mediapipe/mediapipe/tasks/python/components/processors/classifier_options.py
2022-10-25 17:26:32 -07:00

87 lines
3.3 KiB
Python

# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Classifier options data class."""
import dataclasses
from typing import Any, List, Optional
from mediapipe.tasks.cc.components.processors.proto import classifier_options_pb2
from mediapipe.tasks.python.core.optional_dependencies import doc_controls
_ClassifierOptionsProto = classifier_options_pb2.ClassifierOptions
@dataclasses.dataclass
class ClassifierOptions:
"""Options for classification processor.
Attributes:
display_names_locale: The locale to use for display names specified through
the TFLite Model Metadata.
max_results: The maximum number of top-scored classification results to
return.
score_threshold: Overrides the ones provided in the model metadata. Results
below this value are rejected.
category_allowlist: Allowlist of category names. If non-empty, detection
results whose category name is not in this set will be filtered out.
Duplicate or unknown category names are ignored. Mutually exclusive with
`category_denylist`.
category_denylist: Denylist of category names. If non-empty, detection
results whose category name is in this set will be filtered out. Duplicate
or unknown category names are ignored. Mutually exclusive with
`category_allowlist`.
"""
display_names_locale: Optional[str] = None
max_results: Optional[int] = None
score_threshold: Optional[float] = None
category_allowlist: Optional[List[str]] = None
category_denylist: Optional[List[str]] = None
@doc_controls.do_not_generate_docs
def to_pb2(self) -> _ClassifierOptionsProto:
"""Generates a ClassifierOptions protobuf object."""
return _ClassifierOptionsProto(
score_threshold=self.score_threshold,
category_allowlist=self.category_allowlist,
category_denylist=self.category_denylist,
display_names_locale=self.display_names_locale,
max_results=self.max_results)
@classmethod
@doc_controls.do_not_generate_docs
def create_from_pb2(cls,
pb2_obj: _ClassifierOptionsProto) -> 'ClassifierOptions':
"""Creates a `ClassifierOptions` object from the given protobuf object."""
return ClassifierOptions(
score_threshold=pb2_obj.score_threshold,
category_allowlist=[str(name) for name in pb2_obj.category_allowlist],
category_denylist=[str(name) for name in pb2_obj.category_denylist],
display_names_locale=pb2_obj.display_names_locale,
max_results=pb2_obj.max_results)
def __eq__(self, other: Any) -> bool:
"""Checks if this object is equal to the given object.
Args:
other: The object to be compared with.
Returns:
True if the objects are equal.
"""
if not isinstance(other, ClassifierOptions):
return False
return self.to_pb2().__eq__(other.to_pb2())