if __name__ == '__main__':
#
# Load configurations
#
try:
config_path = sys.argv[1]
except IndexError:
config_path = "train.yml"
opt = DictAsMember(yaml_load(config_path))
#
# Instantiate models
#
model = load_from_file(opt.network, 'IlluminationPredictorNet', opt)
#
# Instantiate loaders
#
ldr_image_handler = LDRImageHandler(opt.ldr_mean_std)
hdr_image_handler = HDRImageHandler(opt.hdr_mean_std,
perform_scale_perturbation=False)
train_dataset = IlluminationPredictorDataset(opt.data_path,
dataset_purpose='train',
configs=opt,
transform=ldr_image_handler)
valid_dataset = IlluminationPredictorDataset(opt.data_path,
dataset_purpose='valid',
configs=opt,
if __name__ == '__main__':
#
# Load configurations
#
try:
config_path = sys.argv[1]
except IndexError:
config_path = "test.yml"
opt = DictAsMember(yaml_load(config_path))
#
# Instantiate models
#
model = load_from_file(opt.network, 'AutoEncoderNet')
#
# Instantiate loaders
#
hdr_image_handler = HDRImageHandler(opt.mean_std,
perform_scale_perturbation=False)
test_dataset = AutoEncoderDataset(
opt.data_path, transform=hdr_image_handler.normalization_ops)
test_loader = data.DataLoader(test_dataset,
batch_size=1,
num_workers=0,
pin_memory=True)