# Copyright 2019 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
#
# https://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.
module Google
module Cloud
module VideoIntelligence
module V1
# Video annotation request.
# @!attribute [rw] input_uri
# @return [String]
# Input video location. Currently, only
# [Google Cloud Storage](https://cloud.google.com/storage/) URIs are
# supported, which must be specified in the following format:
# `gs://bucket-id/object-id` (other URI formats return
# {Google::Rpc::Code::INVALID_ARGUMENT}). For more information, see
# [Request URIs](https://cloud.google.com/storage/docs/reference-uris).
# A video URI may include wildcards in `object-id`, and thus identify
# multiple videos. Supported wildcards: '*' to match 0 or more characters;
# '?' to match 1 character. If unset, the input video should be embedded
# in the request as `input_content`. If set, `input_content` should be unset.
# @!attribute [rw] input_content
# @return [String]
# The video data bytes.
# If unset, the input video(s) should be specified via `input_uri`.
# If set, `input_uri` should be unset.
# @!attribute [rw] features
# @return [Array<Google::Cloud::VideoIntelligence::V1::Feature>]
# Required. Requested video annotation features.
# @!attribute [rw] video_context
# @return [Google::Cloud::VideoIntelligence::V1::VideoContext]
# Additional video context and/or feature-specific parameters.
# @!attribute [rw] output_uri
# @return [String]
# Optional. Location where the output (in JSON format) should be stored.
# Currently, only [Google Cloud Storage](https://cloud.google.com/storage/)
# URIs are supported, which must be specified in the following format:
# `gs://bucket-id/object-id` (other URI formats return
# {Google::Rpc::Code::INVALID_ARGUMENT}). For more information, see
# [Request URIs](https://cloud.google.com/storage/docs/reference-uris).
# @!attribute [rw] location_id
# @return [String]
# Optional. Cloud region where annotation should take place. Supported cloud
# regions: `us-east1`, `us-west1`, `europe-west1`, `asia-east1`. If no region
# is specified, a region will be determined based on video file location.
class AnnotateVideoRequest; end
# Video context and/or feature-specific parameters.
# @!attribute [rw] segments
# @return [Array<Google::Cloud::VideoIntelligence::V1::VideoSegment>]
# Video segments to annotate. The segments may overlap and are not required
# to be contiguous or span the whole video. If unspecified, each video is
# treated as a single segment.
# @!attribute [rw] label_detection_config
# @return [Google::Cloud::VideoIntelligence::V1::LabelDetectionConfig]
# Config for LABEL_DETECTION.
# @!attribute [rw] shot_change_detection_config
# @return [Google::Cloud::VideoIntelligence::V1::ShotChangeDetectionConfig]
# Config for SHOT_CHANGE_DETECTION.
# @!attribute [rw] explicit_content_detection_config
# @return [Google::Cloud::VideoIntelligence::V1::ExplicitContentDetectionConfig]
# Config for EXPLICIT_CONTENT_DETECTION.
# @!attribute [rw] face_detection_config
# @return [Google::Cloud::VideoIntelligence::V1::FaceDetectionConfig]
# Config for FACE_DETECTION.
# @!attribute [rw] speech_transcription_config
# @return [Google::Cloud::VideoIntelligence::V1::SpeechTranscriptionConfig]
# Config for SPEECH_TRANSCRIPTION.
# @!attribute [rw] text_detection_config
# @return [Google::Cloud::VideoIntelligence::V1::TextDetectionConfig]
# Config for TEXT_DETECTION.
# @!attribute [rw] object_tracking_config
# @return [Google::Cloud::VideoIntelligence::V1::ObjectTrackingConfig]
# Config for OBJECT_TRACKING.
class VideoContext; end
# Config for LABEL_DETECTION.
# @!attribute [rw] label_detection_mode
# @return [Google::Cloud::VideoIntelligence::V1::LabelDetectionMode]
# What labels should be detected with LABEL_DETECTION, in addition to
# video-level labels or segment-level labels.
# If unspecified, defaults to `SHOT_MODE`.
# @!attribute [rw] stationary_camera
# @return [true, false]
# Whether the video has been shot from a stationary (i.e. non-moving) camera.
# When set to true, might improve detection accuracy for moving objects.
# Should be used with `SHOT_AND_FRAME_MODE` enabled.
# @!attribute [rw] model
# @return [String]
# Model to use for label detection.
# Supported values: "builtin/stable" (the default if unset) and
# "builtin/latest".
# @!attribute [rw] frame_confidence_threshold
# @return [Float]
# The confidence threshold we perform filtering on the labels from
# frame-level detection. If not set, it is set to 0.4 by default. The valid
# range for this threshold is [0.1, 0.9]. Any value set outside of this
# range will be clipped.
# Note: for best results please follow the default threshold. We will update
# the default threshold everytime when we release a new model.
# @!attribute [rw] video_confidence_threshold
# @return [Float]
# The confidence threshold we perform filtering on the labels from
# video-level and shot-level detections. If not set, it is set to 0.3 by
# default. The valid range for this threshold is [0.1, 0.9]. Any value set
# outside of this range will be clipped.
# Note: for best results please follow the default threshold. We will update
# the default threshold everytime when we release a new model.
class LabelDetectionConfig; end
# Config for SHOT_CHANGE_DETECTION.
# @!attribute [rw] model
# @return [String]
# Model to use for shot change detection.
# Supported values: "builtin/stable" (the default if unset) and
# "builtin/latest".
class ShotChangeDetectionConfig; end
# Config for OBJECT_TRACKING.
# @!attribute [rw] model
# @return [String]
# Model to use for object tracking.
# Supported values: "builtin/stable" (the default if unset) and
# "builtin/latest".
class ObjectTrackingConfig; end
# Config for FACE_DETECTION.
# @!attribute [rw] model
# @return [String]
# Model to use for face detection.
# Supported values: "builtin/stable" (the default if unset) and
# "builtin/latest".
# @!attribute [rw] include_bounding_boxes
# @return [true, false]
# Whether bounding boxes be included in the face annotation output.
class FaceDetectionConfig; end
# Config for EXPLICIT_CONTENT_DETECTION.
# @!attribute [rw] model
# @return [String]
# Model to use for explicit content detection.
# Supported values: "builtin/stable" (the default if unset) and
# "builtin/latest".
class ExplicitContentDetectionConfig; end
# Config for TEXT_DETECTION.
# @!attribute [rw] language_hints
# @return [Array<String>]
# Language hint can be specified if the language to be detected is known a
# priori. It can increase the accuracy of the detection. Language hint must
# be language code in BCP-47 format.
#
# Automatic language detection is performed if no hint is provided.
# @!attribute [rw] model
# @return [String]
# Model to use for text detection.
# Supported values: "builtin/stable" (the default if unset) and
# "builtin/latest".
class TextDetectionConfig; end
# Video segment.
# @!attribute [rw] start_time_offset
# @return [Google::Protobuf::Duration]
# Time-offset, relative to the beginning of the video,
# corresponding to the start of the segment (inclusive).
# @!attribute [rw] end_time_offset
# @return [Google::Protobuf::Duration]
# Time-offset, relative to the beginning of the video,
# corresponding to the end of the segment (inclusive).
class VideoSegment; end
# Video segment level annotation results for label detection.
# @!attribute [rw] segment
# @return [Google::Cloud::VideoIntelligence::V1::VideoSegment]
# Video segment where a label was detected.
# @!attribute [rw] confidence
# @return [Float]
# Confidence that the label is accurate. Range: [0, 1].
class LabelSegment; end
# Video frame level annotation results for label detection.
# @!attribute [rw] time_offset
# @return [Google::Protobuf::Duration]
# Time-offset, relative to the beginning of the video, corresponding to the
# video frame for this location.
# @!attribute [rw] confidence
# @return [Float]
# Confidence that the label is accurate. Range: [0, 1].
class LabelFrame; end
# Detected entity from video analysis.
# @!attribute [rw] entity_id
# @return [String]
# Opaque entity ID. Some IDs may be available in
# [Google Knowledge Graph Search
# API](https://developers.google.com/knowledge-graph/).
# @!attribute [rw] description
# @return [String]
# Textual description, e.g. `Fixed-gear bicycle`.
# @!attribute [rw] language_code
# @return [String]
# Language code for `description` in BCP-47 format.
class Entity; end
# Label annotation.
# @!attribute [rw] entity
# @return [Google::Cloud::VideoIntelligence::V1::Entity]
# Detected entity.
# @!attribute [rw] category_entities
# @return [Array<Google::Cloud::VideoIntelligence::V1::Entity>]
# Common categories for the detected entity.
# E.g. when the label is `Terrier` the category is likely `dog`. And in some
# cases there might be more than one categories e.g. `Terrier` could also be
# a `pet`.
# @!attribute [rw] segments
# @return [Array<Google::Cloud::VideoIntelligence::V1::LabelSegment>]
# All video segments where a label was detected.
# @!attribute [rw] frames
# @return [Array<Google::Cloud::VideoIntelligence::V1::LabelFrame>]
# All video frames where a label was detected.
class LabelAnnotation; end
# Video frame level annotation results for explicit content.
# @!attribute [rw] time_offset
# @return [Google::Protobuf::Duration]
# Time-offset, relative to the beginning of the video, corresponding to the
# video frame for this location.
# @!attribute [rw] pornography_likelihood
# @return [Google::Cloud::VideoIntelligence::V1::Likelihood]
# Likelihood of the pornography content..
class ExplicitContentFrame; end
# Explicit content annotation (based on per-frame visual signals only).
# If no explicit content has been detected in a frame, no annotations are
# present for that frame.
# @!attribute [rw] frames
# @return [Array<Google::Cloud::VideoIntelligence::V1::ExplicitContentFrame>]
# All video frames where explicit content was detected.
class ExplicitContentAnnotation; end
# Normalized bounding box.
# The normalized vertex coordinates are relative to the original image.
# Range: [0, 1].
# @!attribute [rw] left
# @return [Float]
# Left X coordinate.
# @!attribute [rw] top
# @return [Float]
# Top Y coordinate.
# @!attribute [rw] right
# @return [Float]
# Right X coordinate.
# @!attribute [rw] bottom
# @return [Float]
# Bottom Y coordinate.
class NormalizedBoundingBox; end
# Video segment level annotation results for face detection.
# @!attribute [rw] segment
# @return [Google::Cloud::VideoIntelligence::V1::VideoSegment]
# Video segment where a face was detected.
class FaceSegment; end
# Video frame level annotation results for face detection.
# @!attribute [rw] normalized_bounding_boxes
# @return [Array<Google::Cloud::VideoIntelligence::V1::NormalizedBoundingBox>]
# Normalized Bounding boxes in a frame.
# There can be more than one boxes if the same face is detected in multiple
# locations within the current frame.
# @!attribute [rw] time_offset
# @return [Google::Protobuf::Duration]
# Time-offset, relative to the beginning of the video,
# corresponding to the video frame for this location.
class FaceFrame; end
# Face annotation.
# @!attribute [rw] thumbnail
# @return [String]
# Thumbnail of a representative face view (in JPEG format).
# @!attribute [rw] segments
# @return [Array<Google::Cloud::VideoIntelligence::V1::FaceSegment>]
# All video segments where a face was detected.
# @!attribute [rw] frames
# @return [Array<Google::Cloud::VideoIntelligence::V1::FaceFrame>]
# All video frames where a face was detected.
class FaceAnnotation; end
# Annotation results for a single video.
# @!attribute [rw] input_uri
# @return [String]
# Video file location in
# [Google Cloud Storage](https://cloud.google.com/storage/).
# @!attribute [rw] segment
# @return [Google::Cloud::VideoIntelligence::V1::VideoSegment]
# Video segment on which the annotation is run.
# @!attribute [rw] segment_label_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::LabelAnnotation>]
# Topical label annotations on video level or user specified segment level.
# There is exactly one element for each unique label.
# @!attribute [rw] segment_presence_label_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::LabelAnnotation>]
# Presence label annotations on video level or user specified segment level.
# There is exactly one element for each unique label. Compared to the
# existing topical `segment_label_annotations`, this field presents more
# fine-grained, segment-level labels detected in video content and is made
# available only when the client sets `LabelDetectionConfig.model` to
# "builtin/latest" in the request.
# @!attribute [rw] shot_label_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::LabelAnnotation>]
# Topical label annotations on shot level.
# There is exactly one element for each unique label.
# @!attribute [rw] shot_presence_label_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::LabelAnnotation>]
# Presence label annotations on shot level. There is exactly one element for
# each unique label. Compared to the existing topical
# `shot_label_annotations`, this field presents more fine-grained, shot-level
# labels detected in video content and is made available only when the client
# sets `LabelDetectionConfig.model` to "builtin/latest" in the request.
# @!attribute [rw] frame_label_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::LabelAnnotation>]
# Label annotations on frame level.
# There is exactly one element for each unique label.
# @!attribute [rw] face_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::FaceAnnotation>]
# Face annotations. There is exactly one element for each unique face.
# @!attribute [rw] shot_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::VideoSegment>]
# Shot annotations. Each shot is represented as a video segment.
# @!attribute [rw] explicit_annotation
# @return [Google::Cloud::VideoIntelligence::V1::ExplicitContentAnnotation]
# Explicit content annotation.
# @!attribute [rw] speech_transcriptions
# @return [Array<Google::Cloud::VideoIntelligence::V1::SpeechTranscription>]
# Speech transcription.
# @!attribute [rw] text_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::TextAnnotation>]
# OCR text detection and tracking.
# Annotations for list of detected text snippets. Each will have list of
# frame information associated with it.
# @!attribute [rw] object_annotations
# @return [Array<Google::Cloud::VideoIntelligence::V1::ObjectTrackingAnnotation>]
# Annotations for list of objects detected and tracked in video.
# @!attribute [rw] error
# @return [Google::Rpc::Status]
# If set, indicates an error. Note that for a single `AnnotateVideoRequest`
# some videos may succeed and some may fail.
class VideoAnnotationResults; end
# Video annotation response. Included in the `response`
# field of the `Operation` returned by the `GetOperation`
# call of the `google::longrunning::Operations` service.
# @!attribute [rw] annotation_results
# @return [Array<Google::Cloud::VideoIntelligence::V1::VideoAnnotationResults>]
# Annotation results for all videos specified in `AnnotateVideoRequest`.
class AnnotateVideoResponse; end
# Annotation progress for a single video.
# @!attribute [rw] input_uri
# @return [String]
# Video file location in
# [Google Cloud Storage](https://cloud.google.com/storage/).
# @!attribute [rw] progress_percent
# @return [Integer]
# Approximate percentage processed thus far. Guaranteed to be
# 100 when fully processed.
# @!attribute [rw] start_time
# @return [Google::Protobuf::Timestamp]
# Time when the request was received.
# @!attribute [rw] update_time
# @return [Google::Protobuf::Timestamp]
# Time of the most recent update.
# @!attribute [rw] feature
# @return [Google::Cloud::VideoIntelligence::V1::Feature]
# Specifies which feature is being tracked if the request contains more than
# one features.
# @!attribute [rw] segment
# @return [Google::Cloud::VideoIntelligence::V1::VideoSegment]
# Specifies which segment is being tracked if the request contains more than
# one segments.
class VideoAnnotationProgress; end
# Video annotation progress. Included in the `metadata`
# field of the `Operation` returned by the `GetOperation`
# call of the `google::longrunning::Operations` service.
# @!attribute [rw] annotation_progress
# @return [Array<Google::Cloud::VideoIntelligence::V1::VideoAnnotationProgress>]
# Progress metadata for all videos specified in `AnnotateVideoRequest`.
class AnnotateVideoProgress; end
# Config for SPEECH_TRANSCRIPTION.
# @!attribute [rw] language_code
# @return [String]
# Required. *Required* The language of the supplied audio as a
# [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag.
# Example: "en-US".
# See [Language Support](https://cloud.google.com/speech/docs/languages)
# for a list of the currently supported language codes.
# @!attribute [rw] max_alternatives
# @return [Integer]
# Optional. Maximum number of recognition hypotheses to be returned.
# Specifically, the maximum number of `SpeechRecognitionAlternative` messages
# within each `SpeechTranscription`. The server may return fewer than
# `max_alternatives`. Valid values are `0`-`30`. A value of `0` or `1` will
# return a maximum of one. If omitted, will return a maximum of one.
# @!attribute [rw] filter_profanity
# @return [true, false]
# Optional. If set to `true`, the server will attempt to filter out
# profanities, replacing all but the initial character in each filtered word
# with asterisks, e.g. "f***". If set to `false` or omitted, profanities
# won't be filtered out.
# @!attribute [rw] speech_contexts
# @return [Array<Google::Cloud::VideoIntelligence::V1::SpeechContext>]
# Optional. A means to provide context to assist the speech recognition.
# @!attribute [rw] enable_automatic_punctuation
# @return [true, false]
# Optional. If 'true', adds punctuation to recognition result hypotheses.
# This feature is only available in select languages. Setting this for
# requests in other languages has no effect at all. The default 'false' value
# does not add punctuation to result hypotheses. NOTE: "This is currently
# offered as an experimental service, complimentary to all users. In the
# future this may be exclusively available as a premium feature."
# @!attribute [rw] audio_tracks
# @return [Array<Integer>]
# Optional. For file formats, such as MXF or MKV, supporting multiple audio
# tracks, specify up to two tracks. Default: track 0.
# @!attribute [rw] enable_speaker_diarization
# @return [true, false]
# Optional. If 'true', enables speaker detection for each recognized word in
# the top alternative of the recognition result using a speaker_tag provided
# in the WordInfo.
# Note: When this is true, we send all the words from the beginning of the
# audio for the top alternative in every consecutive responses.
# This is done in order to improve our speaker tags as our models learn to
# identify the speakers in the conversation over time.
# @!attribute [rw] diarization_speaker_count
# @return [Integer]
# Optional. If set, specifies the estimated number of speakers in the conversation.
# If not set, defaults to '2'.
# Ignored unless enable_speaker_diarization is set to true.
# @!attribute [rw] enable_word_confidence
# @return [true, false]
# Optional. If `true`, the top result includes a list of words and the
# confidence for those words. If `false`, no word-level confidence
# information is returned. The default is `false`.
class SpeechTranscriptionConfig; end
# Provides "hints" to the speech recognizer to favor specific words and phrases
# in the results.
# @!attribute [rw] phrases
# @return [Array<String>]
# Optional. A list of strings containing words and phrases "hints" so that
# the speech recognition is more likely to recognize them. This can be used
# to improve the accuracy for specific words and phrases, for example, if
# specific commands are typically spoken by the user. This can also be used
# to add additional words to the vocabulary of the recognizer. See
# [usage limits](https://cloud.google.com/speech/limits#content).
class SpeechContext; end
# A speech recognition result corresponding to a portion of the audio.
# @!attribute [rw] alternatives
# @return [Array<Google::Cloud::VideoIntelligence::V1::SpeechRecognitionAlternative>]
# May contain one or more recognition hypotheses (up to the maximum specified
# in `max_alternatives`). These alternatives are ordered in terms of
# accuracy, with the top (first) alternative being the most probable, as
# ranked by the recognizer.
# @!attribute [rw] language_code
# @return [String]
# Output only. The [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag of
# the language in this result. This language code was detected to have the
# most likelihood of being spoken in the audio.
class SpeechTranscription; end
# Alternative hypotheses (a.k.a. n-best list).
# @!attribute [rw] transcript
# @return [String]
# Transcript text representing the words that the user spoke.
# @!attribute [rw] confidence
# @return [Float]
# Output only. The confidence estimate between 0.0 and 1.0. A higher number
# indicates an estimated greater likelihood that the recognized words are
# correct. This field is set only for the top alternative.
# This field is not guaranteed to be accurate and users should not rely on it
# to be always provided.
# The default of 0.0 is a sentinel value indicating `confidence` was not set.
# @!attribute [rw] words
# @return [Array<Google::Cloud::VideoIntelligence::V1::WordInfo>]
# Output only. A list of word-specific information for each recognized word.
# Note: When `enable_speaker_diarization` is true, you will see all the words
# from the beginning of the audio.
class SpeechRecognitionAlternative; end
# Word-specific information for recognized words. Word information is only
# included in the response when certain request parameters are set, such
# as `enable_word_time_offsets`.
# @!attribute [rw] start_time
# @return [Google::Protobuf::Duration]
# Time offset relative to the beginning of the audio, and
# corresponding to the start of the spoken word. This field is only set if
# `enable_word_time_offsets=true` and only in the top hypothesis. This is an
# experimental feature and the accuracy of the time offset can vary.
# @!attribute [rw] end_time
# @return [Google::Protobuf::Duration]
# Time offset relative to the beginning of the audio, and
# corresponding to the end of the spoken word. This field is only set if
# `enable_word_time_offsets=true` and only in the top hypothesis. This is an
# experimental feature and the accuracy of the time offset can vary.
# @!attribute [rw] word
# @return [String]
# The word corresponding to this set of information.
# @!attribute [rw] confidence
# @return [Float]
# Output only. The confidence estimate between 0.0 and 1.0. A higher number
# indicates an estimated greater likelihood that the recognized words are
# correct. This field is set only for the top alternative.
# This field is not guaranteed to be accurate and users should not rely on it
# to be always provided.
# The default of 0.0 is a sentinel value indicating `confidence` was not set.
# @!attribute [rw] speaker_tag
# @return [Integer]
# Output only. A distinct integer value is assigned for every speaker within
# the audio. This field specifies which one of those speakers was detected to
# have spoken this word. Value ranges from 1 up to diarization_speaker_count,
# and is only set if speaker diarization is enabled.
class WordInfo; end
# A vertex represents a 2D point in the image.
# NOTE: the normalized vertex coordinates are relative to the original image
# and range from 0 to 1.
# @!attribute [rw] x
# @return [Float]
# X coordinate.
# @!attribute [rw] y
# @return [Float]
# Y coordinate.
class NormalizedVertex; end
# Normalized bounding polygon for text (that might not be aligned with axis).
# Contains list of the corner points in clockwise order starting from
# top-left corner. For example, for a rectangular bounding box:
# When the text is horizontal it might look like:
# 0----1
# | |
# 3----2
#
# When it's clockwise rotated 180 degrees around the top-left corner it
# becomes:
# 2----3
# | |
# 1----0
#
# and the vertex order will still be (0, 1, 2, 3). Note that values can be less
# than 0, or greater than 1 due to trignometric calculations for location of
# the box.
# @!attribute [rw] vertices
# @return [Array<Google::Cloud::VideoIntelligence::V1::NormalizedVertex>]
# Normalized vertices of the bounding polygon.
class NormalizedBoundingPoly; end
# Video segment level annotation results for text detection.
# @!attribute [rw] segment
# @return [Google::Cloud::VideoIntelligence::V1::VideoSegment]
# Video segment where a text snippet was detected.
# @!attribute [rw] confidence
# @return [Float]
# Confidence for the track of detected text. It is calculated as the highest
# over all frames where OCR detected text appears.
# @!attribute [rw] frames
# @return [Array<Google::Cloud::VideoIntelligence::V1::TextFrame>]
# Information related to the frames where OCR detected text appears.
class TextSegment; end
# Video frame level annotation results for text annotation (OCR).
# Contains information regarding timestamp and bounding box locations for the
# frames containing detected OCR text snippets.
# @!attribute [rw] rotated_bounding_box
# @return [Google::Cloud::VideoIntelligence::V1::NormalizedBoundingPoly]
# Bounding polygon of the detected text for this frame.
# @!attribute [rw] time_offset
# @return [Google::Protobuf::Duration]
# Timestamp of this frame.
class TextFrame; end
# Annotations related to one detected OCR text snippet. This will contain the
# corresponding text, confidence value, and frame level information for each
# detection.
# @!attribute [rw] text
# @return [String]
# The detected text.
# @!attribute [rw] segments
# @return [Array<Google::Cloud::VideoIntelligence::V1::TextSegment>]
# All video segments where OCR detected text appears.
class TextAnnotation; end
# Video frame level annotations for object detection and tracking. This field
# stores per frame location, time offset, and confidence.
# @!attribute [rw] normalized_bounding_box
# @return [Google::Cloud::VideoIntelligence::V1::NormalizedBoundingBox]
# The normalized bounding box location of this object track for the frame.
# @!attribute [rw] time_offset
# @return [Google::Protobuf::Duration]
# The timestamp of the frame in microseconds.
class ObjectTrackingFrame; end
# Annotations corresponding to one tracked object.
# @!attribute [rw] segment
# @return [Google::Cloud::VideoIntelligence::V1::VideoSegment]
# Non-streaming batch mode ONLY.
# Each object track corresponds to one video segment where it appears.
# @!attribute [rw] track_id
# @return [Integer]
# Streaming mode ONLY.
# In streaming mode, we do not know the end time of a tracked object
# before it is completed. Hence, there is no VideoSegment info returned.
# Instead, we provide a unique identifiable integer track_id so that
# the customers can correlate the results of the ongoing
# ObjectTrackAnnotation of the same track_id over time.
# @!attribute [rw] entity
# @return [Google::Cloud::VideoIntelligence::V1::Entity]
# Entity to specify the object category that this track is labeled as.
# @!attribute [rw] confidence
# @return [Float]
# Object category's labeling confidence of this track.
# @!attribute [rw] frames
# @return [Array<Google::Cloud::VideoIntelligence::V1::ObjectTrackingFrame>]
# Information corresponding to all frames where this object track appears.
# Non-streaming batch mode: it may be one or multiple ObjectTrackingFrame
# messages in frames.
# Streaming mode: it can only be one ObjectTrackingFrame message in frames.
class ObjectTrackingAnnotation; end
# Video annotation feature.
module Feature
# Unspecified.
FEATURE_UNSPECIFIED = 0
# Label detection. Detect objects, such as dog or flower.
LABEL_DETECTION = 1
# Shot change detection.
SHOT_CHANGE_DETECTION = 2
# Explicit content detection.
EXPLICIT_CONTENT_DETECTION = 3
# Human face detection and tracking.
FACE_DETECTION = 4
# Speech transcription.
SPEECH_TRANSCRIPTION = 6
# OCR text detection and tracking.
TEXT_DETECTION = 7
# Object detection and tracking.
OBJECT_TRACKING = 9
end
# Label detection mode.
module LabelDetectionMode
# Unspecified.
LABEL_DETECTION_MODE_UNSPECIFIED = 0
# Detect shot-level labels.
SHOT_MODE = 1
# Detect frame-level labels.
FRAME_MODE = 2
# Detect both shot-level and frame-level labels.
SHOT_AND_FRAME_MODE = 3
end
# Bucketized representation of likelihood.
module Likelihood
# Unspecified likelihood.
LIKELIHOOD_UNSPECIFIED = 0
# Very unlikely.
VERY_UNLIKELY = 1
# Unlikely.
UNLIKELY = 2
# Possible.
POSSIBLE = 3
# Likely.
LIKELY = 4
# Very likely.
VERY_LIKELY = 5
end
end
end
end
end