108 lines
3.8 KiB
Python
108 lines
3.8 KiB
Python
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#!/usr/bin/python
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import urllib2
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import sys
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import cv
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class Sketcher:
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def __init__(self, windowname, dests):
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self.prev_pt = None
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self.windowname = windowname
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self.dests = dests
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cv.SetMouseCallback(self.windowname, self.on_mouse)
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def on_mouse(self, event, x, y, flags, param):
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pt = (x, y)
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if event == cv.CV_EVENT_LBUTTONUP or not (flags & cv.CV_EVENT_FLAG_LBUTTON):
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self.prev_pt = None
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elif event == cv.CV_EVENT_LBUTTONDOWN:
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self.prev_pt = pt
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elif event == cv.CV_EVENT_MOUSEMOVE and (flags & cv.CV_EVENT_FLAG_LBUTTON) :
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if self.prev_pt:
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for dst in self.dests:
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cv.Line(dst, self.prev_pt, pt, cv.ScalarAll(255), 5, 8, 0)
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self.prev_pt = pt
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cv.ShowImage(self.windowname, img)
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if __name__ == "__main__":
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if len(sys.argv) > 1:
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img0 = cv.LoadImage( sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
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else:
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url = 'https://code.ros.org/svn/opencv/trunk/opencv/samples/c/fruits.jpg'
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filedata = urllib2.urlopen(url).read()
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imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
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cv.SetData(imagefiledata, filedata, len(filedata))
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img0 = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
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rng = cv.RNG(-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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cv.NamedWindow("image", 1)
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cv.NamedWindow("watershed transform", 1)
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img = cv.CloneImage(img0)
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img_gray = cv.CloneImage(img0)
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wshed = cv.CloneImage(img0)
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marker_mask = cv.CreateImage(cv.GetSize(img), 8, 1)
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markers = cv.CreateImage(cv.GetSize(img), cv.IPL_DEPTH_32S, 1)
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cv.CvtColor(img, marker_mask, cv.CV_BGR2GRAY)
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cv.CvtColor(marker_mask, img_gray, cv.CV_GRAY2BGR)
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cv.Zero(marker_mask)
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cv.Zero(wshed)
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cv.ShowImage("image", img)
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cv.ShowImage("watershed transform", wshed)
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sk = Sketcher("image", [img, marker_mask])
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while True:
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c = cv.WaitKey(0) % 0x100
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if c == 27 or c == ord('q'):
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break
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if c == ord('r'):
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cv.Zero(marker_mask)
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cv.Copy(img0, img)
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cv.ShowImage("image", img)
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if c == ord('w'):
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storage = cv.CreateMemStorage(0)
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#cv.SaveImage("wshed_mask.png", marker_mask)
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#marker_mask = cv.LoadImage("wshed_mask.png", 0)
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contours = cv.FindContours(marker_mask, storage, cv.CV_RETR_CCOMP, cv.CV_CHAIN_APPROX_SIMPLE)
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def contour_iterator(contour):
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while contour:
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yield contour
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contour = contour.h_next()
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cv.Zero(markers)
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comp_count = 0
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for c in contour_iterator(contours):
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cv.DrawContours(markers,
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c,
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cv.ScalarAll(comp_count + 1),
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cv.ScalarAll(comp_count + 1),
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-1,
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-1,
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8)
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comp_count += 1
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cv.Watershed(img0, markers)
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cv.Set(wshed, cv.ScalarAll(255))
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# paint the watershed image
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color_tab = [(cv.RandInt(rng) % 180 + 50, cv.RandInt(rng) % 180 + 50, cv.RandInt(rng) % 180 + 50) for i in range(comp_count)]
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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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wshed[j, i] = color_tab[int(idx - 1)]
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cv.AddWeighted(wshed, 0.5, img_gray, 0.5, 0, wshed)
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cv.ShowImage("watershed transform", wshed)
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