try:
from sklearn.svm import SVC
from sklearn.linear_model import LogisticRegression, LinearRegression
from sklearn.ensemble import RandomForestClassifier
from sklearn.externals import joblib
except ImportError:
logging.warning("scikit-learn not found.")
sklearn_available = False
else:
sklearn_available = True
try:
from vigra.learning import RandomForest as BaseVigraRandomForest
from vigra.__version__ import version as vigra_version
vigra_version = tuple(map(int, vigra_version.split(".")))
except ImportError:
vigra_available = False
else:
vigra_available = True
# local imports
from . import iterprogress as ip
def h5py_stack(fn):
try:
a = np.array(h5py.File(fn, "r")["stack"])
except Exception as except_inst:
print(except_inst)
raise
try:
from sklearn.svm import SVC
from sklearn.linear_model import LogisticRegression, LinearRegression
from sklearn.ensemble import RandomForestClassifier
from sklearn.externals import joblib
except ImportError:
logging.warning('scikit-learn not found.')
sklearn_available = False
else:
sklearn_available = True
try:
from vigra.learning import RandomForest as BaseVigraRandomForest
from vigra.__version__ import version as vigra_version
vigra_version = tuple(map(int, vigra_version.split('.')))
except ImportError:
logging.warning('Vigra library not available.')
vigra_available = False
else:
vigra_available = True
# local imports
import iterprogress as ip
from .adaboost import AdaBoost
def h5py_stack(fn):
try:
a = np.array(h5py.File(fn, 'r')['stack'])
except Exception as except_inst:
try:
from sklearn.svm import SVC
from sklearn.linear_model import LogisticRegression, LinearRegression
from sklearn.ensemble import RandomForestClassifier
from sklearn.externals import joblib
except ImportError:
logging.warning('scikit-learn not found.')
sklearn_available = False
else:
sklearn_available = True
try:
from vigra.learning import RandomForest as BaseVigraRandomForest
from vigra.__version__ import version as vigra_version
vigra_version = tuple(map(int, vigra_version.split('.')))
except ImportError:
vigra_available = False
else:
vigra_available = True
# local imports
from . import iterprogress as ip
def h5py_stack(fn):
try:
a = np.array(h5py.File(fn, 'r')['stack'])
except Exception as except_inst:
print(except_inst)
raise