def show_point(file):
global totalpoint
img = io.imread(file, as_grey=True)
tt = (get_outline(
fill_image((get_fileter_image(
adjunction_image(np.where(img / 255 > 0.9, 1,
0))))))).astype(np.uint8)
img_filter = get_fileter_image(
adjunction_image(np.where(img / 255 > 0.9, 1, 0)))
fill_img = fill_image(
(get_fileter_image(adjunction_image(np.where(img / 255 > 0.9, 1, 0)))))
fill_img = img_filter
skelenton_image = skeletonize(fill_img)
end_pointx, end_pointy = end_point(skelenton_image)
# plt.subplot(211).imshow(fill_img)
# pp = plt.subplot(212)
# pp.imshow(skelenton_image)
# pp.plot(end_pointy, end_pointx, 'r.')
# plt.show()
# plt.show()
row, col = tt.shape
# get_line(tt)
horizontal_projection = np.sum(tt[:int(col / 2), :], axis=1)
horizontal_projection_t = horizontal_projection[4:-4]
index_zero = np.where(horizontal_projection_t < 2)
index = np.where(
horizontal_projection == np.max(horizontal_projection))[0][0]
if (len(index_zero[0]) != 0):
print("change index position")
index = index_zero[0][0] + 4
# print(horizontal_projection)
print('基线位置： ', index)
pointx, pointy = [], []
vewol_point = []
if (col <= 80):
corners = cv2.goodFeaturesToTrack((tt).astype(np.uint8), 30, 0.2, 7)
else:
corners = cv2.goodFeaturesToTrack((tt).astype(np.uint8),
30,
0.001,
0.05,
blockSize=4)
"""
1.8 skeleton
water: 71.97
outline:
feature point 20,0.25,7 SVM 0.85 81.33 11859-5461
feature point 20,0.30,7 SVM 0.85 79.72 11180-5353
feature point 20,0.20,7 SVM 0.85 82.44 12751-5535
feature point 20,0.20,7 SVM 0.85 82.23 12151-5521 alter-col
1.4 skeleton
water: 67.887
the best result of outline:
feature point 20,0.20,7 SVM 0.85 78.41 12151-5265 alter-col
"""
print(row, col, '行列')
corners = np.int0(corners)
for item in corners:
x, y = item.ravel()
# cv2.circle(img, (x, y), 3, [0, 255, 255], -1)
print(x, 'total', int(col / 3 + 0.5 + 2))
if ((x <= int(col / 3 + 0.5) or x >= int(col / 3 * 2 + 0.5 - 2))
and col <= 80):
print(x, 'now x id')
continue
if ((x <= int(col / 4 + 0.5) or x >= int(col / 4 * 3 + 0.5))
and col > 80):
continue
point_flag = True
if (tt[y][x] == 0):
y, x = alter_point(tt, y, x)
vewol = 0
for i in range(len(end_pointx)):
if ((end_pointy[i] - x) * (end_pointy[i] - x) +
(end_pointx[i] - y) *
(end_pointx[i] - y) < 25) and (abs(y - index) >= 3):
point_flag = False
break
elif (((end_pointy[i] - x) * (end_pointy[i] - x) +
(end_pointx[i] - y) * (end_pointx[i] - y) > 25)
and (index - y >= 2)):
vewol = vewol + 1
if (len(end_pointx) == vewol):
vewol_point.append([x, y])
if (not point_flag):
continue
if (abs(y - index) < 3 and not (total_point(tt, y, x) > 3)
or y < index):
continue
pointx.append(x)
pointy.append(y)
alter_pointx, alter_pointy = alter_index_points(tt, index)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 1)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 2)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 3)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
pointx, pointy = del_near_point(pointx, pointy)
if (len(pointx) == 0):
print("MDZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ")
for item in corners:
x, y = item.ravel()
# cv2.circle(img, (x, y), 3, [0, 255, 255], -1)
point_flag = True
if (tt[y][x] == 0):
y, x = alter_point(tt, y, x)
if (abs(y - index) < 3 and not (total_point(tt, y, x) > 3)):
continue
if (x <= int(col / 3 + 0.5 + 1)
or x >= int(col / 3 * 2 + 0.5 - 1) and col < 80):
continue
if (x <= int(col / 4 + 0.5 + 2)
or x >= int(col / 4 * 3 + 0.5 - 2) and col >= 80):
continue
if (3 < abs(y - index) < 8):
pointx.append(x)
pointy.append(y)
print('vewol: ', vewol_point)
if (len(vewol_point) > 0):
new_vewol = judge_vowel(img_filter, index, vewol_point)
if (len(new_vewol) > 0):
print('newwol: ', new_vewol)
for i in range(len(new_vewol)):
pointx.append(new_vewol[i][0])
pointy.append(new_vewol[i][1])
position_point = get_position(skelenton_image, pointx, pointy)
if (len(pointx) < 1):
print("can't find feature point!")
return 0
result_point = find_segmention_point(adjunction_image(img), index, pointy,
pointx, position_point)
print(pointx)
print(pointy)
print(position_point)
# wrfile.write(os.path.basename(file) + ',')
# for i in range(len(result_point)):
# wrfile.write(str(result_point[i][1] - 3) + ' ' + str(result_point[i][0] - 3) + ' '
# + str(result_point[i][3] - 3) + ' ' + str(result_point[i][2] - 3) + ',')
# wrfile.write('\n')
result_pointx, result_pointy = [], []
for result in result_point:
result_pointy.append(result[0])
result_pointy.append(result[2])
result_pointx.append(result[1])
result_pointx.append(result[3])
p2 = plt.subplot(111)
p2.imshow(
fill_image(
get_fileter_image(adjunction_image(np.where(img / 255 > 0.9, 1,
0)))))
p2.imshow(img)
# print(corners)
# p1 = plt.subplot(212)
# p1.plot([1, col - 1], [index, index])
# if (col <= 80):
# p1.plot([int(col / 3 + 0.5), int(col / 3 + 0.5)], [0, row - 1], label[0])
# p1.plot([int(col / 3 * 2 + 0.5), int(col / 3 * 2 + 0.5)], [0, row - 1], label[0])
# else:
# p1.plot([int(col / 4 + 0.5), int(col / 4 + 0.5)], [0, row - 1], label[0])
# p1.plot([int(col / 4 * 3 + 0.5), int(col / 4 * 3 + 0.5)], [0, row - 1], label[0])
#
for i in range(len(result_point)):
p2.plot([result_point[i][1], result_point[i][3]],
[result_point[i][0], result_point[i][2]], 'b.-')
p2.plot(pointx, pointy, 'rv')
#
# p1.imshow(tt + skelenton_image * 2)
# p1.plot(pointx, pointy, "r.")
p2.imshow(np.where(adjunction_image(img) > 0, 0, 1), cmap='gray')
plt.show()
def show_point(file):
global totalpoint
img = io.imread(file, as_grey=True)
img_filter = get_fileter_image(
adjunction_image(np.where(img / 255 > 0.9, 1, 0)))
fill_img = fill_image(
(get_fileter_image(adjunction_image(np.where(img / 255 > 0.9, 1, 0)))))
skelenton_image = skeletonize(fill_img)
end_pointx, end_pointy = end_point(skelenton_image)
# plt.subplot(211).imshow(fill_img)
# pp = plt.subplot(212)
# pp.imshow(skelenton_image)
# pp.plot(end_pointy, end_pointx, 'r.')
# plt.show()
p2 = plt.subplot(211)
tt = (get_outline(
fill_image((get_fileter_image(
adjunction_image(np.where(img / 255 > 0.9, 1, 0)))))))
p2.imshow(
fill_image(
get_fileter_image(adjunction_image(np.where(img / 255 > 0.9, 1,
0)))))
p2.imshow(img)
# print(corners)
p1 = plt.subplot(212)
# plt.show()
row, col = tt.shape
# get_line(tt)
horizontal_projection = np.sum(tt, axis=1)
# print(horizontal_projection)
index = np.where(
horizontal_projection == np.max(horizontal_projection))[0][0]
print('基线位置： ', index)
# vowel, new_img_vowel = judge_vowel(img_filter,index)
p1.plot([1, col - 1], [index, index])
p1.plot([int(col / 3 + 0.5), int(col / 3 + 0.5)], [0, row - 1], label[0])
if (col < 100):
p1.plot([int(col / 3 * 2 + 0.5),
int(col / 3 * 2 + 0.5)], [0, row - 1], label[0])
else:
p1.plot([int(col / 4 * 3 + 0.5),
int(col / 4 * 3 + 0.5)], [0, row - 1], label[0])
pointx, pointy = [], []
corners = cv2.goodFeaturesToTrack((tt).astype(np.uint8), 20, 0.3, 7)
corners = np.int0(corners)
for item in corners:
x, y = item.ravel()
# cv2.circle(img, (x, y), 3, [0, 255, 255], -1)
point_flag = True
if (tt[y][x] == 0):
y, x = alter_point(tt, y, x)
for i in range(len(end_pointx)):
if ((end_pointy[i] - x) * (end_pointy[i] - x) +
(end_pointx[i] - y) *
(end_pointx[i] - y) < 25) and (abs(y - index) >= 3):
point_flag = False
break
if (not point_flag):
continue
if (abs(y - index) < 3 and not (total_point(tt, y, x) > 3)
or y < index):
continue
if (x <= int(col / 3 + 0.5 + 2)
or x >= int(col / 3 * 2 + 0.5 - 2) and col < 100):
continue
if (x <= int(col / 3 + 0.5 + 2)
or x >= int(col / 4 * 3 + 0.5 - 2) and col > 100):
continue
pointx.append(x)
pointy.append(y)
alter_pointx, alter_pointy = alter_index_points(tt, index)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 1)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 2)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 3)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
pointx, pointy = del_near_point(pointx, pointy)
if (len(pointx) == 0):
print("MDZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ")
for item in corners:
x, y = item.ravel()
# cv2.circle(img, (x, y), 3, [0, 255, 255], -1)
point_flag = True
if (tt[y][x] == 0):
y, x = alter_point(tt, y, x)
if (abs(y - index) < 3 and not (total_point(tt, y, x) > 3)):
continue
if (x <= int(col / 3 + 0.5 + 1)
or x >= int(col / 3 * 2 + 0.5 - 1)):
continue
if (3 < abs(y - index) < 8):
pointx.append(x)
pointy.append(y)
position_point = get_position(skelenton_image, pointx, pointy)
result_point = find_segmention_point(img_filter, index, pointy, pointx,
position_point)
# print(pointx)
# print(pointy)
# print(position_point)
p1.plot(pointx, pointy, "r.")
# tt = tt.astype(np.uint8)
# io.imsave('tt.png', tt * 255)
# tt_new, point1, point2, point3, point4 = find_extreme_point(tt,index)
p1.imshow(tt + skelenton_image * 2)
# p1.plot([point1[1]],[point1[0]], 'g.')
# p1.plot([point2[1]], [point2[0]], 'g.')
# p1.plot([point3[1]], [point3[0]], 'y.')
# p1.plot([point4[1]], [point4[0]], 'y.')
# print([point1[1]], [point1[0]], 'g.')
# print([point2[1]], [point2[0]], 'k.')
# print([point3[1]], [point3[0]], 'y.')
# print([point4[1]], [point4[0]], 'y.')
plt.show()
def show_point(file):
global totalpoint
img = io.imread(file, as_grey=True)
tt = (get_outline(
fill_image((get_fileter_image(
adjunction_image(np.where(img / 255 > 0.9, 1, 0)))))))
img_filter = get_fileter_image(
adjunction_image(np.where(img / 255 > 0.9, 1, 0)))
fill_img = fill_image(
(get_fileter_image(adjunction_image(np.where(img / 255 > 0.9, 1, 0)))))
skelenton_image = skeletonize(fill_img)
end_pointx, end_pointy = end_point(skelenton_image)
# plt.subplot(211).imshow(fill_img)
# pp = plt.subplot(212)
# pp.imshow(skelenton_image)
# pp.plot(end_pointy, end_pointx, 'r.')
# plt.show()
# plt.show()
row, col = tt.shape
# get_line(tt)
horizontal_projection = np.sum(tt[:int(col / 2), :], axis=1)
horizontal_projection_t = horizontal_projection[4:-4]
index_zero = np.where(horizontal_projection_t < 2)
index = np.where(
horizontal_projection == np.max(horizontal_projection))[0][0]
if (len(index_zero[0]) != 0):
print("change index position")
index = index_zero[0][0] + 4
# print(horizontal_projection)
print('基线位置： ', index)
pointx, pointy = [], []
vewol_point = []
corners = cv2.goodFeaturesToTrack((tt).astype(np.uint8), 20, 0.25, 7)
corners = np.int0(corners)
for item in corners:
x, y = item.ravel()
# cv2.circle(img, (x, y), 3, [0, 255, 255], -1)
if (x <= int(col / 3 + 0.5 + 2)
or x >= int(col / 3 * 2 + 0.5 - 2) and col < 100):
continue
if (x <= int(col / 3 + 0.5 + 2)
or x >= int(col / 4 * 3 + 0.5 - 2) and col > 100):
continue
point_flag = True
if (tt[y][x] == 0):
y, x = alter_point(tt, y, x)
vewol = 0
for i in range(len(end_pointx)):
if ((end_pointy[i] - x) * (end_pointy[i] - x) +
(end_pointx[i] - y) *
(end_pointx[i] - y) < 25) and (abs(y - index) >= 3):
point_flag = False
break
elif (((end_pointy[i] - x) * (end_pointy[i] - x) +
(end_pointx[i] - y) * (end_pointx[i] - y) > 25)
and (index - y >= 2)):
vewol = vewol + 1
if (len(end_pointx) == vewol):
vewol_point.append([x, y])
if (not point_flag):
continue
if (abs(y - index) < 3 and not (total_point(tt, y, x) > 3)
or y < index):
continue
pointx.append(x)
pointy.append(y)
alter_pointx, alter_pointy = alter_index_points(tt, index)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 1)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 2)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
alter_pointx, alter_pointy = alter_index_points(tt, index + 3)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
pointx, pointy = del_near_point(pointx, pointy)
if (len(pointx) == 0):
print("MDZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ")
for item in corners:
x, y = item.ravel()
# cv2.circle(img, (x, y), 3, [0, 255, 255], -1)
point_flag = True
if (tt[y][x] == 0):
y, x = alter_point(tt, y, x)
if (abs(y - index) < 3 and not (total_point(tt, y, x) > 3)):
continue
if (x <= int(col / 3 + 0.5 + 1)
or x >= int(col / 3 * 2 + 0.5 - 1)):
continue
if (3 < abs(y - index) < 8):
pointx.append(x)
pointy.append(y)
print('vewol: ', vewol_point)
if (len(vewol_point) > 0):
new_vewol = judge_vowel(img_filter, index, vewol_point)
if (len(new_vewol) > 0):
print('newwol: ', new_vewol)
for i in range(len(new_vewol)):
pointx.append(new_vewol[i][0])
pointy.append(new_vewol[i][1])
position_point = get_position(skelenton_image, pointx, pointy)
if (len(pointx) < 1):
print("can't find feature point!")
return 0
result_point = find_segmention_point(adjunction_image(img), index, pointy,
pointx, position_point)
# print(pointx)
# print(pointy)
# print(position_point)
# wrfile.write(os.path.basename(file) + ',')
# for i in range(len(result_point)):
# wrfile.write(str(result_point[i][1] - 3) + ' ' + str(result_point[i][0] - 3) + ' '
# + str(result_point[i][3] - 3) + ' ' + str(result_point[i][2] - 3) + ',')
# wrfile.write('\n')
result_pointx, result_pointy = [], []
for result in result_point:
result_pointy.append(result[0])
result_pointy.append(result[2])
result_pointx.append(result[1])
result_pointx.append(result[3])
p2 = plt.subplot(211)
p2.imshow(
fill_image(
get_fileter_image(adjunction_image(np.where(img / 255 > 0.9, 1,
0)))))
p2.imshow(img)
# print(corners)
p1 = plt.subplot(212)
p1.plot([1, col - 1], [index, index])
p1.plot([int(col / 3 + 0.5), int(col / 3 + 0.5)], [0, row - 1], label[0])
if (col < 100):
p1.plot([int(col / 3 * 2 + 0.5),
int(col / 3 * 2 + 0.5)], [0, row - 1], label[0])
else:
p1.plot([int(col / 4 * 3 + 0.5),
int(col / 4 * 3 + 0.5)], [0, row - 1], label[0])
p2.plot(result_pointx, result_pointy, 'b.')
p2.imshow(adjunction_image(img))
p1.imshow(tt + skelenton_image * 2)
p1.plot(pointx, pointy, "r.")
plt.show()
def show_point(file):
global totalpoint
img = io.imread(file, as_grey=True)
plt.subplot(111).imshow(img)
plt.show()
p2 = plt.subplot(211)
tt = (get_outline(
fill_image(
del_T_type(
get_fileter_image(
adjunction_image(np.where(img / 255 > 0.9, 1, 0)))))))
p2.imshow(
fill_image(
get_fileter_image(adjunction_image(np.where(img / 255 > 0.9, 1,
0)))))
# print(corners)
p1 = plt.subplot(212)
# plt.show()
row, col = tt.shape
# get_line(tt)
horizontal_projection = np.sum(tt, axis=1)
# print(horizontal_projection)
index = np.where(
horizontal_projection == np.max(horizontal_projection))[0][0]
print('基线位置： ', index)
p1.plot([1, col - 1], [index, index])
pointx, pointy = [], []
corners = cv2.goodFeaturesToTrack((tt).astype(np.uint8), 1000, 0.4, 7)
corners = np.int0(corners)
for item in corners:
x, y = item.ravel()
# cv2.circle(img, (x, y), 3, [0, 255, 255], -1)
if (tt[y][x] == 0):
y, x = alter_point(tt, y, x)
if (abs(y - index) < 8
and not (total_point(tt, y, x) > 3)) or (y < index):
continue
pointx.append(x)
pointy.append(y)
alter_pointx, alter_pointy = alter_index_points(tt, index)
pointx = pointx + alter_pointx
pointy = pointy + alter_pointy
p1.plot(pointx, pointy, "r.")
tt = tt.astype(np.uint8)
io.imsave('tt.png', tt * 255)
tt_new, point1, point2, point3, point4 = find_extreme_point(tt, index)
p1.imshow(tt_new, cmap="gray")
p1.plot([point1[1]], [point1[0]], 'g.')
p1.plot([point2[1]], [point2[0]], 'g.')
p1.plot([point3[1]], [point3[0]], 'y.')
p1.plot([point4[1]], [point4[0]], 'y.')
print([point1[1]], [point1[0]], 'g.')
print([point2[1]], [point2[0]], 'k.')
print([point3[1]], [point3[0]], 'y.')
print([point4[1]], [point4[0]], 'y.')
plt.show()
tem, only_point = [], []
upget_next_feature_point(tt_new, point1[0], point1[1], point1[0],
point1[1] + 1, tem, only_point)
k = len(totalpoint)
print('total path: ', k)
if k % 2 == 1:
for i in range(k):
point = totalpoint[i]
point = np.array(point)
pt = plt.subplot(2, int(k / 2 + 1), i + 1)
pt.imshow(tt_new)
x, y = point[:, 1], point[:, 0]
pt.plot(x, y, str(label[i]))
else:
for i in range(k):
point = totalpoint[i]
point = np.array(point)
pt = plt.subplot(2, int(k / 2), i + 1)
pt.imshow(tt_new)
x, y = point[:, 1], point[:, 0]
pt.plot(x, y, str(label[i]))
totalpoint = []
plt.show()
upget_next_feature_point(tt_new, point3[0], point3[1], point3[0],
point3[1] + 1, tem, only_point)
k = len(totalpoint)
print('total path: ', k)
if k % 2 == 1:
for i in range(k):
point = totalpoint[i]
point = np.array(point)
pt = plt.subplot(2, int(k / 2 + 1), i + 1)
pt.imshow(tt_new)
x, y = point[:, 1], point[:, 0]
pt.plot(x, y, str(label[i]))
else:
for i in range(k):
point = totalpoint[i]
point = np.array(point)
pt = plt.subplot(2, int(k / 2), i + 1)
pt.imshow(tt_new)
x, y = point[:, 1], point[:, 0]
pt.plot(x, y, str(label[i]))
totalpoint = []
plt.show()
