def contourmethod(self, edges):
hull = None
contours, hierarchy = cv2.findContours(edges, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(self.source_color, contours, -1, (0, 0, 255), 1)
#cv2.imshow("contours", self.source_color)
print hierarchy
c = max(contours, key=cv2.contourArea)
cv2.drawContours(self.source_color, c, -1, (0, 0, 0), 3)
#cv2.imshow("max_contour", self.source_color)
cv2.waitKey(0)
for i, cnt in enumerate(contours):
if hierarchy[
0, i,
3] == -1 and cv2.contourArea(cnt) >= cv2.contourArea(c):
hull = cv2.convexHull(cnt, returnPoints=True)
break
print hull
cv2.drawContours(self.source_color, [hull], -1, (255, 255, 0), 1)
#cv2.imshow("hull", self.source_color)
cv2.waitKey(0)
length = len(hull)
M = cv2.moments(hull)
if M['m00'] == 0:
M['m00'] = 0.01
self.cx = int(M['m10'] / M['m00'])
self.cy = int(M['m01'] / M['m00'])
center = [self.cx, self.cy]
#cv2.circle(self.source_color, (self.cx, self.cy), 5, (0, 255, 255), 2)
print length
coord = Coordinates()
for i in xrange(0, length):
if (i + 3) < length:
[x, y] = coord.intersection(
(hull[i][0][0], hull[i][0][1]),
(hull[i + 1][0][0], hull[i + 1][0][1]),
(hull[i + 2][0][0], hull[i + 2][0][1]),
(hull[i + 3][0][0], hull[i + 3][0][1]))
coord.append(x, y)
cv2.circle(self.source_color, (x, y), 6, (255, 255, 255), 2)
#cv2.imshow("coordinates", self.source_color)
#cv2.waitKey(0)
return coord, center
def get_coordinates_houghP(self, edges):
constant = 100
minLineLength = 10
maxLineGap = 5
coord = Coordinates()
lines = cv2.HoughLinesP(edges, 1, np.pi / 180, constant, minLineLength, maxLineGap)
print lines, type(lines)
points = []
for x1, y1, x2, y2 in lines[0]:
points.append([x1, y1])
points.append([x2, y2])
[x, y] = coord.intersection(points[0], points[1], points[2], points[3])
coord.append(x, y)
# cv2.line(edges, (x1, y1), (x2, y2), (0, 255, 0), 2)
# cv2.imshow("line", edges)
# cv2.waitKey(0)
return coord
def get_coordinates_houghP(self, edges):
constant = 100
minLineLength = 10
maxLineGap = 5
coord = Coordinates()
lines = cv2.HoughLinesP(edges, 1, np.pi / 180, constant, minLineLength,
maxLineGap)
print lines, type(lines)
points = []
for x1, y1, x2, y2 in lines[0]:
points.append([x1, y1])
points.append([x2, y2])
[x, y] = coord.intersection(points[0], points[1], points[2], points[3])
coord.append(x, y)
# cv2.line(edges, (x1, y1), (x2, y2), (0, 255, 0), 2)
# cv2.imshow("line", edges)
# cv2.waitKey(0)
return coord
def contourmethod(self, edges):
hull = None
contours, hierarchy = cv2.findContours(edges, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
print hierarchy
for i, cnt in enumerate(contours):
if hierarchy[0, i, 3] == -1 and cv2.contourArea(cnt) > 5000:
hull = cv2.convexHull(cnt, returnPoints=True)
break
print hull
length = len(hull)
print length
coord = Coordinates()
for i in xrange(0, length):
if (i + 3) < length:
[x, y] = coord.intersection(
(hull[i][0][0], hull[i][0][1]),
(hull[i + 1][0][0], hull[i + 1][0][1]),
(hull[i + 2][0][0], hull[i + 2][0][1]),
(hull[i + 3][0][0], hull[i + 3][0][1]))
coord.append(x, y)
return coord
def contourmethod(self, edges):
hull = None
contours, hierarchy = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
print hierarchy
for i, cnt in enumerate(contours):
if hierarchy[0, i, 3] == -1 and cv2.contourArea(cnt) > 5000:
hull = cv2.convexHull(cnt, returnPoints=True)
break
print hull
length = len(hull)
print length
coord = Coordinates()
for i in xrange(0, length):
if (i + 3) < length:
[x, y] = coord.intersection(
(hull[i][0][0], hull[i][0][1]),
(hull[i + 1][0][0], hull[i + 1][0][1]),
(hull[i + 2][0][0], hull[i + 2][0][1]),
(hull[i + 3][0][0], hull[i + 3][0][1]),
)
coord.append(x, y)
return coord
