def delete_one_edge(self, contour, inliner_idx, d, p):
'''
从contour中删除和第p个未被分配的点在同一条直线上的点，点到直线的最大距离为d
@param contour: 轮廓
@param inliner_idx: 当前点已经完成的分配
@param d: 最大偏差
@param p: 中心点的位置
'''
assert isinstance(contour, np.ndarray)
counter = 0
center = 0 # when the contour is shorter than p, center will be 0
for k, v in enumerate(inliner_idx):
counter = counter + 1 if v == -1 else counter
if counter == p:
center = k
break
# TODO: determine Region of Support (ROS)
points = get_elements_in_window(contour, center, 2)
# get line in format (vx, vy, x0, y0)
line = cv2.fitLine(np.asarray(points, dtype=np.float32),
cv2.cv.CV_DIST_L2, 0, 0.01, 0.01)
vx = line[0]
vy = line[1]
n = np.asarray([vx, vy])
n = np.squeeze(n)
a = np.asarray([line[2], line[3]])
a = np.squeeze(a)
self.set_adjacent_inliner(contour, inliner_idx, center, n, a, d)
return inliner_idx
def delete_one_edge(self, contour, inliner_idx, d, p):
'''
从contour中删除和第p个未被分配的点在同一条直线上的点，点到直线的最大距离为d
@param contour: 轮廓
@param inliner_idx: 当前点已经完成的分配
@param d: 最大偏差
@param p: 中心点的位置
'''
assert isinstance(contour, np.ndarray)
counter = 0
center = 0 # when the contour is shorter than p, center will be 0
for k, v in enumerate(inliner_idx):
counter = counter + 1 if v == -1 else counter
if counter == p:
center = k
break
# TODO: determine Region of Support (ROS)
points = get_elements_in_window(contour, center, 2)
# get line in format (vx, vy, x0, y0)
line = cv2.fitLine(np.asarray(points,
dtype=np.float32),
cv2.cv.CV_DIST_L2,
0, 0.01, 0.01)
vx = line[0]
vy = line[1]
n = np.asarray([vx, vy])
n = np.squeeze(n)
a = np.asarray([line[2], line[3]])
a = np.squeeze(a)
self.set_adjacent_inliner(contour, inliner_idx, center, n, a, d)
return inliner_idx
def filter_indexes(self, indexes, w=1):
'''
使用类似中值滤波的技术，对轮廓进行去噪
@param indexes: 轮廓
@param w: 窗口的大小
'''
assert isinstance(indexes, list)
indexes_ret = []
n = len(indexes)
for i in xrange(n):
indexes_ret.append(np.median(get_elements_in_window(indexes, i,
w)))
return indexes_ret
def filter_indexes(self, indexes, w=1):
'''
使用类似中值滤波的技术，对轮廓进行去噪
@param indexes: 轮廓
@param w: 窗口的大小
'''
assert isinstance(indexes, list)
indexes_ret = []
n = len(indexes)
for i in xrange(n):
indexes_ret.append(
np.median(get_elements_in_window(indexes, i, w))
)
return indexes_ret
def test_indexes_in_window_case4(self):
indexes = [2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 1]
ret_indexes = get_elements_in_window(indexes, 18, 1)
expected_indexes = np.array([2, 2, 1], dtype=np.float32)
self.assertItemsEqual(ret_indexes, expected_indexes)
def test_indexes_in_window_case3(self):
indexes = [2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 1]
ret_indexes = get_elements_in_window(indexes, 2, 2)
expected_indexes = [2, 2, 2, 0, 0]
self.assertItemsEqual(ret_indexes, expected_indexes)
def test_indexes_in_window_case4(self):
indexes = [2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 1]
ret_indexes = get_elements_in_window(indexes, 18, 1)
expected_indexes = np.array([2, 2, 1], dtype=np.float32)
self.assertItemsEqual(ret_indexes, expected_indexes)
def test_indexes_in_window_case3(self):
indexes = [2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 1]
ret_indexes = get_elements_in_window(indexes, 2, 2)
expected_indexes = [2, 2, 2, 0, 0]
self.assertItemsEqual(ret_indexes, expected_indexes)