1 #!/usr/bin/env python 2 3 import unittest 4 import random 5 import time 6 import math 7 import sys 8 import array 9 import os 10 11 import cv2.cv as cv 12 13 def find_sample(s): 14 for d in ["../samples/c/", "../doc/pics/"]: 15 path = os.path.join(d, s) 16 if os.access(path, os.R_OK): 17 return path 18 return s 19 20 class TestTickets(unittest.TestCase): 21 22 def test_2542670(self): 23 xys = [(94, 121), (94, 122), (93, 123), (92, 123), (91, 124), (91, 125), (91, 126), (92, 127), (92, 128), (92, 129), (92, 130), (92, 131), (91, 132), (90, 131), (90, 130), (90, 131), (91, 132), (92, 133), (92, 134), (93, 135), (94, 136), (94, 137), (94, 138), (95, 139), (96, 140), (96, 141), (96, 142), (96, 143), (97, 144), (97, 145), (98, 146), (99, 146), (100, 146), (101, 146), (102, 146), (103, 146), (104, 146), (105, 146), (106, 146), (107, 146), (108, 146), (109, 146), (110, 146), (111, 146), (112, 146), (113, 146), (114, 146), (115, 146), (116, 146), (117, 146), (118, 146), (119, 146), (120, 146), (121, 146), (122, 146), (123, 146), (124, 146), (125, 146), (126, 146), (126, 145), (126, 144), (126, 143), (126, 142), (126, 141), (126, 140), (127, 139), (127, 138), (127, 137), (127, 136), (127, 135), (127, 134), (127, 133), (128, 132), (129, 132), (130, 131), (131, 130), (131, 129), (131, 128), (132, 127), (133, 126), (134, 125), (134, 124), (135, 123), (136, 122), (136, 121), (135, 121), (134, 121), (133, 121), (132, 121), (131, 121), (130, 121), (129, 121), (128, 121), (127, 121), (126, 121), (125, 121), (124, 121), (123, 121), (122, 121), (121, 121), (120, 121), (119, 121), (118, 121), (117, 121), (116, 121), (115, 121), (114, 121), (113, 121), (112, 121), (111, 121), (110, 121), (109, 121), (108, 121), (107, 121), (106, 121), (105, 121), (104, 121), (103, 121), (102, 121), (101, 121), (100, 121), (99, 121), (98, 121), (97, 121), (96, 121), (95, 121)] 24 25 #xys = xys[:12] + xys[16:] 26 pts = cv.CreateMat(len(xys), 1, cv.CV_32SC2) 27 for i,(x,y) in enumerate(xys): 28 pts[i,0] = (x, y) 29 storage = cv.CreateMemStorage() 30 hull = cv.ConvexHull2(pts, storage) 31 hullp = cv.ConvexHull2(pts, storage, return_points = 1) 32 defects = cv.ConvexityDefects(pts, hull, storage) 33 34 vis = cv.CreateImage((1000,1000), 8, 3) 35 x0 = min([x for (x,y) in xys]) - 10 36 x1 = max([x for (x,y) in xys]) + 10 37 y0 = min([y for (y,y) in xys]) - 10 38 y1 = max([y for (y,y) in xys]) + 10 39 def xform(pt): 40 x,y = pt 41 return (1000 * (x - x0) / (x1 - x0), 42 1000 * (y - y0) / (y1 - y0)) 43 44 for d in defects[:2]: 45 cv.Zero(vis) 46 47 # First draw the defect as a red triangle 48 cv.FillConvexPoly(vis, [xform(p) for p in d[:3]], cv.RGB(255,0,0)) 49 50 # Draw the convex hull as a thick green line 51 for a,b in zip(hullp, hullp[1:]): 52 cv.Line(vis, xform(a), xform(b), cv.RGB(0,128,0), 3) 53 54 # Draw the original contour as a white line 55 for a,b in zip(xys, xys[1:]): 56 cv.Line(vis, xform(a), xform(b), (255,255,255)) 57 58 self.snap(vis) 59 60 def test_2686307(self): 61 lena = cv.LoadImage(find_sample("lena.jpg"), 1) 62 dst = cv.CreateImage((512,512), 8, 3) 63 cv.Set(dst, (128,192,255)) 64 mask = cv.CreateImage((512,512), 8, 1) 65 cv.Zero(mask) 66 cv.Rectangle(mask, (10,10), (300,100), 255, -1) 67 cv.Copy(lena, dst, mask) 68 self.snapL([lena, dst, mask]) 69 m = cv.CreateMat(480, 640, cv.CV_8UC1) 70 print "ji", m 71 print m.rows, m.cols, m.type, m.step 72 73 def snap(self, img): 74 self.snapL([img]) 75 76 def snapL(self, L): 77 for i,img in enumerate(L): 78 cv.NamedWindow("snap-%d" % i, 1) 79 cv.ShowImage("snap-%d" % i, img) 80 cv.WaitKey() 81 cv.DestroyAllWindows() 82 83 if __name__ == '__main__': 84 random.seed(0) 85 if len(sys.argv) == 1: 86 suite = unittest.TestLoader().loadTestsFromTestCase(TestTickets) 87 unittest.TextTestRunner(verbosity=2).run(suite) 88 else: 89 suite = unittest.TestSuite() 90 suite.addTest(TestTickets(sys.argv[1])) 91 unittest.TextTestRunner(verbosity=2).run(suite) 92
