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import torch.utils.data as data
import utils.utils_image as util
class DatasetL(data.Dataset):
'''
# -----------------------------------------
# Get L in testing.
# Only "dataroot_L" is needed.
# -----------------------------------------
# -----------------------------------------
'''
def __init__(self, opt):
super(DatasetL, self).__init__()
print('Read L in testing. Only "dataroot_L" is needed.')
self.opt = opt
self.n_channels = opt['n_channels'] if opt['n_channels'] else 3
# ------------------------------------
# get the path of L
# ------------------------------------
self.paths_L = util.get_image_paths(opt['dataroot_L'])
assert self.paths_L, 'Error: L paths are empty.'
def __getitem__(self, index):
L_path = None
# ------------------------------------
# get L image
# ------------------------------------
L_path = self.paths_L[index]
img_L = util.imread_uint(L_path, self.n_channels)
# ------------------------------------
# HWC to CHW, numpy to tensor
# ------------------------------------
img_L = util.uint2tensor3(img_L)
return {'L': img_L, 'L_path': L_path}
def __len__(self):
return len(self.paths_L)
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