/
video_classification.py
84 lines (75 loc) · 3.43 KB
/
video_classification.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
# -*- 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={"VideoClassificationPredictionResult",},
)
class VideoClassificationPredictionResult(proto.Message):
r"""Prediction output format for Video Classification.
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.
type_ (str):
The type of the prediction. The requested
types can be configured via parameters. This
will be one of - segment-classification
- shot-classification
- one-sec-interval-classification
time_segment_start (google.protobuf.duration_pb2.Duration):
The beginning, inclusive, of the video's time
segment in which the AnnotationSpec has been
identified. 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. Note that for
'segment-classification' prediction type, this
equals the original 'timeSegmentStart' from the
input instance, for other types it is the start
of a shot or a 1 second interval respectively.
time_segment_end (google.protobuf.duration_pb2.Duration):
The end, exclusive, of the video's time
segment in which the AnnotationSpec has been
identified. 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. Note that for
'segment-classification' prediction type, this
equals the original 'timeSegmentEnd' from the
input instance, for other types it is the end of
a shot or a 1 second interval respectively.
confidence (google.protobuf.wrappers_pb2.FloatValue):
The Model's confidence in correction of this
prediction, higher value means higher
confidence.
"""
id = proto.Field(proto.STRING, number=1,)
display_name = proto.Field(proto.STRING, number=2,)
type_ = proto.Field(proto.STRING, number=3,)
time_segment_start = proto.Field(
proto.MESSAGE, number=4, message=duration_pb2.Duration,
)
time_segment_end = proto.Field(
proto.MESSAGE, number=5, message=duration_pb2.Duration,
)
confidence = proto.Field(proto.MESSAGE, number=6, message=wrappers_pb2.FloatValue,)
__all__ = tuple(sorted(__protobuf__.manifest))