# Path: google/cloud/datalabeling_v1beta1/types/annotation.py
# class AnnotationSource(proto.Enum):
# class AnnotationSentiment(proto.Enum):
# class AnnotationType(proto.Enum):
# class Annotation(proto.Message):
# class AnnotationValue(proto.Message):
# class ImageClassificationAnnotation(proto.Message):
# class Vertex(proto.Message):
# class NormalizedVertex(proto.Message):
# class BoundingPoly(proto.Message):
# class NormalizedBoundingPoly(proto.Message):
# class ImageBoundingPolyAnnotation(proto.Message):
# class Polyline(proto.Message):
# class NormalizedPolyline(proto.Message):
# class ImagePolylineAnnotation(proto.Message):
# class ImageSegmentationAnnotation(proto.Message):
# class TextClassificationAnnotation(proto.Message):
# class TextEntityExtractionAnnotation(proto.Message):
# class SequentialSegment(proto.Message):
# class TimeSegment(proto.Message):
# class VideoClassificationAnnotation(proto.Message):
# class ObjectTrackingFrame(proto.Message):
# class VideoObjectTrackingAnnotation(proto.Message):
# class VideoEventAnnotation(proto.Message):
# class AnnotationMetadata(proto.Message):
# class OperatorMetadata(proto.Message):
#     ANNOTATION_SOURCE_UNSPECIFIED = 0
#     OPERATOR = 3
#     ANNOTATION_SENTIMENT_UNSPECIFIED = 0
#     NEGATIVE = 1
#     POSITIVE = 2
#     ANNOTATION_TYPE_UNSPECIFIED = 0
#     IMAGE_CLASSIFICATION_ANNOTATION = 1
#     IMAGE_BOUNDING_BOX_ANNOTATION = 2
#     IMAGE_ORIENTED_BOUNDING_BOX_ANNOTATION = 13
#     IMAGE_BOUNDING_POLY_ANNOTATION = 10
#     IMAGE_POLYLINE_ANNOTATION = 11
#     IMAGE_SEGMENTATION_ANNOTATION = 12
#     VIDEO_SHOTS_CLASSIFICATION_ANNOTATION = 3
#     VIDEO_OBJECT_TRACKING_ANNOTATION = 4
#     VIDEO_OBJECT_DETECTION_ANNOTATION = 5
#     VIDEO_EVENT_ANNOTATION = 6
#     TEXT_CLASSIFICATION_ANNOTATION = 8
#     TEXT_ENTITY_EXTRACTION_ANNOTATION = 9
#     GENERAL_CLASSIFICATION_ANNOTATION = 14
# 
# Path: google/cloud/datalabeling_v1beta1/types/annotation_spec_set.py
# class AnnotationSpecSet(proto.Message):
# class AnnotationSpec(proto.Message):


import proto  # type: ignore
from google.cloud.datalabeling_v1beta1.types import annotation
from google.cloud.datalabeling_v1beta1.types import annotation_spec_set
from google.protobuf import timestamp_pb2  # type: ignore
        "PrCurve",
        "ConfusionMatrix",
    },
)


class Evaluation(proto.Message):
    r"""Describes an evaluation between a machine learning model's
    predictions and ground truth labels. Created when an
    [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob]
    runs successfully.

    Attributes:
        name (str):
            Output only. Resource name of an evaluation. The name has
            the following format:

            "projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}'
        config (google.cloud.datalabeling_v1beta1.types.EvaluationConfig):
            Output only. Options used in the evaluation
            job that created this evaluation.
        evaluation_job_run_time (google.protobuf.timestamp_pb2.Timestamp):
            Output only. Timestamp for when the
            evaluation job that created this evaluation ran.
        create_time (google.protobuf.timestamp_pb2.Timestamp):
            Output only. Timestamp for when this
            evaluation was created.
        evaluation_metrics (google.cloud.datalabeling_v1beta1.types.EvaluationMetrics):
            Output only. Metrics comparing predictions to
            ground truth labels.

# Path: google/cloud/datalabeling_v1beta1/types/annotation.py
# class AnnotationSource(proto.Enum):
# class AnnotationSentiment(proto.Enum):
# class AnnotationType(proto.Enum):
# class Annotation(proto.Message):
# class AnnotationValue(proto.Message):
# class ImageClassificationAnnotation(proto.Message):
# class Vertex(proto.Message):
# class NormalizedVertex(proto.Message):
# class BoundingPoly(proto.Message):
# class NormalizedBoundingPoly(proto.Message):
# class ImageBoundingPolyAnnotation(proto.Message):
# class Polyline(proto.Message):
# class NormalizedPolyline(proto.Message):
# class ImagePolylineAnnotation(proto.Message):
# class ImageSegmentationAnnotation(proto.Message):
# class TextClassificationAnnotation(proto.Message):
# class TextEntityExtractionAnnotation(proto.Message):
# class SequentialSegment(proto.Message):
# class TimeSegment(proto.Message):
# class VideoClassificationAnnotation(proto.Message):
# class ObjectTrackingFrame(proto.Message):
# class VideoObjectTrackingAnnotation(proto.Message):
# class VideoEventAnnotation(proto.Message):
# class AnnotationMetadata(proto.Message):
# class OperatorMetadata(proto.Message):
#     ANNOTATION_SOURCE_UNSPECIFIED = 0
#     OPERATOR = 3
#     ANNOTATION_SENTIMENT_UNSPECIFIED = 0
#     NEGATIVE = 1
#     POSITIVE = 2
#     ANNOTATION_TYPE_UNSPECIFIED = 0
#     IMAGE_CLASSIFICATION_ANNOTATION = 1
#     IMAGE_BOUNDING_BOX_ANNOTATION = 2
#     IMAGE_ORIENTED_BOUNDING_BOX_ANNOTATION = 13
#     IMAGE_BOUNDING_POLY_ANNOTATION = 10
#     IMAGE_POLYLINE_ANNOTATION = 11
#     IMAGE_SEGMENTATION_ANNOTATION = 12
#     VIDEO_SHOTS_CLASSIFICATION_ANNOTATION = 3
#     VIDEO_OBJECT_TRACKING_ANNOTATION = 4
#     VIDEO_OBJECT_DETECTION_ANNOTATION = 5
#     VIDEO_EVENT_ANNOTATION = 6
#     TEXT_CLASSIFICATION_ANNOTATION = 8
#     TEXT_ENTITY_EXTRACTION_ANNOTATION = 9
#     GENERAL_CLASSIFICATION_ANNOTATION = 14
# 
# Path: google/cloud/datalabeling_v1beta1/types/annotation_spec_set.py
# class AnnotationSpecSet(proto.Message):
# class AnnotationSpec(proto.Message):


# Path: google/cloud/datalabeling_v1beta1/types/evaluation.py
import proto  # type: ignore
from google.cloud.datalabeling_v1beta1.types import annotation
from google.cloud.datalabeling_v1beta1.types import annotation_spec_set
from google.protobuf import timestamp_pb2  # type: ignore

        "PrCurve",
        "ConfusionMatrix",
    },
)


class Evaluation(proto.Message):
    r"""Describes an evaluation between a machine learning model's
    predictions and ground truth labels. Created when an
    [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob]
    runs successfully.

    Attributes:
        name (str):
            Output only. Resource name of an evaluation. The name has
            the following format:

            "projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}'
        config (google.cloud.datalabeling_v1beta1.types.EvaluationConfig):
            Output only. Options used in the evaluation
            job that created this evaluation.
        evaluation_job_run_time (google.protobuf.timestamp_pb2.Timestamp):
            Output only. Timestamp for when the
            evaluation job that created this evaluation ran.
        create_time (google.protobuf.timestamp_pb2.Timestamp):
            Output only. Timestamp for when this
            evaluation was created.
        evaluation_metrics (google.cloud.datalabeling_v1beta1.types.EvaluationMetrics):
            Output only. Metrics comparing predictions to
            ground truth labels.

        annotation_type (google.cloud.datalabeling_v1beta1.types.AnnotationType):