google.cloud.videointelligence.v1p3beta1

FEATURE_UNSPECIFIED

Unspecified.

LABEL_DETECTION

Label detection. Detect objects, such as dog or flower.

SHOT_CHANGE_DETECTION

Shot change detection.

EXPLICIT_CONTENT_DETECTION

Explicit content detection.

SPEECH_TRANSCRIPTION

Speech transcription.

TEXT_DETECTION

OCR text detection and tracking.

OBJECT_TRACKING

Object detection and tracking.

LOGO_RECOGNITION

Logo detection, tracking, and recognition.

LABEL_DETECTION_MODE_UNSPECIFIED

Unspecified.

SHOT_MODE

Detect shot-level labels.

FRAME_MODE

Detect frame-level labels.

SHOT_AND_FRAME_MODE

Detect both shot-level and frame-level labels.

LIKELIHOOD_UNSPECIFIED

Unspecified likelihood.

VERY_UNLIKELY

Very unlikely.

UNLIKELY

Unlikely.

POSSIBLE

Possible.

LIKELY

Likely.

VERY_LIKELY

Very likely.

STREAMING_FEATURE_UNSPECIFIED

Unspecified.

STREAMING_LABEL_DETECTION

Label detection. Detect objects, such as dog or flower.

STREAMING_SHOT_CHANGE_DETECTION

Shot change detection.

STREAMING_EXPLICIT_CONTENT_DETECTION

Explicit content detection.

STREAMING_OBJECT_TRACKING

Object detection and tracking.

annotationProgress

Array of Object

Progress metadata for all videos specified in AnnotateVideoRequest.

This object should have the same structure as VideoAnnotationProgress

inputUri

string

Input video location. Currently, only Google Cloud 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. 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.

inputContent

string

The video data bytes. If unset, the input video(s) should be specified via input_uri. If set, input_uri should be unset.

features

Array of number

Requested video annotation features.

The number should be among the values of Feature

videoContext

Object

Additional video context and/or feature-specific parameters.

This object should have the same structure as VideoContext

outputUri

string

Optional location where the output (in JSON format) should be stored. Currently, only Google Cloud 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.

locationId

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.

annotationResults

Array of Object

Annotation results for all videos specified in AnnotateVideoRequest.

This object should have the same structure as VideoAnnotationResults

name

string

The name of the attribute, i.e. glasses, dark_glasses, mouth_open etc. A full list of supported type names will be provided in the document.

confidence

number

Detected attribute confidence. Range [0, 1].

value

string

Text value of the detection result. For example, the value for "HairColor" can be "black", "blonde", etc.

entityId

string

Opaque entity ID. Some IDs may be available in Google Knowledge Graph Search API.

description

string

Textual description, e.g. Fixed-gear bicycle.

languageCode

string

Language code for description in BCP-47 format.

frames

Array of Object

All video frames where explicit content was detected.

This object should have the same structure as ExplicitContentFrame

model

string

Model to use for explicit content detection. Supported values: "builtin/stable" (the default if unset) and "builtin/latest".

timeOffset

Object

Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.

This object should have the same structure as Duration

pornographyLikelihood

number

Likelihood of the pornography content..

The number should be among the values of Likelihood

entity

Object

Detected entity.

This object should have the same structure as Entity

categoryEntities

Array of Object

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.

This object should have the same structure as Entity

segments

Array of Object

All video segments where a label was detected.

This object should have the same structure as LabelSegment

frames

Array of Object

All video frames where a label was detected.

This object should have the same structure as LabelFrame

labelDetectionMode

number

What labels should be detected with LABEL_DETECTION, in addition to video-level labels or segment-level labels. If unspecified, defaults to SHOT_MODE.

The number should be among the values of LabelDetectionMode

stationaryCamera

boolean

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.

model

string

Model to use for label detection. Supported values: "builtin/stable" (the default if unset) and "builtin/latest".

frameConfidenceThreshold

number

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.

videoConfidenceThreshold

number

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.

timeOffset

Object

Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.

This object should have the same structure as Duration

confidence

number

Confidence that the label is accurate. Range: [0, 1].

segment

Object

Video segment where a label was detected.

This object should have the same structure as VideoSegment

confidence

number

Confidence that the label is accurate. Range: [0, 1].

entity

Object

Entity category information to specify the logo class that all the logo tracks within this LogoRecognitionAnnotation are recognized as.

This object should have the same structure as Entity

tracks

Array of Object

All logo tracks where the recognized logo appears. Each track corresponds to one logo instance appearing in consecutive frames.

This object should have the same structure as Track

segments

Array of Object

All video segments where the recognized logo appears. There might be multiple instances of the same logo class appearing in one VideoSegment.

This object should have the same structure as VideoSegment

left

number

Left X coordinate.

top

number

Top Y coordinate.

right

number

Right X coordinate.

bottom

number

Bottom Y coordinate.

vertices

Array of Object

Normalized vertices of the bounding polygon.

This object should have the same structure as NormalizedVertex

x

number

X coordinate.

y

number

Y coordinate.

entity

Object

Entity to specify the object category that this track is labeled as.

This object should have the same structure as Entity

confidence

number

Object category's labeling confidence of this track.

frames

Array of Object

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.

This object should have the same structure as ObjectTrackingFrame

segment

Object

Non-streaming batch mode ONLY. Each object track corresponds to one video segment where it appears.

This object should have the same structure as VideoSegment

trackId

number

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.

model

string

Model to use for object tracking. Supported values: "builtin/stable" (the default if unset) and "builtin/latest".

normalizedBoundingBox

Object

The normalized bounding box location of this object track for the frame.

This object should have the same structure as NormalizedBoundingBox

timeOffset

Object

The timestamp of the frame in microseconds.

This object should have the same structure as Duration

model

string

Model to use for shot change detection. Supported values: "builtin/stable" (the default if unset) and "builtin/latest".

phrases

Array of 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.

transcript

string

Transcript text representing the words that the user spoke.

confidence

number

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 typically provided only for the top hypothesis, and only for is_final=true results. Clients should not rely on the confidence field as it is not guaranteed to be accurate or consistent. The default of 0.0 is a sentinel value indicating confidence was not set.

words

Array of Object

A list of word-specific information for each recognized word.

This object should have the same structure as WordInfo

alternatives

Array of Object

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.

This object should have the same structure as SpeechRecognitionAlternative

languageCode

string

Output only. The BCP-47 language tag of the language in this result. This language code was detected to have the most likelihood of being spoken in the audio.

languageCode

string

Required The language of the supplied audio as a BCP-47 language tag. Example: "en-US". See Language Support for a list of the currently supported language codes.

maxAlternatives

number

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.

filterProfanity

boolean

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.

speechContexts

Array of Object

Optional A means to provide context to assist the speech recognition.

This object should have the same structure as SpeechContext

enableAutomaticPunctuation

boolean

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."

audioTracks

Array of number

Optional For file formats, such as MXF or MKV, supporting multiple audio tracks, specify up to two tracks. Default: track 0.

enableSpeakerDiarization

boolean

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.

diarizationSpeakerCount

number

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.

enableWordConfidence

boolean

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.

videoConfig

Object

Provides information to the annotator, specifing how to process the request. The first AnnotateStreamingVideoRequest message must only contain a video_config message.

This object should have the same structure as StreamingVideoConfig

inputContent

string

The video data to be annotated. Chunks of video data are sequentially sent in StreamingAnnotateVideoRequest messages. Except the initial StreamingAnnotateVideoRequest message containing only video_config, all subsequent AnnotateStreamingVideoRequest messages must only contain input_content field. Note: as with all bytes fields, protobuffers use a pure binary representation (not base64).

error

Object

If set, returns a google.rpc.Status message that specifies the error for the operation.

This object should have the same structure as Status

annotationResults

Object

Streaming annotation results.

This object should have the same structure as StreamingVideoAnnotationResults

annotationResultsUri

string

GCS URI that stores annotation results of one streaming session. It is a directory that can hold multiple files in JSON format. Example uri format: gs://bucket_id/object_id/cloud_project_name-session_id

stationaryCamera

boolean

Whether the video has been captured from a stationary (i.e. non-moving) camera. When set to true, might improve detection accuracy for moving objects. Default: false.

enableStorageAnnotationResult

boolean

Enable streaming storage. Default: false.

annotationResultStorageDirectory

string

GCS URI to store all annotation results for one client. Client should specify this field as the top-level storage directory. Annotation results of different sessions will be put into different sub-directories denoted by project_name and session_id. All sub-directories will be auto generated by program and will be made accessible to client in response proto. URIs must be specified in the following format: gs://bucket-id/object-id bucket-id should be a valid GCS bucket created by client and bucket permission shall also be configured properly. object-id can be arbitrary string that make sense to client. Other URI formats will return error and cause GCS write failure.

shotAnnotations

Array of Object

Shot annotation results. Each shot is represented as a video segment.

This object should have the same structure as VideoSegment

labelAnnotations

Array of Object

Label annotation results.

This object should have the same structure as LabelAnnotation

explicitAnnotation

Object

Explicit content annotation results.

This object should have the same structure as ExplicitContentAnnotation

objectAnnotations

Array of Object

Object tracking results.

This object should have the same structure as ObjectTrackingAnnotation

feature

number

Requested annotation feature.

The number should be among the values of StreamingFeature

shotChangeDetectionConfig

Object

Config for STREAMING_SHOT_CHANGE_DETECTION.

This object should have the same structure as StreamingShotChangeDetectionConfig

labelDetectionConfig

Object

Config for STREAMING_LABEL_DETECTION.

This object should have the same structure as StreamingLabelDetectionConfig

explicitContentDetectionConfig

Object

Config for STREAMING_EXPLICIT_CONTENT_DETECTION.

This object should have the same structure as StreamingExplicitContentDetectionConfig

objectTrackingConfig

Object

Config for STREAMING_OBJECT_TRACKING.

This object should have the same structure as StreamingObjectTrackingConfig

storageConfig

Object

Streaming storage option. By default: storage is disabled.

This object should have the same structure as StreamingStorageConfig

text

string

The detected text.

segments

Array of Object

All video segments where OCR detected text appears.

This object should have the same structure as TextSegment

languageHints

Array of 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.

model

string

Model to use for text detection. Supported values: "builtin/stable" (the default if unset) and "builtin/latest".

rotatedBoundingBox

Object

Bounding polygon of the detected text for this frame.

This object should have the same structure as NormalizedBoundingPoly

timeOffset

Object

Timestamp of this frame.

This object should have the same structure as Duration

segment

Object

Video segment where a text snippet was detected.

This object should have the same structure as VideoSegment

confidence

number

Confidence for the track of detected text. It is calculated as the highest over all frames where OCR detected text appears.

frames

Array of Object

Information related to the frames where OCR detected text appears.

This object should have the same structure as TextFrame

normalizedBoundingBox

Object

Normalized Bounding box in a frame, where the object is located.

This object should have the same structure as NormalizedBoundingBox

timeOffset

Object

Time-offset, relative to the beginning of the video, corresponding to the video frame for this object.

This object should have the same structure as Duration

attributes

Array of Object

Optional. The attributes of the object in the bounding box.

This object should have the same structure as DetectedAttribute

segment

Object

Video segment of a track.

This object should have the same structure as VideoSegment

timestampedObjects

Array of Object

The object with timestamp and attributes per frame in the track.

This object should have the same structure as TimestampedObject

attributes

Array of Object

Optional. Attributes in the track level.

This object should have the same structure as DetectedAttribute

confidence

number

Optional. The confidence score of the tracked object.

inputUri

string

Video file location in Google Cloud Storage.

progressPercent

number

Approximate percentage processed thus far. Guaranteed to be 100 when fully processed.

startTime

Object

Time when the request was received.

This object should have the same structure as Timestamp

updateTime

Object

Time of the most recent update.

This object should have the same structure as Timestamp

inputUri

string

Video file location in Google Cloud Storage.

segmentLabelAnnotations

Array of Object

Label annotations on video level or user specified segment level. There is exactly one element for each unique label.

This object should have the same structure as LabelAnnotation

shotLabelAnnotations

Array of Object

Label annotations on shot level. There is exactly one element for each unique label.

This object should have the same structure as LabelAnnotation

frameLabelAnnotations

Array of Object

Label annotations on frame level. There is exactly one element for each unique label.

This object should have the same structure as LabelAnnotation

shotAnnotations

Array of Object

Shot annotations. Each shot is represented as a video segment.

This object should have the same structure as VideoSegment

explicitAnnotation

Object

Explicit content annotation.

This object should have the same structure as ExplicitContentAnnotation

speechTranscriptions

Array of Object

Speech transcription.

This object should have the same structure as SpeechTranscription

textAnnotations

Array of Object

OCR text detection and tracking. Annotations for list of detected text snippets. Each will have list of frame information associated with it.

This object should have the same structure as TextAnnotation

objectAnnotations

Array of Object

Annotations for list of objects detected and tracked in video.

This object should have the same structure as ObjectTrackingAnnotation

logoRecognitionAnnotations

Array of Object

Annotations for list of logos detected, tracked and recognized in video.

This object should have the same structure as LogoRecognitionAnnotation

error

Object

If set, indicates an error. Note that for a single AnnotateVideoRequest some videos may succeed and some may fail.

This object should have the same structure as Status

segments

Array of Object

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.

This object should have the same structure as VideoSegment

labelDetectionConfig

Object

Config for LABEL_DETECTION.

This object should have the same structure as LabelDetectionConfig

shotChangeDetectionConfig

Object

Config for SHOT_CHANGE_DETECTION.

This object should have the same structure as ShotChangeDetectionConfig

explicitContentDetectionConfig

Object

Config for EXPLICIT_CONTENT_DETECTION.

This object should have the same structure as ExplicitContentDetectionConfig

speechTranscriptionConfig

Object

Config for SPEECH_TRANSCRIPTION.

This object should have the same structure as SpeechTranscriptionConfig

textDetectionConfig

Object

Config for TEXT_DETECTION.

This object should have the same structure as TextDetectionConfig

objectTrackingConfig

Object

Config for OBJECT_TRACKING.

This object should have the same structure as ObjectTrackingConfig

startTimeOffset

Object

Time-offset, relative to the beginning of the video, corresponding to the start of the segment (inclusive).

This object should have the same structure as Duration

endTimeOffset

Object

Time-offset, relative to the beginning of the video, corresponding to the end of the segment (inclusive).

This object should have the same structure as Duration

startTime

Object

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.

This object should have the same structure as Duration

endTime

Object

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.

This object should have the same structure as Duration

word

string

The word corresponding to this set of information.

confidence

number

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.

speakerTag

number

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.