mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
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107 lines
3.8 KiB
107 lines
3.8 KiB
#!/usr/bin/python |
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import urllib2 |
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import sys |
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import cv2.cv as 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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