As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Types for Google Cloud Videointelligence v1p3beta1 API¶

class google.cloud.videointelligence_v1p3beta1.types.AnnotateVideoProgress(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video annotation progress. Included in the metadata field of the Operation returned by the GetOperation call of the google::longrunning::Operations service.

annotation_progress¶

Progress metadata for all videos specified in AnnotateVideoRequest.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.VideoAnnotationProgress]

class google.cloud.videointelligence_v1p3beta1.types.AnnotateVideoRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video annotation request.

input_uri¶

Input video location. Currently, only Cloud Storage URIs are supported. URIs must be specified in the following format: gs://bucket-id/object-id (other URI formats return [google.rpc.Code.INVALID_ARGUMENT][google.rpc.Code.INVALID_ARGUMENT]). For more information, see Request URIs. To identify multiple videos, a video URI may include wildcards in the object-id. 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 must be unset.

Type: str

input_content¶

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

Type: bytes

features¶

Required. Requested video annotation features.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.Feature]

video_context¶

Additional video context and/or feature-specific parameters.

Type: google.cloud.videointelligence_v1p3beta1.types.VideoContext

output_uri¶

Optional. Location where the output (in JSON format) should be stored. Currently, only Cloud Storage URIs are supported. These must be specified in the following format: gs://bucket-id/object-id (other URI formats return [google.rpc.Code.INVALID_ARGUMENT][google.rpc.Code.INVALID_ARGUMENT]). For more information, see Request URIs.

Type: str

location_id¶

Optional. Cloud region where annotation should take place. Supported cloud regions are: us-east1, us-west1, europe-west1, asia-east1. If no region is specified, the region will be determined based on video file location.

Type: str

class google.cloud.videointelligence_v1p3beta1.types.AnnotateVideoResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video annotation response. Included in the response field of the Operation returned by the GetOperation call of the google::longrunning::Operations service.

annotation_results¶

Annotation results for all videos specified in AnnotateVideoRequest.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.VideoAnnotationResults]

class google.cloud.videointelligence_v1p3beta1.types.Celebrity(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Celebrity definition.

name¶

The resource name of the celebrity. Have the format video-intelligence/kg-mid indicates a celebrity from preloaded gallery. kg-mid is the id in Google knowledge graph, which is unique for the celebrity.

Type: str

display_name¶

The celebrity name.

Type: str

description¶

Textual description of additional information about the celebrity, if applicable.

Type: str

class google.cloud.videointelligence_v1p3beta1.types.CelebrityRecognitionAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Celebrity recognition annotation per video.

celebrity_tracks¶

The tracks detected from the input video, including recognized celebrities and other detected faces in the video.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.CelebrityTrack]

class google.cloud.videointelligence_v1p3beta1.types.CelebrityTrack(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

The annotation result of a celebrity face track. RecognizedCelebrity field could be empty if the face track does not have any matched celebrities.

celebrities¶

Top N match of the celebrities for the face in this track.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.CelebrityTrack.RecognizedCelebrity]

face_track¶

A track of a person’s face.

Type: google.cloud.videointelligence_v1p3beta1.types.Track

class RecognizedCelebrity(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

The recognized celebrity with confidence score.

celebrity¶

The recognized celebrity.

Type: google.cloud.videointelligence_v1p3beta1.types.Celebrity

confidence¶

Recognition confidence. Range [0, 1].

Type: float

class google.cloud.videointelligence_v1p3beta1.types.DetectedAttribute(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A generic detected attribute represented by name in string format.

name¶

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

Type: str

confidence¶

Detected attribute confidence. Range [0, 1].

Type: float

value¶

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

Type: str

class google.cloud.videointelligence_v1p3beta1.types.DetectedLandmark(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A generic detected landmark represented by name in string format and a 2D location.

name¶

The name of this landmark, for example, left_hand, right_shoulder.

Type: str

point¶

The 2D point of the detected landmark using the normalized image coordindate system. The normalized coordinates have the range from 0 to 1.

Type: google.cloud.videointelligence_v1p3beta1.types.NormalizedVertex

confidence¶

The confidence score of the detected landmark. Range [0, 1].

Type: float

class google.cloud.videointelligence_v1p3beta1.types.Entity(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Detected entity from video analysis.

entity_id¶

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

Type: str

description¶

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

Type: str

language_code¶

Language code for description in BCP-47 format.

Type: str

class google.cloud.videointelligence_v1p3beta1.types.ExplicitContentAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

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.

frames¶

All video frames where explicit content was detected.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.ExplicitContentFrame]

class google.cloud.videointelligence_v1p3beta1.types.ExplicitContentDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for EXPLICIT_CONTENT_DETECTION.

model¶

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

Type: str

class google.cloud.videointelligence_v1p3beta1.types.ExplicitContentFrame(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video frame level annotation results for explicit content.

time_offset¶

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

Type: google.protobuf.duration_pb2.Duration

pornography_likelihood¶

Likelihood of the pornography content..

Type: google.cloud.videointelligence_v1p3beta1.types.Likelihood

class google.cloud.videointelligence_v1p3beta1.types.FaceDetectionAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Face detection annotation.

tracks¶

The face tracks with attributes.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.Track]

thumbnail¶

The thumbnail of a person’s face.

Type: bytes

class google.cloud.videointelligence_v1p3beta1.types.FaceDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for FACE_DETECTION.

model¶

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

Type: str

include_bounding_boxes¶

Whether bounding boxes are included in the face annotation output.

Type: bool

include_attributes¶

Whether to enable face attributes detection, such as glasses, dark_glasses, mouth_open etc. Ignored if ‘include_bounding_boxes’ is set to false.

Type: bool

class google.cloud.videointelligence_v1p3beta1.types.Feature(value)[source]¶

Bases: proto.enums.Enum

Video annotation feature.

Values:

FEATURE_UNSPECIFIED (0):: Unspecified.
LABEL_DETECTION (1):: Label detection. Detect objects, such as dog or flower.
SHOT_CHANGE_DETECTION (2):: Shot change detection.
EXPLICIT_CONTENT_DETECTION (3):: Explicit content detection.
FACE_DETECTION (4):: Human face detection.
SPEECH_TRANSCRIPTION (6):: Speech transcription.
TEXT_DETECTION (7):: OCR text detection and tracking.
OBJECT_TRACKING (9):: Object detection and tracking.
LOGO_RECOGNITION (12):: Logo detection, tracking, and recognition.
CELEBRITY_RECOGNITION (13):: Celebrity recognition.
PERSON_DETECTION (14):: Person detection.

class google.cloud.videointelligence_v1p3beta1.types.LabelAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Label annotation.

entity¶

Detected entity.

Type: google.cloud.videointelligence_v1p3beta1.types.Entity

category_entities¶

Common categories for the detected entity. For example, 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.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.Entity]

segments¶

All video segments where a label was detected.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.LabelSegment]

frames¶

All video frames where a label was detected.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.LabelFrame]

class google.cloud.videointelligence_v1p3beta1.types.LabelDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for LABEL_DETECTION.

label_detection_mode¶

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

Type: google.cloud.videointelligence_v1p3beta1.types.LabelDetectionMode

stationary_camera¶

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.

Type: bool

model¶

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

Type: str

frame_confidence_threshold¶

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, follow the default threshold. We will update the default threshold everytime when we release a new model.

Type: float

video_confidence_threshold¶

The confidence threshold we perform filtering on the labels from video-level and shot-level detections. If not set, it’s 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, follow the default threshold. We will update the default threshold everytime when we release a new model.

Type: float

class google.cloud.videointelligence_v1p3beta1.types.LabelDetectionMode(value)[source]¶

Bases: proto.enums.Enum

Label detection mode.

Values:

LABEL_DETECTION_MODE_UNSPECIFIED (0):: Unspecified.
SHOT_MODE (1):: Detect shot-level labels.
FRAME_MODE (2):: Detect frame-level labels.
SHOT_AND_FRAME_MODE (3):: Detect both shot-level and frame-level labels.

class google.cloud.videointelligence_v1p3beta1.types.LabelFrame(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video frame level annotation results for label detection.

time_offset¶

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

Type: google.protobuf.duration_pb2.Duration

confidence¶

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

Type: float

class google.cloud.videointelligence_v1p3beta1.types.LabelSegment(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video segment level annotation results for label detection.

segment¶

Video segment where a label was detected.

Type: google.cloud.videointelligence_v1p3beta1.types.VideoSegment

confidence¶

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

Type: float

class google.cloud.videointelligence_v1p3beta1.types.Likelihood(value)[source]¶

Bases: proto.enums.Enum

Bucketized representation of likelihood.

Values:

LIKELIHOOD_UNSPECIFIED (0):: Unspecified likelihood.
VERY_UNLIKELY (1):: Very unlikely.
UNLIKELY (2):: Unlikely.
POSSIBLE (3):: Possible.
LIKELY (4):: Likely.
VERY_LIKELY (5):: Very likely.

class google.cloud.videointelligence_v1p3beta1.types.LogoRecognitionAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Annotation corresponding to one detected, tracked and recognized logo class.

entity¶

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

Type: google.cloud.videointelligence_v1p3beta1.types.Entity

tracks¶

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

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.Track]

segments¶

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

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.VideoSegment]

class google.cloud.videointelligence_v1p3beta1.types.NormalizedBoundingBox(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Normalized bounding box. The normalized vertex coordinates are relative to the original image. Range: [0, 1].

left¶

Left X coordinate.

Type: float

top¶

Top Y coordinate.

Type: float

right¶

Right X coordinate.

Type: float

bottom¶

Bottom Y coordinate.

Type: float

class google.cloud.videointelligence_v1p3beta1.types.NormalizedBoundingPoly(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

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.

vertices¶

Normalized vertices of the bounding polygon.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.NormalizedVertex]

class google.cloud.videointelligence_v1p3beta1.types.NormalizedVertex(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

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.

x¶

X coordinate.

Type: float

y¶

Y coordinate.

Type: float

class google.cloud.videointelligence_v1p3beta1.types.ObjectTrackingAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Annotations corresponding to one tracked object.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

segment¶

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

This field is a member of oneof track_info.

Type: google.cloud.videointelligence_v1p3beta1.types.VideoSegment

track_id¶

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.

This field is a member of oneof track_info.

Type: int

entity¶

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

Type: google.cloud.videointelligence_v1p3beta1.types.Entity

confidence¶

Object category’s labeling confidence of this track.

Type: float

frames¶

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.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.ObjectTrackingFrame]

class google.cloud.videointelligence_v1p3beta1.types.ObjectTrackingConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for OBJECT_TRACKING.

model¶

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

Type: str

class google.cloud.videointelligence_v1p3beta1.types.ObjectTrackingFrame(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video frame level annotations for object detection and tracking. This field stores per frame location, time offset, and confidence.

normalized_bounding_box¶

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

Type: google.cloud.videointelligence_v1p3beta1.types.NormalizedBoundingBox

time_offset¶

The timestamp of the frame in microseconds.

Type: google.protobuf.duration_pb2.Duration

class google.cloud.videointelligence_v1p3beta1.types.PersonDetectionAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Person detection annotation per video.

tracks¶

The detected tracks of a person.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.Track]

class google.cloud.videointelligence_v1p3beta1.types.PersonDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for PERSON_DETECTION.

include_bounding_boxes¶

Whether bounding boxes are included in the person detection annotation output.

Type: bool

include_pose_landmarks¶

Whether to enable pose landmarks detection. Ignored if ‘include_bounding_boxes’ is set to false.

Type: bool

include_attributes¶

Whether to enable person attributes detection, such as cloth color (black, blue, etc), type (coat, dress, etc), pattern (plain, floral, etc), hair, etc. Ignored if ‘include_bounding_boxes’ is set to false.

Type: bool

class google.cloud.videointelligence_v1p3beta1.types.ShotChangeDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for SHOT_CHANGE_DETECTION.

model¶

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

Type: str

class google.cloud.videointelligence_v1p3beta1.types.SpeechContext(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Provides “hints” to the speech recognizer to favor specific words and phrases in the results.

phrases¶

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.

Type: MutableSequence[str]

class google.cloud.videointelligence_v1p3beta1.types.SpeechRecognitionAlternative(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Alternative hypotheses (a.k.a. n-best list).

transcript¶

Transcript text representing the words that the user spoke.

Type: str

confidence¶

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.

Type: float

words¶

Output only. A list of word-specific information for each recognized word. Note: When enable_speaker_diarization is set to true, you will see all the words from the beginning of the audio.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.WordInfo]

class google.cloud.videointelligence_v1p3beta1.types.SpeechTranscription(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A speech recognition result corresponding to a portion of the audio.

alternatives¶

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.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.SpeechRecognitionAlternative]

language_code¶

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.

Type: str

class google.cloud.videointelligence_v1p3beta1.types.SpeechTranscriptionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for SPEECH_TRANSCRIPTION.

language_code¶

Required. 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.

Type: str

max_alternatives¶

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.

Type: int

filter_profanity¶

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.

Type: bool

speech_contexts¶

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

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.SpeechContext]

enable_automatic_punctuation¶

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.”.

Type: bool

audio_tracks¶

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

Type: MutableSequence[int]

enable_speaker_diarization¶

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 response. This is done in order to improve our speaker tags as our models learn to identify the speakers in the conversation over time.

Type: bool

diarization_speaker_count¶

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.

Type: int

enable_word_confidence¶

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.

Type: bool

class google.cloud.videointelligence_v1p3beta1.types.StreamingAnnotateVideoRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

The top-level message sent by the client for the StreamingAnnotateVideo method. Multiple StreamingAnnotateVideoRequest messages are sent. The first message must only contain a StreamingVideoConfig message. All subsequent messages must only contain input_content data.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

video_config¶

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

This field is a member of oneof streaming_request.

Type: google.cloud.videointelligence_v1p3beta1.types.StreamingVideoConfig

input_content¶

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).

This field is a member of oneof streaming_request.

Type: bytes

class google.cloud.videointelligence_v1p3beta1.types.StreamingAnnotateVideoResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

StreamingAnnotateVideoResponse is the only message returned to the client by StreamingAnnotateVideo. A series of zero or more StreamingAnnotateVideoResponse messages are streamed back to the client.

error¶

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

Type: google.rpc.status_pb2.Status

annotation_results¶

Streaming annotation results.

Type: google.cloud.videointelligence_v1p3beta1.types.StreamingVideoAnnotationResults

annotation_results_uri¶

Google Cloud Storage(GCS) URI that stores annotation results of one streaming session in JSON format. It is the annotation_result_storage_directory from the request followed by ‘/cloud_project_number-session_id’.

Type: str

class google.cloud.videointelligence_v1p3beta1.types.StreamingAutomlActionRecognitionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for STREAMING_AUTOML_ACTION_RECOGNITION.

model_name¶

Resource name of AutoML model. Format: projects/{project_id}/locations/{location_id}/models/{model_id}

Type: str

class google.cloud.videointelligence_v1p3beta1.types.StreamingAutomlClassificationConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for STREAMING_AUTOML_CLASSIFICATION.

model_name¶

Resource name of AutoML model. Format: projects/{project_number}/locations/{location_id}/models/{model_id}

Type: str

class google.cloud.videointelligence_v1p3beta1.types.StreamingAutomlObjectTrackingConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for STREAMING_AUTOML_OBJECT_TRACKING.

model_name¶

Resource name of AutoML model. Format: projects/{project_id}/locations/{location_id}/models/{model_id}

Type: str

class google.cloud.videointelligence_v1p3beta1.types.StreamingExplicitContentDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for STREAMING_EXPLICIT_CONTENT_DETECTION.

class google.cloud.videointelligence_v1p3beta1.types.StreamingFeature(value)[source]¶

Bases: proto.enums.Enum

Streaming video annotation feature.

Values:

STREAMING_FEATURE_UNSPECIFIED (0):: Unspecified.
STREAMING_LABEL_DETECTION (1):: Label detection. Detect objects, such as dog or flower.
STREAMING_SHOT_CHANGE_DETECTION (2):: Shot change detection.
STREAMING_EXPLICIT_CONTENT_DETECTION (3):: Explicit content detection.
STREAMING_OBJECT_TRACKING (4):: Object detection and tracking.
STREAMING_AUTOML_ACTION_RECOGNITION (23):: Action recognition based on AutoML model.
STREAMING_AUTOML_CLASSIFICATION (21):: Video classification based on AutoML model.
STREAMING_AUTOML_OBJECT_TRACKING (22):: Object detection and tracking based on AutoML model.

class google.cloud.videointelligence_v1p3beta1.types.StreamingLabelDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for STREAMING_LABEL_DETECTION.

stationary_camera¶

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.

Type: bool

class google.cloud.videointelligence_v1p3beta1.types.StreamingObjectTrackingConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for STREAMING_OBJECT_TRACKING.

class google.cloud.videointelligence_v1p3beta1.types.StreamingShotChangeDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for STREAMING_SHOT_CHANGE_DETECTION.

class google.cloud.videointelligence_v1p3beta1.types.StreamingStorageConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for streaming storage option.

enable_storage_annotation_result¶

Enable streaming storage. Default: false.

Type: bool

annotation_result_storage_directory¶

Cloud Storage 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 Cloud Storage 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 Cloud Storage write failure.

Type: str

class google.cloud.videointelligence_v1p3beta1.types.StreamingVideoAnnotationResults(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Streaming annotation results corresponding to a portion of the video that is currently being processed.

shot_annotations¶

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

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.VideoSegment]

label_annotations¶

Label annotation results.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.LabelAnnotation]

explicit_annotation¶

Explicit content annotation results.

Type: google.cloud.videointelligence_v1p3beta1.types.ExplicitContentAnnotation

object_annotations¶

Object tracking results.

Type: MutableSequence[google.cloud.videointelligence_v1p3beta1.types.ObjectTrackingAnnotation]

class google.cloud.videointelligence_v1p3beta1.types.StreamingVideoConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Provides information to the annotator that specifies how to process the request.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

shot_change_detection_config¶

Config for STREAMING_SHOT_CHANGE_DETECTION.