107 lines
4.0 KiB
Python
107 lines
4.0 KiB
Python
# Copyright 2022 The MediaPipe Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Landmarks Detection Result data class."""
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import dataclasses
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from typing import Optional, List
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from mediapipe.framework.formats import classification_pb2
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from mediapipe.framework.formats import landmark_pb2
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from mediapipe.tasks.cc.components.containers.proto import landmarks_detection_result_pb2
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from mediapipe.tasks.python.components.containers import category as category_module
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from mediapipe.tasks.python.components.containers import landmark as landmark_module
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from mediapipe.tasks.python.components.containers import rect as rect_module
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from mediapipe.tasks.python.core.optional_dependencies import doc_controls
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_LandmarksDetectionResultProto = landmarks_detection_result_pb2.LandmarksDetectionResult
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_ClassificationProto = classification_pb2.Classification
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_ClassificationListProto = classification_pb2.ClassificationList
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_LandmarkListProto = landmark_pb2.LandmarkList
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_NormalizedLandmarkListProto = landmark_pb2.NormalizedLandmarkList
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_NormalizedRect = rect_module.NormalizedRect
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_Category = category_module.Category
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_NormalizedLandmark = landmark_module.NormalizedLandmark
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_Landmark = landmark_module.Landmark
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@dataclasses.dataclass
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class LandmarksDetectionResult:
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"""Represents the landmarks detection result.
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Attributes:
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landmarks: A list of `NormalizedLandmark` objects.
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categories: A list of `Category` objects.
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world_landmarks: A list of `Landmark` objects.
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rect: A `NormalizedRect` object.
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"""
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landmarks: Optional[List[_NormalizedLandmark]]
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categories: Optional[List[_Category]]
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world_landmarks: Optional[List[_Landmark]]
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rect: _NormalizedRect
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@doc_controls.do_not_generate_docs
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def to_pb2(self) -> _LandmarksDetectionResultProto:
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"""Generates a LandmarksDetectionResult protobuf object."""
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landmarks = _NormalizedLandmarkListProto()
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classifications = _ClassificationListProto()
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world_landmarks = _LandmarkListProto()
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for landmark in self.landmarks:
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landmarks.landmark.append(landmark.to_pb2())
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for category in self.categories:
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classifications.classification.append(
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_ClassificationProto(
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index=category.index,
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score=category.score,
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label=category.category_name,
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display_name=category.display_name))
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return _LandmarksDetectionResultProto(
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landmarks=landmarks,
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classifications=classifications,
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world_landmarks=world_landmarks,
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rect=self.rect.to_pb2())
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@classmethod
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@doc_controls.do_not_generate_docs
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def create_from_pb2(
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cls,
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pb2_obj: _LandmarksDetectionResultProto) -> 'LandmarksDetectionResult':
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"""Creates a `LandmarksDetectionResult` object from the given protobuf object."""
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categories = []
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landmarks = []
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world_landmarks = []
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for classification in pb2_obj.classifications.classification:
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categories.append(
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category_module.Category(
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score=classification.score,
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index=classification.index,
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category_name=classification.label,
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display_name=classification.display_name))
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for landmark in pb2_obj.landmarks.landmark:
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landmarks.append(_NormalizedLandmark.create_from_pb2(landmark))
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for landmark in pb2_obj.world_landmarks.landmark:
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world_landmarks.append(_Landmark.create_from_pb2(landmark))
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return LandmarksDetectionResult(
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landmarks=landmarks,
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categories=categories,
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world_landmarks=world_landmarks,
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rect=_NormalizedRect.create_from_pb2(pb2_obj.rect))
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