import six
import collections
import bob.bio.base
import bob.bio.face
from . import Base, normalize_annotations
class Wrapper(Base):
"""Annotates video files using the provided image annotator.
See the documentation of :any:`Base` too.
Parameters
----------
annotator : :any:`bob.bio.base.annotator.Annotator` or str
The image annotator to be used. The annotator could also be the name of a
bob.bio.annotator resource which will be loaded.
max_age : int
see :any:`normalize_annotations`.
normalize : bool
If True, it will normalize annotations using :any:`normalize_annotations`
validator : object
See :any:`normalize_annotations` and
:any:`bob.bio.face.annotator.min_face_size_validator` for one example.
Please see :any:`Base` for more accepted parameters.
.. warning::
You should only set ``normalize`` to True only if you are annotating
**all** frames of the video file.
"""
def __init__(self,
annotator,
normalize=False,
validator=bob.bio.face.annotator.min_face_size_validator,
max_age=-1,
**kwargs
):
super(Wrapper, self).__init__(**kwargs)
self.annotator = annotator
self.normalize = normalize
self.validator = validator
self.max_age = max_age
# load annotator configuration
if isinstance(annotator, six.string_types):
self.annotator = bob.bio.base.load_resource(annotator, "annotator")
[docs] def annotate(self, frames, **kwargs):
"""See :any:`Base.annotate`
"""
annotations = collections.OrderedDict()
for i, frame in self.frame_ids_and_frames(frames):
annotations[i] = self.annotator(frame, **kwargs)
if self.normalize:
annotations = collections.OrderedDict(normalize_annotations(
annotations, self.validator, self.max_age))
return annotations