# -*- coding: utf-8 -*-
# Copyright 2020 Google LLC
#
# 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.
#
import proto  # type: ignore

from google.protobuf import duration_pb2  # type: ignore
from google.protobuf import wrappers_pb2  # type: ignore


__protobuf__ = proto.module(
    package="google.cloud.aiplatform.v1.schema.predict.prediction",
    manifest={"VideoObjectTrackingPredictionResult",},
)


class VideoObjectTrackingPredictionResult(proto.Message):
    r"""Prediction output format for Video Object Tracking.

    Attributes:
        id (str):
            The resource ID of the AnnotationSpec that
            had been identified.
        display_name (str):
            The display name of the AnnotationSpec that
            had been identified.
        time_segment_start (google.protobuf.duration_pb2.Duration):
            The beginning, inclusive, of the video's time
            segment in which the object instance has been
            detected. Expressed as a number of seconds as
            measured from the start of the video, with
            fractions up to a microsecond precision, and
            with "s" appended at the end.
        time_segment_end (google.protobuf.duration_pb2.Duration):
            The end, inclusive, of the video's time
            segment in which the object instance has been
            detected. Expressed as a number of seconds as
            measured from the start of the video, with
            fractions up to a microsecond precision, and
            with "s" appended at the end.
        confidence (google.protobuf.wrappers_pb2.FloatValue):
            The Model's confidence in correction of this
            prediction, higher value means higher
            confidence.
        frames (Sequence[google.cloud.aiplatform.v1.schema.predict.prediction_v1.types.VideoObjectTrackingPredictionResult.Frame]):
            All of the frames of the video in which a
            single object instance has been detected. The
            bounding boxes in the frames identify the same
            object.
    """

    class Frame(proto.Message):
        r"""The fields ``xMin``, ``xMax``, ``yMin``, and ``yMax`` refer to a
        bounding box, i.e. the rectangle over the video frame pinpointing
        the found AnnotationSpec. The coordinates are relative to the frame
        size, and the point 0,0 is in the top left of the frame.

        Attributes:
            time_offset (google.protobuf.duration_pb2.Duration):
                A time (frame) of a video in which the object
                has been detected. Expressed as a number of
                seconds as measured from the start of the video,
                with fractions up to a microsecond precision,
                and with "s" appended at the end.
            x_min (google.protobuf.wrappers_pb2.FloatValue):
                The leftmost coordinate of the bounding box.
            x_max (google.protobuf.wrappers_pb2.FloatValue):
                The rightmost coordinate of the bounding box.
            y_min (google.protobuf.wrappers_pb2.FloatValue):
                The topmost coordinate of the bounding box.
            y_max (google.protobuf.wrappers_pb2.FloatValue):
                The bottommost coordinate of the bounding
                box.
        """

        time_offset = proto.Field(
            proto.MESSAGE, number=1, message=duration_pb2.Duration,
        )
        x_min = proto.Field(proto.MESSAGE, number=2, message=wrappers_pb2.FloatValue,)
        x_max = proto.Field(proto.MESSAGE, number=3, message=wrappers_pb2.FloatValue,)
        y_min = proto.Field(proto.MESSAGE, number=4, message=wrappers_pb2.FloatValue,)
        y_max = proto.Field(proto.MESSAGE, number=5, message=wrappers_pb2.FloatValue,)

    id = proto.Field(proto.STRING, number=1,)
    display_name = proto.Field(proto.STRING, number=2,)
    time_segment_start = proto.Field(
        proto.MESSAGE, number=3, message=duration_pb2.Duration,
    )
    time_segment_end = proto.Field(
        proto.MESSAGE, number=4, message=duration_pb2.Duration,
    )
    confidence = proto.Field(proto.MESSAGE, number=5, message=wrappers_pb2.FloatValue,)
    frames = proto.RepeatedField(proto.MESSAGE, number=6, message=Frame,)


__all__ = tuple(sorted(__protobuf__.manifest))
