def parse_operation_sequence(op_name, resol, return_str=False, stack=None):
inverse = op_name.startswith('-')
if inverse:
op_name = op_name[1:]
#op = load_ini(os.path.join(DATA_ROOTDIR, 'CSHL_data_processed', stack, 'operation_configs', op_name + '.ini'))
op_path = os.path.join(DATA_ROOTDIR, 'CSHL_data_processed', stack,
'operation_configs', op_name + '.ini')
op = load_ini(op_path)
#print op
if op is None:
raise Exception("Cannot load %s.ini" % op_name)
if 'operation_sequence' in op: # composite operation
assert not inverse, "Inverse composite operation is not implemented."
op_seq = list(
chain(*map(
lambda o: parse_operation_sequence(
o, resol=resol, return_str=return_str, stack=stack),
op['operation_sequence'])))
assert all(
[
op_seq[i][3] == op_seq[i + 1][2]
for i in range(0,
len(op_seq) - 1)
]
), "In and out domains are not consistent along the composite operation chain. %s" % [
(o[2], o[3]) for o in op_seq
]
else: # single operation
op_arr = convert_operation_to_arr(op,
resol=resol,
inverse=inverse,
return_str=return_str,
stack=stack)
if inverse:
op_seq = [(op['type'], op_arr, op['dest_prep_id'],
op['base_prep_id'])]
else:
op_seq = [(op['type'], op_arr, op['base_prep_id'],
op['dest_prep_id'])]
#print op_seq
return op_seq
from utilities.data_manager_v2 import DataManager
from utilities.utilities2015 import load_ini, create_parent_dir_if_not_exists
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter,
description='Rescale image')
parser.add_argument("input_spec", type=str, help="Input image name")
parser.add_argument('out_resol', type=str, help='')
parser.add_argument("-f", "--rescale_factor", type=float, help="Rescale factor")
parser.add_argument("-W", "--width", type=int, help="Width")
parser.add_argument("-H", "--height", type=int, help="Height")
args = parser.parse_args()
input_spec = load_ini(args.input_spec)
stack = input_spec['stack']
prep_id = input_spec['prep_id']
if prep_id == 'None':
prep_id = None
resol = input_spec['resol']
version = input_spec['version']
if version == 'None':
version = None
image_name_list = input_spec['image_name_list']
if image_name_list == 'all':
image_name_list = DataManager.load_sorted_filenames(stack=stack)[0].keys()
from PIL import Image
parser.add_argument("--op", type=str, help="Op id of warp")
parser.add_argument("--prep_id", type=str, help="Prep ID of the warp")
parser.add_argument("--elastix_output_dir",
type=str,
help="Elastix-generated pairwise transform output dir")
parser.add_argument("--custom_output_dir",
type=str,
help="User-corrected pairwise transform output dir")
parser.add_argument("--anchor_img_name", type=str, help="Anchor image name")
parser.add_argument("--out",
type=str,
help="csv, composed transforms for each image to anchor")
args = parser.parse_args()
input_spec = load_ini(args.input_spec)
image_name_list = input_spec['image_name_list']
if image_name_list == 'all':
#image_name_list = DataManager.load_sorted_filenames(stack=stack)[0].keys()
image_name_list = map(
lambda x: x[0],
sorted(DataManager.load_sorted_filenames(
stack=input_spec['stack'])[0].items(),
key=lambda x: x[1]))
#op = load_ini(os.path.join(DATA_ROOTDIR, 'CSHL_data_processed', input_spec['stack'], 'operation_configs', args.op + '.ini'))
op = load_ini(
os.path.join(DATA_ROOTDIR, 'CSHL_data_processed', input_spec['stack'],
'operation_configs', args.op + '.ini'))
assert op['type'] == 'warp', "Op type must be warp."
assert op['base_prep_id'] == input_spec[
from utilities.data_manager_v2 import DataManager
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter,
description=
"""Align consecutive images. Possible bad alignment pairs are written into a separate file.
Usage 1: align_compose.py in.ini --op from_none_to_aligned
""")
parser.add_argument("input_spec", type=str, help="input specifier. ini")
parser.add_argument("--op", type=str, help="operation id")
args = parser.parse_args()
print('args', args)
input_spec = load_ini(args.input_spec)
stack = input_spec['stack']
sqlController = SqlController()
fileLocationManager = FileLocationManager(stack)
execute_command('python align_v3.py %s --op %s' % (args.input_spec, args.op))
# execute_command('python compose_v3.py %s --op %s' % (args.input_spec, args.op))
#image_name_list = input_spec['image_name_list']
image_name_list = sqlController.get_image_list(stack, 'destination')
#if image_name_list == 'all':
# #image_name_list = DataManager.load_sorted_filenames(stack=stack)[0].keys()
# image_name_list = map(lambda x: x[0], sorted(DataManager.load_sorted_filenames(stack=input_spec['stack'])[0].items(), key=lambda x: x[1]))
#op = load_ini(os.path.join(DATA_ROOTDIR, 'CSHL_data_processed', input_spec['stack'], 'operation_configs', args.op + '.ini'))
op = load_ini(
simple_global_bbox_fp = os.path.join(DATA_ROOTDIR, 'CSHL_simple_global_registration',
stack + '_registered_atlas_structures_wrt_wholebrainXYcropped_xysecTwoCorners.json')
# Try to load the XY cropping boxes for each structure, generated from Global Alignment
try:
registered_atlas_structures_wrt_wholebrainXYcropped_xysecTwoCorners = load_json( simple_global_bbox_fp )
print('Global Alignment files loaded!')
# Make cropping box cover the entire image if Global Alignment was not run
except:
print('Global Alignment files not found, not using a cropping box')
registered_atlas_structures_wrt_wholebrainXYcropped_xysecTwoCorners = {}
all_structures_total = structures_sided_sorted_by_size
op_path = os.path.join( DATA_ROOTDIR,'CSHL_data_processed',stack, 'operation_configs', 'from_padded_to_brainstem.ini')
op = load_ini(op_path)
img_x_len = 32*(op['caudal_limit'] - op['rostral_limit'])
img_y_len = 32*(op['ventral_limit'] - op['dorsal_limit'])
num_images = 1 + valid_secmax - valid_secmin
for structure in all_structures_total:
registered_atlas_structures_wrt_wholebrainXYcropped_xysecTwoCorners[structure] = [[0, 0, 0], [img_x_len, img_y_len, num_images]]
######## Identify ROI based on simple global alignment ########
print('\n\nIdentifying ROIs based on simple global alignment:')
print('____________________________________________________\n')
registered_atlas_structures_wrt_wholebrainXYcropped_bboxes_perSection = defaultdict(dict)
section_margin_um = 400.