if gt_path is None:
data = itertools.zip_longest(raw_files, [])
else:
gt_files = sorted(gt_path.glob('*.tif'))
if len(raw_files) != len(gt_files):
raise ValueError(
'Mismatch between raw and ground truth file counts '
f'({len(raw_files)} vs. {len(gt_files)})')
data = zip(raw_files, gt_files)
else:
data = [(input_path, gt_path)]
model_path = get_model_path(args.model_dir)
print('Loading model from', model_path)
model = load_model(str(model_path), input_shape=args.block_shape)
if args.block_overlap_shape is None:
overlap_shape = [
max(1, x // 8) if x > 2 else 0
for x in model.input.shape.as_list()[1:-1]
]
else:
overlap_shape = args.block_overlap_shape
if args.scale_value is None:
sValue = 2000
else:
sValue = args.scale_value
step2_output_path.mkdir(parents=True)
if config['step3_trigger'] and config[
'step3_output_trigger'] and not step3_output_path.exists():
print('Creating step3 output directory', step3_output_path)
step3_output_path.mkdir(parents=True)
if input_path.is_dir():
data = sorted(input_path.glob('*.tif'))
# raw_files = sorted(input_path.glob('*.tif'))
# data = itertools.zip_longest(raw_files, [])
else:
data = input_path
if config['step1_trigger']:
step1_model_path = get_model_path(config['step1_model_dir'])
print('Loading step1 model from', step1_model_path)
step1_model = load_model(str(step1_model_path),
input_shape=config['step1_block_shape'])
if config['step1_block_overlap_shape'] is None:
step1_overlap_shape = [
max(1, x // 8) if x > 2 else 0
for x in step1_model.input.shape.as_list()[1:-1]
]
else:
step1_overlap_shape = config['step1_block_overlap_shape']
if config['step2_trigger']:
step2_model_path = get_model_path(config['step2_model_dir'])
print('Loading step2 model from', step2_model_path)