def __init__(self, min_size=(100, 100), max_size=None):
storage = lib.cvCreateMemStorage(0)
assert storage is not None
self._storage = storage
if min_size is None:
min_width = min_height = 0
else:
min_width, min_height = min_size
if max_size is None:
max_width = max_height = 0
else:
max_width, max_height = max_size
self._min_size = lib.cvSize(min_width, min_height)
self._max_size = lib.cvSize(max_width, max_height)
def __init__(self, min_size=(100, 100), max_size=None):
storage = lib.cvCreateMemStorage(0)
assert storage is not None
self._storage = storage
if min_size is None:
min_width = min_height = 0
else:
min_width, min_height = min_size
if max_size is None:
max_width = max_height = 0
else:
max_width, max_height = max_size
self._min_size = lib.cvSize(min_width, min_height)
self._max_size = lib.cvSize(max_width, max_height)
def from_path(cls, path, **kwargs):
cascade = lib.cvLoadHaarClassifierCascade(
path.path,
lib.cvSize(1, 1),
)
if cascade == ffi.NULL:
raise _CannotLoadClassifierCascade(path, cascade)
return cls(cascade=cascade, **kwargs)
def from_path(cls, path, **kwargs):
cascade = lib.cvLoadHaarClassifierCascade(
path.path,
lib.cvSize(1, 1),
)
if cascade == ffi.NULL:
raise _CannotLoadClassifierCascade(path, cascade)
return cls(cascade=cascade, **kwargs)