class TestDataset:
def __init__(self, opt, split='test', use_difficult=True):
self.opt = opt
if self.opt.data == 'markers':
self.db = MarkersDataset(opt.data_dir)
elif self.opt.data == 'voc':
self.db = VOCBboxDataset(opt.data_dir)
else:
raise Exception('database type not recognised: {}'.format(
self.opt.data))
self.label_names = self.db.get_label_names()
def __getitem__(self, idx):
ori_img, bbox, label, difficult = self.db.get_example(idx)
img = preprocess(ori_img)
return img, ori_img.shape[1:], bbox, label, difficult
def __len__(self):
return len(self.db)
class Dataset:
def __init__(self, opt):
self.opt = opt
if self.opt.data == 'markers':
self.db = MarkersDataset(opt.data_dir)
elif self.opt.data == 'voc':
self.db = VOCBboxDataset(opt.data_dir)
else:
raise Exception('database type not recognised: {}'.format(
self.opt.data))
self.tsf = Transform(opt.min_size, opt.max_size)
self.label_names = self.db.get_label_names()
def __getitem__(self, idx):
ori_img, bbox, label, difficult = self.db.get_example(idx)
img, bbox, label, scale = self.tsf((ori_img, bbox, label))
# TODO: check whose stride is negative to fix this instead copy all
# some of the strides of a given numpy array are negative.
return img.copy(), bbox.copy(), label.copy(), scale
def __len__(self):
return len(self.db)
