def main():
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
data3d_a_path = None # os.path.join(path_to_script, '../../../data/medical/data_orig/sliver07/training-part1/liver-orig001.mhd')
data3d_b_path = None #os.path.join(path_to_script, '../../../data/medical/data_orig/sliver07/training-part1/liver-seg001.mhd')
parser = argparse.ArgumentParser(
description='Information about pkl/pklz file')
parser.add_argument('pklzFile',
help='path to data' )
args = parser.parse_args()
data = misc.obj_from_file(args.pklzFile, 'pickle')
print(data)
try:
pyed = sed3.sed3(data['data3d'], contour=data['segmentation'])
pyed.show()
except:
try:
pyed = sed3.sed3(data['data3d'])
pyed.show()
except:
print("Problem with visualization")
def main():
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
# input parser
parser = argparse.ArgumentParser(
description='Module for segmentation of simple anatomical structures')
parser.add_argument('-i',
'--inputfile',
default='organ.pkl',
help='path to data dir')
args = parser.parse_args()
data = misc.obj_from_file(args.inputfile, filetype='pickle')
data3d = data['data3d']
voxelsize_mm = data['voxelsize_mm']
ss = SimpleSegmentation()
simple_seg = ss.simple_segmentation(data3d, voxelsize_mm)
#visualization
pyed = sed3.sed3(data['data3d'], seeds=simple_seg)
pyed.show()
# save
savestring = raw_input('Save output data? (y/n): ')
if savestring in ['Y', 'y']:
misc.obj_to_file(data, "resection.pkl", filetype='pickle')
def main():
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
# logger.debug('input params')
# input parser
parser = argparse.ArgumentParser(description='\
3D visualization of segmentation\n\
\npython show_segmentation.py\n\
\npython show_segmentation.py -i resection.pkl -l 2 3 4 -d 4')
parser.add_argument('-i',
'--inputfile',
default='organ.pkl',
help='input file')
parser.add_argument('-o',
'--outputfile',
default='~/lisa_data/mesh_geom.vtk',
help='output file')
parser.add_argument('-d',
'--degrad',
type=int,
default=4,
help='data degradation, default 4')
parser.add_argument(
'-r',
'--resize',
type=float,
default=None,
help='resize voxel to defined size in milimeters, default is None')
parser.add_argument('-l',
'--label',
type=int,
metavar='N',
nargs='+',
default=[1],
help='segmentation labels, default 1')
args = parser.parse_args()
# data = misc.obj_from_file(args.inputfile, filetype='pickle')
import io3d
data = io3d.read(args.inputfile, dataplus_format=True)
# args.label = np.array(eval(args.label))
# print args.label
# import pdb; pdb.set_trace()
ds = np.zeros(data['segmentation'].shape, np.bool)
for i in range(0, len(args.label)):
ds = ds | (data['segmentation'] == args.label[i])
outputfile = os.path.expanduser(args.outputfile)
showSegmentation(ds,
degrad=args.degrad,
voxelsize_mm=data['voxelsize_mm'],
vtk_file=outputfile,
resize_mm=args.resize)
def get_logger(name):
logger = logging.getLogger(name)
file_name = str(datetime.date.today()) + ".log"
logger.setLevel(logging.DEBUG)
# create console handler and set level to debug
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
# create formatter
formatter = logging.Formatter(
"[%(asctime)s] %(levelname)s %(filename)s %(lineno)s %(message)s"
)
# add formatter to ch
ch.setFormatter(formatter)
logger.addHandler(ch)
log_path = os.path.join(base_dir, name)
if not os.path.exists(log_path):
os.mkdir(log_path)
log_file_path = os.path.join(log_path, file_name)
handler = logging.handlers.RotatingFileHandler(log_file_path, maxBytes=1024 * 1024)
dir_list = [os.path.join(log_path, file) for file in os.listdir(log_path)]
for log in dir_list:
create_time = int(os.path.getctime(log))
if int(time.time()) - create_time >= 3600 * 24 * 3:
os.remove(log)
handler.setFormatter(formatter)
handler.setLevel(logging.ERROR)
logger.addHandler(handler)
return logger
def main():
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
update()
def create_logger(log_dir: str, logger_name: str):
# 创建一个logger
logger = logging.getLogger(logger_name)
logger.setLevel(logging.DEBUG)
if not os.path.exists(log_dir):
os.mkdir(log_dir)
# 创建一个handler，
timestamp = time.strftime("%Y.%m.%d_%H.%M.%S", time.localtime())
log_filename = f"{log_dir}/log_{logger_name}_{timestamp}.txt"
fh = logging.FileHandler(log_filename)
fh.setLevel(logging.DEBUG)
# 再创建一个handler，用于输出到控制台
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
# 定义handler的输出格式
formatter = logging.Formatter(
'[%(asctime)s][%(levelname)s] ## %(message)s')
fh.setFormatter(formatter)
ch.setFormatter(formatter)
# 给logger添加handler
logger.addHandler(fh)
logger.addHandler(ch)
return logger
def main():
# logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
logger.addHandler(ch)
# create file handler which logs even debug messages
# fh = logging.FileHandler('log.txt')
# fh.setLevel(logging.DEBUG)
# formatter = logging.Formatter(
# '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# fh.setFormatter(formatter)
# logger.addHandler(fh)
# logger.debug('start')
# input parser
parser = argparse.ArgumentParser(
description=__doc__
)
parser.add_argument(
'-i', '--inputfile',
default=None,
required=True,
help='input file'
)
parser.add_argument(
'-d', '--debug', action='store_true',
help='Debug mode')
args = parser.parse_args()
if args.debug:
ch.setLevel(logging.DEBUG)
def main():
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
data3d_a_path = None # os.path.join(path_to_script, '../../../data/medical/data_orig/sliver07/training-part1/liver-orig001.mhd')
data3d_b_path = None #os.path.join(path_to_script, '../../../data/medical/data_orig/sliver07/training-part1/liver-seg001.mhd')
parser = argparse.ArgumentParser(
description='Visualization of sliver data and our segmentation')
parser.add_argument(
'-dd',
'--densityData',
help='path to input data with density. It can be Dicom or pklz',
default=data3d_a_path)
parser.add_argument(
'-sa',
'--segmentationA',
help='path to input (sliver) segmentation Dicom or pklz',
default=data3d_b_path)
parser.add_argument(
'-sb',
'--segmentationB',
help='path to out pklz or pkl segmentation. Dicom is not supported.',
default=None)
args = parser.parse_args()
show(args.densityData, args.segmentationA, args.segmentationB)
def start_flask_server(daemonize=True, debug=True):
if Path(PID_PATH).exists():
pid = int(Path(PID_PATH).read_text())
if pid in psutil.pids():
clrc.info(
"It seems daemon is already running. Use restart command to restart it"
)
return
else:
clrc.warn(
"It seems daemon was not stopped correctly the last time. PID file exists, and PID inside it do not match any running process. Please remove PID file manually: {0}"
.format(PID_PATH))
clrc.info("After removing PID file daemon should start as usual")
return
if daemonize:
if debug:
clrc.info("Information:")
clrc.info("Database is at: {0}".format(DATABASE_PATH))
clrc.info("Daemon process PID file is at: {0}".format(PID_PATH))
if LOG_PATH:
clrc.info(
"You specified LOG_PATH. It's at: {0}".format(LOG_PATH))
if (_can_create_pid_file() and _can_create_logs()):
clrc.info("Starting daemon...")
clrc.info(
"Daemon started successfully. You can access your server at http://{0}:{1}"
.format(HOST, PORT))
clrc.info(
"If you are not able to access the web server and sure this is not a problem with firewall/closed port etc, please check logs here: {0}"
.format(LOG_PATH))
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
fh = logging.FileHandler(LOG_PATH)
logger.addHandler(fh)
# Fix to work with pyinstaller onefile
fds_to_myself = []
if getattr(sys, 'frozen', False):
fds_to_myself = [
of.fd for of in psutil.Process(os.getpid()).open_files()
if of.path == sys.executable
]
with daemon.DaemonContext(
pidfile=pidlockfile.PIDLockFile(PID_PATH),
stdout=fh.stream,
stderr=fh.stream,
files_preserve=[fh.stream] + fds_to_myself):
_run_flask_app()
clrc.success(
"Daemon started! You can access server at {0}:{1}".format(
HOST, PORT))
else:
_run_flask_app(debug=True)
def main():
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
# logger.debug('input params')
# input parser
parser = argparse.ArgumentParser(
description='Module for segmentation of simple anatomical structures')
parser.add_argument('-i',
'--inputfile',
default='vessels.pkl',
help='path to data dir')
# args = parser.parse_args()
# horsi kvalita segmentace
# datapath = os.path.join(path_to_script, "../vessels1.pkl")
# hypodenzni meta
# datapath = os.path.join(path_to_script, args.inputfile)
# horsi kvalita segmentace
# datapath = os.path.join(path_to_script, "../organ.pkl")
# data = misc.obj_from_file(args.inputfile, filetype = 'pickle')
dcmdir = '/home/tomas/Dropbox/Work/Data/medical/org-38289898-export1.pklz'
data = misc.obj_from_file(dcmdir, filetype='pickle')
# windowing
data['data3d'] = tools.windowing(data['data3d'], level=50, width=350)
# data['data3d'] = smoothing(data['data3d'], sliceId=0)
# smoothing ----------------
# bilateral
# data['data3d'] = tools.smoothing_bilateral(data['data3d'],
# sigma_space=15, sigma_color=0.05, sliceId=0)
# more bilateral
# data['data3d'] = tools.smoothing_bilateral(data['data3d'],
# sigma_space=15, sigma_color=0.1, sliceId=0)
# total-variation
data['data3d'] = tools.smoothing_tv(data['data3d'], weight=0.05, sliceId=0)
# more total-variation
# data['data3d'] = tools.smoothing_tv(data['data3d'], weight=0.2,
# multichannel=False, sliceId=0)
# sed3.sed3(data['data3d']).show()
tumory = Lesions()
# tumory.overlay_test()
tumory.import_data(data)
tumory.automatic_localization()
tumors = tumory.segmentation == tumory.data['slab']['lesions']
sed3.sed3(tumory.data3d, contour=tumors).show()
def setup_custom_logger(name):
formatter = logging.Formatter('%(asctime)s,%(msecs)d %(levelname)-8s [%(filename)s:%(lineno)d] %(message)s')
handler = logging.StreamHandler()
handler.setFormatter(formatter)
logger = logging.getLogger(name)
logger.setLevel(logging.DEBUG)
logger.addHandler(handler)
return logger
def main():
# logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
logger.addHandler(ch)
# create file handler which logs even debug messages
# fh = logging.FileHandler('log.txt')
# fh.setLevel(logging.DEBUG)
# formatter = logging.Formatter(
# '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# fh.setFormatter(formatter)
# logger.addHandler(fh)
# logger.debug('start')
# input parser
parser = argparse.ArgumentParser(
description=__doc__
)
# parser.add_argument(
# '-i', '--inputfile',
# default=None,
# required=True,
# help='input file'
# )
parser.add_argument(
'-o', '--outputfile',
default="~/lisa_data/liver_intensity.Model.p",
help='output file'
)
parser.add_argument(
'-fv', '--extern_fv',
default=None,
help='string describing extern feature vector function'
)
parser.add_argument(
'-d', '--debug', action='store_true',
help='Debug mode')
args = parser.parse_args()
modelparams={}
if args.debug:
ch.setLevel(logging.DEBUG)
if args.extern_fv is not None:
modelparams.update({
'fv_type': "fv_extern",
'fv_extern': args.extern_fv,
})
train_liver_model_from_sliver_data(args.outputfile, modelparams=modelparams)
def setup(logging_level="INFO", logger_file=None):
if logger_file is None:
logging.basicConfig(handlers=[InterceptHandler()], level=logging_level)
else:
logger = logging.getLogger()
logging_level = getattr(logging, logging_level)
logger.setLevel(logging_level)
handler = logging.FileHandler(logger_file, "w", encoding="UTF-8")
handler.setFormatter(logging.Formatter("%(asctime)s %(levelname)s %(threadName)s %(name)s %(message)s"))
logger.addHandler(handler)
def add_log_client(logger, client):
if ':' in client:
client, port = tuple(client.split(':', 1))
port = int(port)
else:
port = logging.handlers.DEFAULT_TCP_LOGGING_PORT
socket_handler = logging.handlers.SocketHandler(client, port)
socket_handler.setLevel(logging.INFO)
logger.addHandler(socket_handler)
return socket_handler
def main():
# logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
logger.addHandler(ch)
# create file handler which logs even debug messages
# fh = logging.FileHandler('log.txt')
# fh.setLevel(logging.DEBUG)
# formatter = logging.Formatter(
# '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# fh.setFormatter(formatter)
# logger.addHandler(fh)
# logger.debug('start')
# input parser
parser = argparse.ArgumentParser(
description=__doc__
)
parser.add_argument(
'-i', '--inputfile',
default=None,
required=True,
help='input file'
)
parser.add_argument(
'-d', '--debug', action='store_true',
help='Debug mode')
args = parser.parse_args()
if args.debug:
ch.setLevel(logging.DEBUG)
app = QApplication(sys.argv)
# form = LogViewerForm(args.inputfile, qapp=app)
# form.show()
list = QListView()
list.setWindowTitle('nazev okna')
list.setMinimumSize(600,400)
model = LogEntryModel(args.inputfile, parent=list)
list.setModel(model)
watcher = QFileSystemWatcher([args.inputfile], parent=None)
watcher.fileChanged['QString'].connect(model.slurp)
list.show()
app.exec_()
def main():
# # logger = logging.getLogger()
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
# logger.debug('input params')
default_data_file = os.path.join(path_to_script,
"20130812_liver_volumetry.yaml")
parser = argparse.ArgumentParser(
description='Compare two segmentation. Evaluation is similar\
to MICCAI 2007 workshop. Metrics are described in\
www.sliver07.com/p7.pdf')
parser.add_argument('-d', '--debug', action='store_true',
help='run in debug mode', default=False)
parser.add_argument('-si', '--sampleInput', action='store_true',
help='generate sample intput data', default=False)
parser.add_argument('-v', '--visualization', action='store_true',
help='Turn on visualization', default=False)
parser.add_argument('-y', '--inputYamlFile', help='input yaml file',
default=default_data_file)
parser.add_argument('-ds', '--directorySliver',
help='input SLiver directory. If this and\
directoryPklz is not None, yaml file is generated',
default=None)
parser.add_argument('-dp', '--directoryPklz', help='input pklz directory',
default=None)
parser.add_argument('-o', '--outputfile',
help='output file without extension',
default='20130812_liver_volumetry')
args = parser.parse_args()
if args.debug:
logger.setLevel(logging.DEBUG)
logger.debug('debug mode logging')
if args.sampleInput:
sample_input_data()
evaluate_and_write_to_file(
args.inputYamlFile,
args.directoryPklz,
args.directorySliver,
args.outputfile,
args.visualization
)
def main():
## logger = logging.getLogger()
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
parser = argparse.ArgumentParser(
description='Compute features on liver and other tissue.')
parser.add_argument('-si', '--sampleInput', action='store_true',
help='generate sample intput data', default=False)
parser.add_argument('-v', '--visualization', action='store_true',
help='Turn on visualization', default=False)
parser.add_argument('-i', '--input', help='input yaml file',
default="20130919_liver_statistics.yaml")
parser.add_argument('-o', '--output', help='output file',
default="20130919_liver_statistics_results.pkl")
parser.add_argument('-t', '--train', help='Training', default=False,
action='store_true'
)
args = parser.parse_args()
if args.sampleInput:
sample_input_data()
# input parser
#path_to_yaml = os.path.join(path_to_script, args.input)
path_to_yaml = args.input
#write_csv(fvall)
list_of_feature_fcn = [feat_hist]
from sklearn import svm
from sklearn.naive_bayes import GaussianNB
list_of_classifiers = [svm.SVC, GaussianNB]
tile_shape = [1, 100, 100]
featrs_plus_classifs = make_product_list(list_of_feature_fcn,
list_of_classifiers)
result = experiment(path_to_yaml, featrs_plus_classifs,
tile_shape=tile_shape,
visualization=args.visualization, train=args.train)
# Ukládání výsledku do souboru
output_file = os.path.join(path_to_script, args.output)
misc.obj_to_file(result, output_file, filetype='pickle')
def main():
# logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
logger.addHandler(ch)
# create file handler which logs even debug messages
# fh = logging.FileHandler('log.txt')
# fh.setLevel(logging.DEBUG)
# formatter = logging.Formatter(
# '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# fh.setFormatter(formatter)
# logger.addHandler(fh)
# logger.debug('start')
# input parser
parser = argparse.ArgumentParser(description=__doc__)
# parser.add_argument(
# '-i', '--inputfile',
# default=None,
# required=True,
# help='input file'
# )
parser.add_argument(
'--dict',
default="{'jatra':2, 'ledviny':7}",
# required=True,
help='input dict')
parser.add_argument('-d',
'--debug',
action='store_true',
help='Debug mode')
args = parser.parse_args()
if args.debug:
ch.setLevel(logging.DEBUG)
app = QtWidgets.QApplication(sys.argv)
# w = QtGui.QWidget()
# w = DictEdit(dictionary={'jatra':2, 'ledviny':7})
w = DictEdit(dictionary=eval(args.dict))
w.resize(250, 150)
w.move(300, 300)
w.setWindowTitle('Simple')
w.show()
sys.exit(app.exec_())
def main():
# logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
logger.addHandler(ch)
# create file handler which logs even debug messages
# fh = logging.FileHandler('log.txt')
# fh.setLevel(logging.DEBUG)
# formatter = logging.Formatter(
# '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# fh.setFormatter(formatter)
# logger.addHandler(fh)
# logger.debug('start')
# input parser
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
'-i',
'--inputfile',
default=None,
# required=True,
help='input file')
parser.add_argument('-d',
'--debug',
action='store_true',
help='Debug mode')
parser.add_argument('-lm',
'--liver-model',
action='store_true',
help='Train liver model')
parser.add_argument('-ll',
'--liver-localizator',
action='store_true',
help='Train liver localizator')
parser.add_argument('--all', action='store_true', help='Train all')
args = parser.parse_args()
if args.debug:
ch.setLevel(logging.DEBUG)
if args.liver_localizator or args.all:
organ_localizator.train_liver_localizator_from_sliver_data()
if args.liver_model or args.all:
organ_model.train_liver_model_from_sliver_data()
def __new__(cls, *args, **kwargs):
print(args)
filename, fmt, level = args
logger = logging.getLogger(__name__)
format_str = logging.Formatter(fmt) # 设置日志格式
logger.setLevel(level) # 设置日志级别
sh = logging.StreamHandler() # 往屏幕上输出
sh.setFormatter(format_str) # 设置屏幕上显示的格式
th = handlers.TimedRotatingFileHandler(
filename=filename,
when="D",
backupCount=3,
encoding='utf-8'
) # 往文件里写入#指定间隔时间自动生成文件的处理器
th.setFormatter(format_str) # 设置文件里写入的格式
logger.addHandler(sh) # 把对象加到logger里
logger.addHandler(th)
return logger
def main():
# logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
logger.addHandler(ch)
# create file handler which logs even debug messages
# fh = logging.FileHandler('log.txt')
# fh.setLevel(logging.DEBUG)
# formatter = logging.Formatter(
# '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# fh.setFormatter(formatter)
# logger.addHandler(fh)
# logger.debug('start')
# input parser
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
'-i',
'--inputfile',
default=None,
# required=True,
help='input file')
parser.add_argument('-d',
'--debug',
action='store_true',
help='Debug mode')
args = parser.parse_args()
if args.debug:
ch.setLevel(logging.DEBUG)
import sys
app = QtWidgets.QApplication(sys.argv)
login = Login()
if login.exec_() == QtWidgets.QDialog.Accepted:
window = Window()
window.show()
sys.exit(app.exec_())
def setup_logger(name=None, level=None):
"""
Returns a logger formatted as specified in the SuRVoS config file.
"""
from .config import Config
logger = logging.getLogger(name)
logger.handlers = []
level = level or Config["logging.level"].upper() or logging.ERROR
if Config["logging.std"]:
handler = logging.StreamHandler()
handler.setLevel(level)
fmt = logging.Formatter(Config["logging.std_format"])
handler.setFormatter(fmt)
logger.addHandler(handler)
if Config["logging.file"]:
handler = logging.FileHandler(Config["logging.file"])
handler.setLevel(level)
fmt = logging.Formatter(Config["logging.file_format"])
handler.setFormatter(fmt)
logger.addHandler(handler)
return logger
def main():
## logger = logging.getLogger()
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
## read confguraton from file, use default values from OrganSegmentation
# input parser
parser = argparse.ArgumentParser(
description=' Show dicom data with overlay')
parser.add_argument('-i', '--inputdatapath',
default='',
help='path to data dir')
args_obj = parser.parse_args()
args = vars(args_obj)
#print args["arg"]
reader = datareader.DataReader()
data3d, metadata = reader.Get3DData(args['inputdatapath'], qt_app=None, dataplus_format=False)
overlays = reader.get_overlay()
overlay = np.zeros(data3d.shape, dtype=np.int8)
print("overlays ", list(overlays.keys()))
for key in overlays:
overlay += overlays[key]
#import ipdb; ipdb.set_trace() # BREAKPOINT
pyed = sed3.sed3(data3d, contour=overlay)
pyed.show()
#print savestring
# import pdb; pdb.set_trace()
return
def main():
# logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
logger.addHandler(ch)
# create file handler which logs even debug messages
# fh = logging.FileHandler('log.txt')
# fh.setLevel(logging.DEBUG)
# formatter = logging.Formatter(
# '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# fh.setFormatter(formatter)
# logger.addHandler(fh)
# logger.debug('start')
# input parser
parser = argparse.ArgumentParser(description=__doc__)
# parser.add_argument(
# '-i', '--inputfile',
# default=None,
# required=True,
# help='input file'
# )
parser.add_argument('-o',
'--outputfile',
default="~/lisa_data/liver.ol.p",
help='output file')
parser.add_argument('-d',
'--debug',
action='store_true',
help='Debug mode')
args = parser.parse_args()
if args.debug:
ch.setLevel(logging.DEBUG)
train_liver_localizator_from_sliver_data(args.outputfile)
def main():
# # logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
# input parser
parser = argparse.ArgumentParser(
description=
'Segment vessels from liver \n \npython organ_segmentation.py\n \n\
python organ_segmentation.py -mroi -vs 0.6')
parser.add_argument('-d',
'--get_sample_data',
action='store_true',
default=False,
help='Get sample data')
parser.add_argument('-i',
'--install',
action='store_true',
default=False,
help='Install')
parser.add_argument('-icn',
'--make_icon',
action='store_true',
default=False,
help='Creates desktop icon, works only in ubuntu')
parser.add_argument('-g',
'--get_git',
action='store_true',
default=False,
help='Get git in windows')
parser.add_argument('--build_gco',
action='store_true',
default=False,
help='Build gco_python in windows. Problematic step.')
args = parser.parse_args()
# if args.get_sample_data == False and args.install == False and args.build_gco == False:
## default setup is install and get sample data
# args.get_sample_data = True
# args.install = True
# args.build_gco = False
if args.get_sample_data:
import lisa
import lisa.dataset
lisa.dataset.get_sample_data()
# get_sample_data()
if args.make_icon:
make_icon()
if args.install:
print('Installing system environment')
if sys.platform.startswith('linux'):
subprocess.call('./envinstall/envubuntu.sh')
#submodule_update()
elif sys.platform.startswith('win'):
windows_install()
if args.build_gco:
windows_build_gco()
else:
windows_get_gco()
if args.get_git:
windows_get_git()
def main():
## logger = logging.getLogger()
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
# input parser
parser = argparse.ArgumentParser(description=
'Segmentation of bones, lungs and heart.')
parser.add_argument('-i','--datadir',
default=None,
help='path to data dir')
parser.add_argument('-o','--output',
default=None,
help='output file')
parser.add_argument('-d', '--debug', action='store_true',
help='run in debug mode')
parser.add_argument('-ss', '--segspine', action='store_true',
help='run spine segmentaiton')
parser.add_argument('-sb', '--segbody', action='store_true',
help='run body segmentaiton')
parser.add_argument('-exd', '--exampledata', action='store_true',
help='run unittest')
parser.add_argument('-so', '--show_output', action='store_true',
help='Show output data in viewer')
args = parser.parse_args()
if args.debug:
logger.setLevel(logging.DEBUG)
if args.exampledata:
args.dcmdir = '../sample_data/liver-orig001.raw'
# if dcmdir == None:
#else:
#dcm_read_from_dir('/home/mjirik/data/medical/data_orig/46328096/')
#data3d, metadata = dcmr.dcm_read_from_dir(args.dcmdir)
import io3d
data3d , metadata = io3d.datareader.read(args.datadir, dataplus_format=False)
bn = BodyNavigation(data3d = data3d,
voxelsize_mm = metadata['voxelsize_mm'],
)
seg = np.zeros(data3d.shape, dtype=np.int8)
#sseg.orientation()
if args.segspine:
seg += bn.get_spine()
if args.segspine:
seg += bn.get_body()
#print("Data size: " + str(data3d.nbytes) + ', shape: ' + str(data3d.shape) )
#igc = pycut.ImageGraphCut(data3d, zoom = 0.5)
#igc.interactivity()
#igc.make_gc()
#igc.show_segmentation()
# volume
#volume_mm3 = np.sum(oseg.segmentation > 0) * np.prod(oseg.voxelsize_mm)
#pyed = sed3.sed3(oseg.data3d, contour = oseg.segmentation)
#pyed.show()
if args.show_output:
import sed3
sed3.show_slices(data3d, contour=seg)
#savestring = raw_input ('Save output data? (y/n): ')
#sn = int(snstring)
if args.output is not None: # savestring in ['Y','y']:
md = {
'voxelsize_mm': metadata['voxelsize_mm'],
'segmentation': seg, }
io3d.write(data3d, args.output, metadata=md)
def main():
# # logger = logging.getLogger()
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
# logger.debug('input params')
parser = argparse.ArgumentParser(
description='Compute features on liver and other tissue.')
parser.add_argument('-tr',
'--training_yaml_path',
help='Input yaml file.' +
" You can check sample with -si parameter.",
default="20130919_liver_statistics.yaml")
parser.add_argument('-te',
'--testing_yaml_path',
help='Input yaml file.' +
" You can check sample with -si parameter.",
default=None)
parser.add_argument('-si',
'--sampleInput',
action='store_true',
help='generate sample intput data',
default=False)
parser.add_argument('-v',
'--visualization',
action='store_true',
help='Turn on visualization',
default=False)
parser.add_argument('-fc',
'--features_classifs',
action='store_true',
help='Read features and classifs list from file',
default=False)
parser.add_argument('-o',
'--output',
help='output file',
default="20130919_liver_statistics_results.pkl")
parser.add_argument('-t',
'--train',
help='Training',
default=False,
action='store_true')
parser.add_argument(
'-cl',
'--classifers',
help='classifer by string: "SVC", or "GaussianNB", ...',
nargs='+',
type=str,
default=['SVC'])
parser.add_argument('-fe',
'--features',
help='features by string: "hist", or "glcm", ...',
nargs='+',
type=str,
default=['hist'])
args = parser.parse_args()
if args.sampleInput:
sample_input_data()
# input parser
# path_to_yaml = os.path.join(path_to_script, args.input)
# training_yaml_path = args.training_yaml_path
# testing_yaml_path = args.testing_yaml_path
if args.testing_yaml_path is None:
print('testing is same as training')
args.testing_yaml_path = args.training_yaml_path
# write_csv(fvall)
gf = tfeat.GaborFeatures() # noqa
glcmf = tfeat.GlcmFeatures() # noqa
haralick = tfeat.HaralickFeatures() # noqa
list_of_feature_fcn = prepared_texture_features_by_string(args.features)
list_of_classifiers = prepared_classifiers_by_string(args.classifers)
tile_shape = [10, 50, 50]
if args.features_classifs:
import features_classifs
featrs_plus_classifs = features_classifs.fc
else:
featrs_plus_classifs = make_product_list(list_of_feature_fcn,
list_of_classifiers)
result = experiment(args.training_yaml_path,
args.testing_yaml_path,
featrs_plus_classifs,
tile_shape=tile_shape,
use_voxelsize_norm=True,
working_voxelsize_mm=[1, 1, 1],
visualization=args.visualization,
train=args.train)
# Ukládání výsledku do souboru
output_file = os.path.join(path_to_script, args.output)
misc.obj_to_file(result, output_file, filetype='pickle')
def main():
## logger = logging.getLogger()
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
# input parser
params = {'datadir': None, 'working_voxelsize_mm': 3}
dirpath = os.path.join(path_to_script,
"../../../data/medical/data_orig/volumetrie")
experiment_results = {'params': params, 'dirpath': dirpath, 'volume_l': {}}
output_dirpath = os.path.join(path_to_script, '../../../data/medical')
dirlist = experiments.get_subdirs(dirpath)
for key in dirlist:
print(key)
# import pdb; pdb.set_trace()
try:
dirname = dirlist[key]['abspath']
params['datadir'] = dirname
oseg = organ_segmentation.OrganSegmentation(**params)
oseg.interactivity()
print("Volume " +
str(oseg.get_segmented_volume_size_mm3() / 1000000.0) +
' [l]')
volume_l = (oseg.get_segmented_volume_size_mm3() / 1000000.0)
experiment_results['volume_l'][key] = volume_l
head, teil = os.path.split(dirname)
filename_organ = os.path.join(output_dirpath, teil)
data = oseg.export()
misc.obj_to_file(data,
filename_organ + "-organ.pkl",
filetype='pickle')
#misc.obj_to_file(data, "organ.pkl", filetype='pickle')
misc.obj_to_file(oseg.get_iparams(),
filename_organ + '-iparams.pkl',
filetype='pickle')
misc.obj_to_file(experiment_results,
filename_organ + "-info.yaml",
filetype='yaml')
except:
print('Selhani, pokracujeme dal')
print(traceback.format_exc())
import pdb
pdb.set_trace()
misc.obj_to_file(experiment_results, "results.yaml", filetype='yaml')
if lb != 0:
new_slabel = new_label_str_format.format(vessel_label, lb)
new_nlabel = oseg.nlabels(new_slabel)
oseg.segmentation[bl == lb] = new_nlabel
# ima.distance_segmentation(oseg.select_label(vessel_label))
return bl
if __name__ == "__main__":
# # logger = logging.getLogger()
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
# SectorDisplay2__()
# logger.debug('input params')
# input parser
parser = argparse.ArgumentParser(description='Segment vessels from liver')
parser.add_argument('-pkl', '--picklefile',
help='input file from organ_segmentation')
parser.add_argument('-oe', '--use_old_editor', action='store_true',
help='use an old editor for vessel cut')
parser.add_argument('-o', '--outputfile', default=None,
help='output file')
parser.add_argument('-oo', '--defaultoutputfile', action='store_true',
help='"vessels.pickle" as output file')
parser.add_argument('-d', '--debug', action='store_true',
help='Debug mode')
def main():
## logger = logging.getLogger()
# logger = logging.getLogger()
logger.setLevel(logging.WARNING)
ch = logging.StreamHandler()
logger.addHandler(ch)
#logger.debug('input params')
# input parser
parser = argparse.ArgumentParser(
description='Segment vessels from liver \n\
\npython organ_segmentation.py\n\
\npython organ_segmentation.py -mroi -vs 0.6')
parser.add_argument('-dd', '--dcmdir',
default=None,
help='path to data dir')
parser.add_argument('-d', '--debug', action='store_true',
help='run in debug mode')
parser.add_argument('-vs', '--voxelsize_mm', default='3', type=str,
help='Insert working voxelsize. It can be number or \
array of three numbers. \n \
-vs 3 \n \
-vs [3,3,5]')
parser.add_argument('-mroi', '--manualroi', action='store_true',
help='manual crop before data processing')
parser.add_argument('-iparams', '--iparams',
default=None,
help='filename of ipars file with stored interactivity')
parser.add_argument('-t', '--tests', action='store_true',
help='run unittest')
parser.add_argument('-tx', '--textureanalysis', action='store_true',
help='run with texture analysis')
parser.add_argument('-exd', '--exampledata', action='store_true',
help='run unittest')
parser.add_argument('-ed', '--editdata', action='store_true',
help='Run data editor')
parser.add_argument('-so', '--show_output', action='store_true',
help='Show output data in viewer')
parser.add_argument(
'-ss',
'--segmentation_smoothing',
action='store_true',
help='Smoothing of output segmentation',
default=False
)
args = parser.parse_args()
# voxelsize_mm can be number or array
args.voxelsize_mm = np.array(eval(args.voxelsize_mm))
if args.debug:
logger.setLevel(logging.DEBUG)
if args.tests:
# hack for use argparse and unittest in one module
sys.argv[1:] = []
unittest.main()
sys.exit()
if args.exampledata:
args.dcmdir = '../sample_data/\
matlab/examples/sample_data/DICOM/digest_article/'
if args.iparams is not None:
args.iparams = misc.obj_from_file(args.iparams)
#else:
#dcm_read_from_dir('/home/mjirik/data/medical/data_orig/46328096/')
#data3d, metadata = dcmreaddata.dcm_read_from_dir()
oseg = OrganSegmentation(args.dcmdir,
working_voxelsize_mm=args.voxelsize_mm,
manualroi=args.manualroi,
texture_analysis=args.textureanalysis,
edit_data=args.editdata,
smoothing=args.action_segmentation_smoothing,
iparams=args.iparams
)
oseg.interactivity()
#igc = pycut.ImageGraphCut(data3d, zoom = 0.5)
#igc.interactivity()
#igc.make_gc()
#igc.show_segmentation()
# volume
#volume_mm3 = np.sum(oseg.segmentation > 0) * np.prod(oseg.voxelsize_mm)
print(
"Volume " +
str(oseg.get_segmented_volume_size_mm3() / 1000000.0) + ' [l]')
#pyed = sed3.sed3(oseg.data3d, contour =
# oseg.segmentation)
#pyed.show()
if args.show_output:
oseg.show_output()
savestring = raw_input('Save output data? (y/n): ')
#sn = int(snstring)
if savestring in ['Y', 'y']:
data = oseg.export()
misc.obj_to_file(data, "organ.pkl", filetype='pickle')
misc.obj_to_file(oseg.get_ipars(), 'ipars.pkl', filetype='pickle')
#output = segmentation.vesselSegmentation(oseg.data3d,
# oseg.orig_segmentation)
def checkSegData(self):
if self.segmentation_data is None:
self.statusBar().showMessage('No SEG data!')
return
nzs = self.segmentation_data.nonzero()
nn = nzs[0].shape[0]
if nn > 0:
aux = ' voxels = %d, volume = %.2e mm3' % (nn, nn * self.voxel_volume)
self.setLabelText(self.text_seg_data, aux)
self.setLabelText(self.text_mesh_in, 'segmentation data')
self.statusBar().showMessage('Ready')
else:
self.statusBar().showMessage('Zero SEG data!')
def autoSeg(self):
if self.dcm_3Ddata is None:
self.statusBar().showMessage('No DICOM data!')
return
igc = pycut.ImageGraphCut(self.dcm_3Ddata,
voxelsize=self.voxel_size_mm)
pyed = QTSeedEditor(self.dcm_3Ddata,
seeds=self.segmentation_seeds,
modeFun=igc.interactivity_loop,
voxelVolume=self.voxel_volume)
pyed.exec_()
self.segmentation_data = pyed.getContours()
self.segmentation_seeds = pyed.getSeeds()
self.checkSegData()
