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