forked from sacmehta/3D-ESPNet
-
Notifications
You must be signed in to change notification settings - Fork 0
/
DataSet.py
33 lines (28 loc) · 1.11 KB
/
DataSet.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
#============================================
__author__ = "Sachin Mehta"
__license__ = "MIT"
__maintainer__ = "Sachin Mehta"
#============================================
import torch.utils.data
import nibabel as nib
'''
Custom dataset loader
'''
class MyDataset(torch.utils.data.Dataset):
def __init__(self, imList, labelList, transform=None):
self.imList = imList
self.labelList = labelList
self.transform = transform
def __len__(self):
return len(self.imList)
def __getitem__(self, idx):
image_name = self.imList[idx]
label_name = self.labelList[idx]
image1 = nib.load(image_name).get_data() # flair
image2 = nib.load(image_name.replace('flair', 't1')).get_data()
image3 = nib.load(image_name.replace('flair', 't1ce')).get_data()
image4 = nib.load(image_name.replace('flair', 't2')).get_data()
label = nib.load(label_name).get_data()
if self.transform:
[image1, image2, image3, image4, label] = self.transform(image1, image2, image3, image4, label)
return (image1, image2, image3, image4, label)