I used supervise.ly 1 tool to manually create masks. However, the order and assignment of mask labels are not consistent across images. Is it possible to redefine the order and assignment of them?
Note: If this problem needs mask label annotations you can download them from here.
Input- 1
Order
[0 3 4 5 6 7 8]

Assignment
0 - unlabeled
3 - left_psoas
4 - right_psoas
5 - left_erector
6 - right_erector
7 - left_rectus
8 - right_rectus

Input-2
Order
[0 3 4 5 6 7 8]

Assignment
0 - unlabeled
3 - left_rectus
4 - right_rectus
5 - left_psoas
6 - right_psoas
7 - left_erector
8 - right_erector

I want something like this
output-1
Order
[0 1, 2, 3, 4, 5, 6]

Assignment
0 - unlabeled
1 - left_psoas
2 - right_psoas
3 - left_erector
4 - right_erector
5 - left_rectus
6 - right_rectus

output-2
Order
[0 1, 2, 3, 4, 5, 6]

Assignment
0 - unlabeled
1 - left_psoas
2 - right_psoas
3 - left_erector
4 - right_erector
5 - left_rectus
6 - right_rectus

Reproducible_example
Input-1
numpy.set_printoptions(threshold=sys.maxsize)

#IM-0010-0007 - Rectus, Psoas

mask = Image.open(urlopen('https://user-images.githubusercontent.com/3885659/78283975-27721000-750e-11ea-8c0b-57d682c45f18.png'))
#plt.imshow(mask)
array = np.array(mask)
#print('Array Dimensions', array.shape)
new_array = [tuple(row) for row in array]
uniques = np.unique(new_array)
print(uniques)

#IM-0010-0010 - Rectus, Psoas, Erector

mask = Image.open(urlopen('https://user-images.githubusercontent.com/3885659/78284008-38228600-750e-11ea-95cc-0e71c1c90ade.png'))
array = np.array(mask)
new_array = [tuple(row) for row in array]
uniques = np.unique(new_array)
print(uniques)

#IM-0010-0011 - Rectus, Erector

mask = Image.open(urlopen('https://user-images.githubusercontent.com/3885659/78284035-453f7500-750e-11ea-8439-d26b9168c805.png'))
array = np.array(mask)
new_array = [tuple(row) for row in array]
uniques = np.unique(new_array)
print(uniques)

Input-2

numpy.set_printoptions(threshold=sys.maxsize)

# IM-0010-0005 - Rectus

mask = Image.open(urlopen('https://user-images.githubusercontent.com/3885659/78290155-cef14180-7512-11ea-96f4-c7f0ad9566b4.png'))
array = np.array(mask)
new_array = [tuple(row) for row in array]
uniques = np.unique(new_array)
print(uniques)

# IM-0010-0006 - Rectus, Psoas

mask = Image.open(urlopen('https://user-images.githubusercontent.com/3885659/78290189-dd3f5d80-7512-11ea-9eab-d0f861c5bf16.png'))
array = np.array(mask)
new_array = [tuple(row) for row in array]
uniques = np.unique(new_array)
print(uniques)

# IM-0010-0008 - Rectus, Psoas, Erector

mask = Image.open(urlopen('https://user-images.githubusercontent.com/3885659/78290216-eb8d7980-7512-11ea-9b17-1f1c1c170886.png'))
array = np.array(mask)
new_array = [tuple(row) for row in array]
uniques = np.unique(new_array)
print(uniques)