+++ /dev/null
-#!/usr/bin/python
-#
-# The full "Square Detector" program.
-# It loads several images subsequentally and tries to find squares in
-# each image
-#
-
-from opencv.cv import *
-from opencv.highgui import *
-from math import sqrt
-
-thresh = 50;
-img = None;
-img0 = None;
-storage = None;
-wndname = "Square Detection Demo";
-
-def angle( pt1, pt2, pt0 ):
- dx1 = pt1.x - pt0.x;
- dy1 = pt1.y - pt0.y;
- dx2 = pt2.x - pt0.x;
- dy2 = pt2.y - pt0.y;
- return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
-
-def findSquares4( img, storage ):
- N = 11;
- sz = cvSize( img.width & -2, img.height & -2 );
- timg = cvCloneImage( img ); # make a copy of input image
- gray = cvCreateImage( sz, 8, 1 );
- pyr = cvCreateImage( cvSize(sz.width/2, sz.height/2), 8, 3 );
- # create empty sequence that will contain points -
- # 4 points per square (the square's vertices)
- squares = cvCreateSeq( 0, sizeof_CvSeq, sizeof_CvPoint, storage );
- squares = CvSeq_CvPoint.cast( squares )
-
- # select the maximum ROI in the image
- # with the width and height divisible by 2
- subimage = cvGetSubRect( timg, cvRect( 0, 0, sz.width, sz.height ))
-
- # down-scale and upscale the image to filter out the noise
- cvPyrDown( subimage, pyr, 7 );
- cvPyrUp( pyr, subimage, 7 );
- tgray = cvCreateImage( sz, 8, 1 );
- # find squares in every color plane of the image
- for c in range(3):
- # extract the c-th color plane
- channels = [None, None, None]
- channels[c] = tgray
- cvSplit( subimage, channels[0], channels[1], channels[2], None )
- for l in range(N):
- # hack: use Canny instead of zero threshold level.
- # Canny helps to catch squares with gradient shading
- if( l == 0 ):
- # apply Canny. Take the upper threshold from slider
- # and set the lower to 0 (which forces edges merging)
- cvCanny( tgray, gray, 0, thresh, 5 );
- # dilate canny output to remove potential
- # holes between edge segments
- cvDilate( gray, gray, None, 1 );
- else:
- # apply threshold if l!=0:
- # tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
- cvThreshold( tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY );
-
- # find contours and store them all as a list
- count, contours = cvFindContours( gray, storage, sizeof_CvContour,
- CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) );
-
- if not contours:
- continue
-
- # test each contour
- for contour in contours.hrange():
- # approximate contour with accuracy proportional
- # to the contour perimeter
- result = cvApproxPoly( contour, sizeof_CvContour, storage,
- CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 );
- # square contours should have 4 vertices after approximation
- # relatively large area (to filter out noisy contours)
- # and be convex.
- # Note: absolute value of an area is used because
- # area may be positive or negative - in accordance with the
- # contour orientation
- if( result.total == 4 and
- abs(cvContourArea(result)) > 1000 and
- cvCheckContourConvexity(result) ):
- s = 0;
- for i in range(5):
- # find minimum angle between joint
- # edges (maximum of cosine)
- if( i >= 2 ):
- t = abs(angle( result[i], result[i-2], result[i-1]))
- if s<t:
- s=t
- # if cosines of all angles are small
- # (all angles are ~90 degree) then write quandrange
- # vertices to resultant sequence
- if( s < 0.3 ):
- for i in range(4):
- squares.append( result[i] )
-
- return squares;
-
-# the function draws all the squares in the image
-def drawSquares( img, squares ):
- cpy = cvCloneImage( img );
- # read 4 sequence elements at a time (all vertices of a square)
- i=0
- while i<squares.total:
- pt = []
- # read 4 vertices
- pt.append( squares[i] )
- pt.append( squares[i+1] )
- pt.append( squares[i+2] )
- pt.append( squares[i+3] )
-
- # draw the square as a closed polyline
- cvPolyLine( cpy, [pt], 1, CV_RGB(0,255,0), 3, CV_AA, 0 );
- i+=4
-
- # show the resultant image
- cvShowImage( wndname, cpy );
-
-def on_trackbar( a ):
- if( img ):
- drawSquares( img, findSquares4( img, storage ) );
-
-names = ["../c/pic1.png", "../c/pic2.png", "../c/pic3.png",
- "../c/pic4.png", "../c/pic5.png", "../c/pic6.png" ];
-
-if __name__ == "__main__":
- # create memory storage that will contain all the dynamic data
- storage = cvCreateMemStorage(0);
- for name in names:
- img0 = cvLoadImage( name, 1 );
- if not img0:
- print "Couldn't load %s" % name
- continue;
- img = cvCloneImage( img0 );
- # create window and a trackbar (slider) with parent "image" and set callback
- # (the slider regulates upper threshold, passed to Canny edge detector)
- cvNamedWindow( wndname, 1 );
- cvCreateTrackbar( "canny thresh", wndname, thresh, 1000, on_trackbar );
- # force the image processing
- on_trackbar(0);
- # wait for key.
- # Also the function cvWaitKey takes care of event processing
- c = cvWaitKey(0);
- # clear memory storage - reset free space position
- cvClearMemStorage( storage );
- if( c == '\x1b' ):
- break;
- cvDestroyWindow( wndname );
projects / opencv / blobdiff