Open Source Computer Vision Library https://opencv.org/
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#!/usr/bin/python
from opencv.cv import *
from opencv.highgui import *
import sys
marker_mask = None;
markers = None;
img0 = None
img = None
img_gray = None
wshed = None
prev_pt = cvPoint(-1,-1)
def on_mouse( event, x, y, flags, param ):
global prev_pt
if( not img ):
return;
if( event == CV_EVENT_LBUTTONUP or not (flags & CV_EVENT_FLAG_LBUTTON) ):
prev_pt = cvPoint(-1,-1);
elif( event == CV_EVENT_LBUTTONDOWN ):
prev_pt = cvPoint(x,y);
elif( event == CV_EVENT_MOUSEMOVE and (flags & CV_EVENT_FLAG_LBUTTON) ):
pt = cvPoint(x,y);
if( prev_pt.x < 0 ):
prev_pt = pt;
cvLine( marker_mask, prev_pt, pt, cvScalarAll(255), 5, 8, 0 );
cvLine( img, prev_pt, pt, cvScalarAll(255), 5, 8, 0 );
prev_pt = pt;
cvShowImage( "image", img );
if __name__ == "__main__":
filename = "../c/fruits.jpg"
if len(sys.argv)>1:
filename = sys.argv[1]
rng = cvRNG(-1);
img0 = cvLoadImage(filename,1)
if not img0:
print "Error opening image '%s'" % filename
sys.exit(-1)
print "Hot keys:"
print "\tESC - quit the program"
print "\tr - restore the original image"
print "\tw - run watershed algorithm"
print "\t (before that, roughly outline several markers on the image)"
cvNamedWindow( "image", 1 );
cvNamedWindow( "watershed transform", 1 );
img = cvCloneImage( img0 );
img_gray = cvCloneImage( img0 );
wshed = cvCloneImage( img0 );
marker_mask = cvCreateImage( cvGetSize(img), 8, 1 );
markers = cvCreateImage( cvGetSize(img), IPL_DEPTH_32S, 1 );
cvCvtColor( img, marker_mask, CV_BGR2GRAY );
cvCvtColor( marker_mask, img_gray, CV_GRAY2BGR );
cvZero( marker_mask );
cvZero( wshed );
cvShowImage( "image", img );
cvShowImage( "watershed transform", wshed );
cvSetMouseCallback( "image", on_mouse, None );
while True:
c = cvWaitKey(0);
if c=='\x1b':
break;
if c == 'r':
cvZero( marker_mask );
cvCopy( img0, img );
cvShowImage( "image", img );
if c == 'w':
storage = cvCreateMemStorage(0);
comp_count = 0;
#cvSaveImage( "wshed_mask.png", marker_mask );
#marker_mask = cvLoadImage( "wshed_mask.png", 0 );
nb_cont, contours = cvFindContours( marker_mask, storage, sizeof_CvContour,
CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );
cvZero( markers );
while contours:
cvDrawContours( markers, contours, cvScalarAll(comp_count+1),
cvScalarAll(comp_count+1), -1, -1, 8, cvPoint(0,0) );
contours=contours.h_next
comp_count+=1
color_tab = cvCreateMat( comp_count, 1, CV_8UC3 );
for i in range(comp_count):
color_tab[i] = cvScalar( cvRandInt(rng)%180 + 50,
cvRandInt(rng)%180 + 50,
cvRandInt(rng)%180 + 50 );
t = cvGetTickCount();
cvWatershed( img0, markers );
t = cvGetTickCount() - t;
#print "exec time = %f" % t/(cvGetTickFrequency()*1000.)
cvSet( wshed, cvScalarAll(255) );
# paint the watershed image
for j in range(markers.height):
for i in range(markers.width):
idx = markers[j,i]
if idx==-1:
continue
idx = idx-1
wshed[j,i] = color_tab[idx,0]
cvAddWeighted( wshed, 0.5, img_gray, 0.5, 0, wshed );
cvShowImage( "watershed transform", wshed );
cvWaitKey();