REVA-QCAV/src/utils/dataset.py
Laurent Fainsin 7bdac6583b feat: binarized the masks + lots of new metrics to fix
Former-commit-id: c840d14f722503d241f6bb6d899630ad6345aca0 [formerly e435a21234620add4f0e4e269a4141e5c1508cd9]
Former-commit-id: 8006af185fd68cc88b2305a02513106c16758d77
2022-06-30 23:28:38 +02:00

33 lines
922 B
Python

import os
import numpy as np
from PIL import Image
from torch.utils.data import Dataset
class SphereDataset(Dataset):
def __init__(self, image_dir, transform=None):
self.image_dir = image_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])
image = np.array(Image.open(img_path).convert("RGB"), dtype=np.uint8)
mask = np.zeros((image.shape[0], image.shape[1]), dtype=np.uint8)
if self.transform is not None:
augmentations = self.transform(image=image, mask=mask)
image = augmentations["image"]
mask = augmentations["mask"]
# make sure image and mask are floats
image = image.float()
mask = mask.float()
return image, mask