def test_2542670(self):
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)]
#xys = xys[:12] + xys[16:]
pts = cv.CreateMat(len(xys), 1, cv.CV_32SC2)
for i,(x,y) in enumerate(xys):
pts[i,0] = (x, y)
storage = cv.CreateMemStorage()
hull = cv.ConvexHull2(pts, storage)
hullp = cv.ConvexHull2(pts, storage, return_points = 1)
defects = cv.ConvexityDefects(pts, hull, storage)
vis = cv.CreateImage((1000,1000), 8, 3)
x0 = min([x for (x,y) in xys]) - 10
x1 = max([x for (x,y) in xys]) + 10
y0 = min([y for (y,y) in xys]) - 10
y1 = max([y for (y,y) in xys]) + 10
def xform(pt):
x,y = pt
return (1000 * (x - x0) / (x1 - x0),
1000 * (y - y0) / (y1 - y0))
for d in defects[:2]:
cv.Zero(vis)
# First draw the defect as a red triangle
cv.FillConvexPoly(vis, [xform(p) for p in d[:3]], cv.RGB(255,0,0))
# Draw the convex hull as a thick green line
for a,b in zip(hullp, hullp[1:]):
cv.Line(vis, xform(a), xform(b), cv.RGB(0,128,0), 3)
# Draw the original contour as a white line
for a,b in zip(xys, xys[1:]):
cv.Line(vis, xform(a), xform(b), (255,255,255))
self.snap(vis)
# get a random number of points
count = my_random.randrange(0, _MAX_POINTS) + 1
# initialisations
points = []
for i in range(count):
# generate a random point
points.append(
(my_random.randrange(0, image.width / 2) + image.width / 4,
my_random.randrange(0, image.width / 2) + image.width / 4))
# compute the convex hull
storage = cv.CreateMemStorage(0)
hull = cv.ConvexHull2(points, storage, cv.CV_CLOCKWISE, 1)
# start with an empty image
cv.SetZero(image)
# draw all the points as circles in red
for i in range(count):
cv.Circle(image, points[i], 2, (0, 0, 255, 0), cv.CV_FILLED,
cv.CV_AA, 0)
# Draw the convex hull as a closed polyline in green
cv.PolyLine(image, [hull], 1, cv.RGB(0, 255, 0), 1, cv.CV_AA)
# display the final image
cv.ShowImage('hull', image)