-
Notifications
You must be signed in to change notification settings - Fork 0
/
dataset.py
29 lines (24 loc) · 1002 Bytes
/
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
import os
from PIL import Image
from torch.utils.data import Dataset
import numpy as np
class CanvanaDataset(Dataset):
def __init__(self, image_dir, mask_dir, transform=None):
self.image_dir = image_dir
self.mask_dir = mask_dir
self.transform = transform
self.images = os.listdir(image_dir)
def __len__(self):
return len(self.images)
def __getitem__(self, index):
img_path = os.path.join(self.image_dir, self.images[index])
mask_path = os.path.join(self.mask_dir, self.images[index].replace(".jpg", "_mask.gif"))
image = np.array(Image.open(img_path).convert("RGB"))
mask = np.array(Image.open(mask_path).convert("L"), dtype=np.float32)
# 0.0, 255.0
mask[mask == 255.0] = 1.0
if self.transform is not None:
augmentations = self.transform(image=image, mask=mask)
image = augmentations["image"]
mask = augmentations["mask"]
return image, mask