def __init__(self, configer):
self.configer = configer
if self.configer.get('data', 'image_tool') == 'pil':
self.aug_train_transform = pil_aug_trans.PILAugCompose(
self.configer, split='train')
elif self.configer.get('data', 'image_tool') == 'cv2':
self.aug_train_transform = cv2_aug_trans.CV2AugCompose(
self.configer, split='train')
else:
Log.error('Not support {} image tool.'.format(
self.configer.get('data', 'image_tool')))
exit(1)
if self.configer.get('data', 'image_tool') == 'pil':
self.aug_val_transform = pil_aug_trans.PILAugCompose(self.configer,
split='val')
elif self.configer.get('data', 'image_tool') == 'cv2':
self.aug_val_transform = cv2_aug_trans.CV2AugCompose(self.configer,
split='val')
else:
Log.error('Not support {} image tool.'.format(
self.configer.get('data', 'image_tool')))
exit(1)
self.img_transform = trans.Compose([
trans.ToTensor(),
trans.Normalize(**self.configer.get('data', 'normalize')),
])
self.label_transform = trans.Compose([
trans.ToLabel(),
trans.ReLabel(255, -1),
])
def __init__(self, configer):
self.configer = configer
if self.configer.get('data', 'image_tool') == 'pil':
self.aug_test_transform = pil_aug_trans.PILAugCompose(self.configer, split='test')
elif self.configer.get('data', 'image_tool') == 'cv2':
self.aug_test_transform = cv2_aug_trans.CV2AugCompose(self.configer, split='test')
else:
Log.error('Not support {} image tool.'.format(self.configer.get('data', 'image_tool')))
exit(1)
self.img_transform = Compose([
ToTensor(),
Normalize(**self.configer.get('data', 'normalize')), ])