ValueError: A Concatenate layer requires inputs with matching shapes except for the concat axis

[amirnasab]

I wanted to use voxelmorph pretrained brain_3D model and test my data
my input data is in shape of:
(119,512,512)
and ive kept nb_features as deflaut:
nb_features = [
[16, 32, 32, 32],
[32, 32, 32, 32, 32, 16, 16]
]

but it buils up an error:
ValueError: A Concatenate layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 28, 128, 128, 32), (None, 29, 128, 128, 32)]

I cant get what the problem is. can anyone help me?

[Ehsan-data]

use this code to resize your data. Hope it helps:

import itertools

def resize_data(data):
initial_size_x = data.shape[0]
initial_size_y = data.shape[1]
initial_size_z = data.shape[2]
new_size_x = 160
new_size_y = 192
new_size_z = 224
delta_x = initial_size_x / new_size_x
delta_y = initial_size_y / new_size_y
delta_z = initial_size_z / new_size_z
new_data = np.zeros((new_size_x, new_size_y, new_size_z))
for x, y, z in itertools.product(range(new_size_x), range(new_size_y), range(new_size_z)):
new_data[x][y][z] = data[int(x * delta_x)][int(y * delta_y)][int(z * delta_z)]
return new_data