def __init__(self, opts):
self.data_root = opts.data_root
self.device = opts.device
hr_list = os.path.join(opts.test_filelist)
self.datasets_hr = pd.read_csv(hr_list, header=None)
self.noises_mean, self.noise_yuv, self.noises_weight = get_noises_list(
opts.noise_path, 0.5)
def __init__(self, opts):
self.data_root = opts.data_root
self.device = opts.device
hr_list = os.path.join(opts.test_filelist)
self.datasets_hr = pd.read_csv(hr_list, header=None)
self.noises_mean, self.noise_yuv, self.noises_weight = get_noises_list(
opts.noise_path, 1)
self.transform = transforms.Compose([
# transforms.Resize(256),
transforms.RandomCrop(256),
transforms.ToTensor(),
])
def __init__(self, opts):
self.data_root = opts.data_root
self.device = opts.device
self.main_path = opts.main_path
hr_list = os.path.join(opts.val_filelist)
self.datasets_hr = pd.read_csv(hr_list, header=None)
self.noises_mean, self.noise_yuv, self.noises_weight = get_noises_list(
opts.noise_path, 1)
self.with_possion = opts.with_possion
self.imgfilter_l = opts.imgfilter_l
self.imgfilter_h = opts.imgfilter_h
self.with_texturesyn_thesis = opts.with_texturesyn_thesis
self.transform = transforms.Compose([
# transforms.Resize(256),
transforms.CenterCrop(opts.centralcropsize),
transforms.RandomCrop(opts.cropsize),
transforms.ToTensor(),
])