def __getitem__(self, index):
datafiles = self.files[index]
image = Image.open(datafiles["img"]).convert('RGB')
label = Image.open(datafiles["label"])
size = np.asarray(image).shape
name = datafiles["name"]
composed_transforms = transforms.Compose([
tr.Normalize(mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225)),
tr.ToTensor()])
sample = {'image': image, 'label': label}
sampled = composed_transforms(sample)
image, label = sampled['image'], sampled['label']
return image, label, np.array(size), name
def __getitem__(self, index):
datafiles = self.files[index]
image = Image.open(datafiles["img"]).convert('RGB')
label = Image.open(datafiles["label"])
size = np.asarray(image).shape
name = datafiles["name"]
composed_transforms = transforms.Compose([
tr.RandomHorizontalFlip(),
# tr.RandomRotate(180),
tr.RandomScaleCrop(base_size=self.base_size, crop_size=self.crop_size, fill=255),
tr.RandomGaussianBlur(),
tr.Normalize(mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225)),
tr.ToTensor()])
sample = {'image': image, 'label': label}
sampled = composed_transforms(sample)
image, label = sampled['image'], sampled['label']
return image, label, np.array(size), name