X obj -292 689 route 0 1 2 3 4;
#X obj -464 624 pdp_opencv_contours_convexity;
#X obj -295 727 unpack 0 0 0 0 0 0;
#X floatatom -200 753 5 0 0 0 - - -;
#X floatatom -166 753 5 0 0 0 - - -;
#X text -182 690 For each convexity defect in our contour;
#X text -256 792 Start point (X -Y);
#X text -192 772 Depth point (X -Y);
#X text -127 754 End point (X -Y);
#X floatatom -285 880 5 0 0 0 - - -;
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#X floatatom -122 842 5 0 0 0 - - -;
#X text -212 881 Start point (X -Y);
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#X text -83 843 End point (X -Y);
#X floatatom -224 976 5 0 0 0 - - -;
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#X obj -190 912 unpack 0 0 0 0 0 0;
#X floatatom -95 938 5 0 0 0 - - -;
#X floatatom -61 938 5 0 0 0 - - -;
#X text -151 977 Start point (X -Y);
#X text -87 957 Depth point (X -Y);
#X text -22 939 End point (X -Y);
#X floatatom -152 1050 5 0 0 0 - - -;
#X floatatom -117 1050 5 0 0 0 - - -;
#X floatatom -87 1031 5 0 0 0 - - -;
#X floatatom -53 1031 5 0 0 0 - - -;
#X obj -118 986 unpack 0 0 0 0 0 0;
#X floatatom -23 1012 5 0 0 0 - - -;
#X floatatom 11 1012 5 0 0 0 - - -;
#X text -79 1051 Start point (X -Y);
#X text -15 1031 Depth point (X -Y);
#X text 50 1013 End point (X -Y);
#X floatatom -378 654 5 0 0 0 - - -;
#X obj -465 925 pdp_xv;
#X text -342 658 number convexity defects in our detected contour;
#X text -512 7 pdp_opencv_contours_convexity :: Finds convexity defects
of the bigest contour of a binary image.;
#X text -512 104 pdp_opencv_contours_boundingrect works detecting the
bigest white area in the input image \, sometimes you will need to
use pdp_opencv_morphology to transform the contours of the shape to
be analyzed..;
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