{ "ownerName": "Google", "canonicalName": "Cloud Video Intelligence", "mtlsRootUrl": "https://videointelligence.mtls.googleapis.com/", "basePath": "", "servicePath": "", "version": "v1beta2", "id": "videointelligence:v1beta2", "ownerDomain": "google.com", "icons": { "x32": "http://www.google.com/images/icons/product/search-32.gif", "x16": "http://www.google.com/images/icons/product/search-16.gif" }, "batchPath": "batch", "kind": "discovery#restDescription", "rootUrl": "https://videointelligence.googleapis.com/", "auth": { "oauth2": { "scopes": { "https://www.googleapis.com/auth/cloud-platform": { "description": "See, edit, configure, and delete your Google Cloud data and see the email address for your Google Account." } } } }, "title": "Cloud Video Intelligence API", "baseUrl": "https://videointelligence.googleapis.com/", "protocol": "rest", "name": "videointelligence", "version_module": true, "documentationLink": "https://cloud.google.com/video-intelligence/docs/", "revision": "20260428", "parameters": { "callback": { "type": "string", "description": "JSONP", "location": "query" }, "prettyPrint": { "default": "true", "location": "query", "type": "boolean", "description": "Returns response with indentations and line breaks." }, "alt": { "type": "string", "default": "json", "description": "Data format for response.", "location": "query", "enum": [ "json", "media", "proto" ], "enumDescriptions": [ "Responses with Content-Type of application/json", "Media download with context-dependent Content-Type", "Responses with Content-Type of application/x-protobuf" ] }, "access_token": { "location": "query", "type": "string", "description": "OAuth access token." }, "$.xgafv": { "enumDescriptions": [ "v1 error format", "v2 error format" ], "enum": [ "1", "2" ], "location": "query", "description": "V1 error format.", "type": "string" }, "key": { "type": "string", "description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.", "location": "query" }, "fields": { "type": "string", "description": "Selector specifying which fields to include in a partial response.", "location": "query" }, "upload_protocol": { "location": "query", "type": "string", "description": "Upload protocol for media (e.g. \"raw\", \"multipart\")." }, "oauth_token": { "location": "query", "type": "string", "description": "OAuth 2.0 token for the current user." }, "quotaUser": { "type": "string", "description": "Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.", "location": "query" }, "uploadType": { "type": "string", "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").", "location": "query" } }, "description": "Detects objects, explicit content, and scene changes in videos. It also specifies the region for annotation and transcribes speech to text. Supports both asynchronous API and streaming API.", "resources": { "videos": { "methods": { "annotate": { "parameters": {}, "flatPath": "v1beta2/videos:annotate", "id": "videointelligence.videos.annotate", "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "parameterOrder": [], "description": "Performs asynchronous video annotation. Progress and results can be retrieved through the `google.longrunning.Operations` interface. `Operation.metadata` contains `AnnotateVideoProgress` (progress). `Operation.response` contains `AnnotateVideoResponse` (results).", "request": { "$ref": "GoogleCloudVideointelligenceV1beta2_AnnotateVideoRequest" }, "path": "v1beta2/videos:annotate", "response": { "$ref": "GoogleLongrunning_Operation" } } } } }, "schemas": { "GoogleCloudVideointelligenceV1p3beta1_FaceFrame": { "deprecated": true, "description": "Deprecated. No effect.", "properties": { "normalizedBoundingBoxes": { "description": "Normalized Bounding boxes in a frame. There can be more than one boxes if the same face is detected in multiple locations within the current frame.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_NormalizedBoundingBox" } }, "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_FaceFrame", "type": "object" }, "GoogleCloudVideointelligenceV1_TextAnnotation": { "properties": { "version": { "description": "Feature version.", "type": "string" }, "text": { "description": "The detected text.", "type": "string" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1_TextSegment" }, "description": "All video segments where OCR detected text appears.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1_TextAnnotation", "description": "Annotations related to one detected OCR text snippet. This will contain the corresponding text, confidence value, and frame level information for each detection.", "type": "object" }, "GoogleCloudVideointelligenceV1_SpeechRecognitionAlternative": { "id": "GoogleCloudVideointelligenceV1_SpeechRecognitionAlternative", "description": "Alternative hypotheses (a.k.a. n-best list).", "type": "object", "properties": { "transcript": { "description": "Transcript text representing the words that the user spoke.", "type": "string" }, "confidence": { "description": "Output only. The confidence estimate between 0.0 and 1.0. A higher number indicates an estimated greater likelihood that the recognized words are correct. This field is set only for the top alternative. This field is not guaranteed to be accurate and users should not rely on it to be always provided. The default of 0.0 is a sentinel value indicating `confidence` was not set.", "readOnly": true, "type": "number", "format": "float" }, "words": { "items": { "$ref": "GoogleCloudVideointelligenceV1_WordInfo" }, "description": "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.", "readOnly": true, "type": "array" } } }, "GoogleCloudVideointelligenceV1beta2_Track": { "id": "GoogleCloudVideointelligenceV1beta2_Track", "description": "A track of an object instance.", "type": "object", "properties": { "segment": { "description": "Video segment of a track.", "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" }, "timestampedObjects": { "description": "The object with timestamp and attributes per frame in the track.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_TimestampedObject" } }, "attributes": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_DetectedAttribute" }, "description": "Optional. Attributes in the track level.", "type": "array" }, "confidence": { "format": "float", "description": "Optional. The confidence score of the tracked object.", "type": "number" } } }, "GoogleCloudVideointelligenceV1p1beta1_NormalizedVertex": { "properties": { "x": { "description": "X coordinate.", "type": "number", "format": "float" }, "y": { "format": "float", "description": "Y coordinate.", "type": "number" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_NormalizedVertex", "description": "A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_PersonDetectionAnnotation": { "properties": { "tracks": { "description": "The detected tracks of a person.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_Track" } }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_PersonDetectionAnnotation", "description": "Person detection annotation per video.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_LabelAnnotation": { "id": "GoogleCloudVideointelligenceV1p1beta1_LabelAnnotation", "description": "Label annotation.", "type": "object", "properties": { "entity": { "description": "Detected entity.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_Entity" }, "segments": { "description": "All video segments where a label was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_LabelSegment" } }, "categoryEntities": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_Entity" }, "description": "Common categories for the detected entity. For example, when the label is `Terrier`, the category is likely `dog`. And in some cases there might be more than one categories e.g., `Terrier` could also be a `pet`.", "type": "array" }, "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_LabelFrame" }, "description": "All video frames where a label was detected.", "type": "array" }, "version": { "description": "Feature version.", "type": "string" } } }, "GoogleCloudVideointelligenceV1_SpeechTranscription": { "id": "GoogleCloudVideointelligenceV1_SpeechTranscription", "description": "A speech recognition result corresponding to a portion of the audio.", "type": "object", "properties": { "languageCode": { "description": "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.", "readOnly": true, "type": "string" }, "alternatives": { "description": "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": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_SpeechRecognitionAlternative" } } } }, "GoogleCloudVideointelligenceV1beta2_TextDetectionConfig": { "id": "GoogleCloudVideointelligenceV1beta2_TextDetectionConfig", "description": "Config for TEXT_DETECTION.", "type": "object", "properties": { "languageHints": { "description": "Language hint can be specified if the language to be detected is known a priori. It can increase the accuracy of the detection. Language hint must be language code in BCP-47 format. Automatic language detection is performed if no hint is provided.", "type": "array", "items": { "type": "string" } }, "model": { "description": "Model to use for text detection. Supported values: \"builtin/stable\" (the default if unset) and \"builtin/latest\".", "type": "string" } } }, "GoogleCloudVideointelligenceV1p3beta1_TextFrame": { "id": "GoogleCloudVideointelligenceV1p3beta1_TextFrame", "description": "Video frame level annotation results for text annotation (OCR). Contains information regarding timestamp and bounding box locations for the frames containing detected OCR text snippets.", "type": "object", "properties": { "rotatedBoundingBox": { "description": "Bounding polygon of the detected text for this frame.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_NormalizedBoundingPoly" }, "timeOffset": { "format": "google-duration", "description": "Timestamp of this frame.", "type": "string" } } }, "GoogleCloudVideointelligenceV1_VideoAnnotationProgress": { "id": "GoogleCloudVideointelligenceV1_VideoAnnotationProgress", "description": "Annotation progress for a single video.", "type": "object", "properties": { "feature": { "description": "Specifies which feature is being tracked if the request contains more than one feature.", "type": "string", "enum": [ "FEATURE_UNSPECIFIED", "LABEL_DETECTION", "SHOT_CHANGE_DETECTION", "EXPLICIT_CONTENT_DETECTION", "FACE_DETECTION", "SPEECH_TRANSCRIPTION", "TEXT_DETECTION", "OBJECT_TRACKING", "LOGO_RECOGNITION", "PERSON_DETECTION" ], "enumDescriptions": [ "Unspecified.", "Label detection. Detect objects, such as dog or flower.", "Shot change detection.", "Explicit content detection.", "Human face detection.", "Speech transcription.", "OCR text detection and tracking.", "Object detection and tracking.", "Logo detection, tracking, and recognition.", "Person detection." ] }, "updateTime": { "description": "Time of the most recent update.", "type": "string", "format": "google-datetime" }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "startTime": { "description": "Time when the request was received.", "type": "string", "format": "google-datetime" }, "progressPercent": { "format": "int32", "description": "Approximate percentage processed thus far. Guaranteed to be 100 when fully processed.", "type": "integer" }, "segment": { "description": "Specifies which segment is being tracked if the request contains more than one segment.", "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" }, "exportStatus": { "description": "Status of exporting annotation response to user specified `output_uri`. Only set if `output_uri` is set in the request.", "$ref": "GoogleCloudVideointelligenceV1_ExportToOutputUriStatus" } } }, "GoogleCloudVideointelligenceV1p1beta1_LogoRecognitionAnnotation": { "id": "GoogleCloudVideointelligenceV1p1beta1_LogoRecognitionAnnotation", "description": "Annotation corresponding to one detected, tracked and recognized logo class.", "type": "object", "properties": { "entity": { "description": "Entity category information to specify the logo class that all the logo tracks within this LogoRecognitionAnnotation are recognized as.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_Entity" }, "segments": { "description": "All video segments where the recognized logo appears. There might be multiple instances of the same logo class appearing in one VideoSegment.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" } }, "tracks": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_Track" }, "description": "All logo tracks where the recognized logo appears. Each track corresponds to one logo instance appearing in consecutive frames.", "type": "array" } } }, "GoogleCloudVideointelligenceV1p1beta1_SpeechRecognitionAlternative": { "properties": { "words": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_WordInfo" }, "description": "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.", "readOnly": true, "type": "array" }, "transcript": { "description": "Transcript text representing the words that the user spoke.", "type": "string" }, "confidence": { "description": "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.", "readOnly": true, "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_SpeechRecognitionAlternative", "description": "Alternative hypotheses (a.k.a. n-best list).", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_ObjectTrackingFrame": { "id": "GoogleCloudVideointelligenceV1p1beta1_ObjectTrackingFrame", "description": "Video frame level annotations for object detection and tracking. This field stores per frame location, time offset, and confidence.", "type": "object", "properties": { "timeOffset": { "format": "google-duration", "description": "The timestamp of the frame in microseconds.", "type": "string" }, "normalizedBoundingBox": { "description": "The normalized bounding box location of this object track for the frame.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_NormalizedBoundingBox" } } }, "GoogleCloudVideointelligenceV1beta2_LabelFrame": { "id": "GoogleCloudVideointelligenceV1beta2_LabelFrame", "description": "Video frame level annotation results for label detection.", "type": "object", "properties": { "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string" }, "confidence": { "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number", "format": "float" } } }, "GoogleCloudVideointelligenceV1_LabelSegment": { "properties": { "segment": { "description": "Video segment where a label was detected.", "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" }, "confidence": { "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1_LabelSegment", "description": "Video segment level annotation results for label detection.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_NormalizedBoundingPoly": { "properties": { "vertices": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_NormalizedVertex" }, "description": "Normalized vertices of the bounding polygon.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1beta2_NormalizedBoundingPoly", "description": "Normalized bounding polygon for text (that might not be aligned with axis). Contains list of the corner points in clockwise order starting from top-left corner. For example, for a rectangular bounding box: When the text is horizontal it might look like: 0----1 | | 3----2 When it's clockwise rotated 180 degrees around the top-left corner it becomes: 2----3 | | 1----0 and the vertex order will still be (0, 1, 2, 3). Note that values can be less than 0, or greater than 1 due to trigonometric calculations for location of the box.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_FaceSegment": { "properties": { "segment": { "description": "Video segment where a face was detected.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_FaceSegment", "description": "Video segment level annotation results for face detection.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_ExportToOutputUriStatus": { "id": "GoogleCloudVideointelligenceV1p2beta1_ExportToOutputUriStatus", "description": "Status of exporting annotation response to user specified `output_uri`.", "type": "object", "properties": { "state": { "type": "string", "enumDescriptions": [ "Default value.", "Export succeeded.", "Export failed." ], "enum": [ "STATE_UNSPECIFIED", "SUCCEEDED", "FAILED" ], "description": "Output only. State of the `output_uri` export.", "readOnly": true }, "status": { "description": "Output only. Only set if state is FAILED.", "readOnly": true, "$ref": "GoogleRpc_Status" } } }, "GoogleCloudVideointelligenceV1_VideoSegment": { "id": "GoogleCloudVideointelligenceV1_VideoSegment", "description": "Video segment.", "type": "object", "properties": { "startTimeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the start of the segment (inclusive).", "type": "string" }, "endTimeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the end of the segment (inclusive).", "type": "string", "format": "google-duration" } } }, "GoogleCloudVideointelligenceV1beta2_ObjectTrackingFrame": { "id": "GoogleCloudVideointelligenceV1beta2_ObjectTrackingFrame", "description": "Video frame level annotations for object detection and tracking. This field stores per frame location, time offset, and confidence.", "type": "object", "properties": { "timeOffset": { "format": "google-duration", "description": "The timestamp of the frame in microseconds.", "type": "string" }, "normalizedBoundingBox": { "description": "The normalized bounding box location of this object track for the frame.", "$ref": "GoogleCloudVideointelligenceV1beta2_NormalizedBoundingBox" } } }, "GoogleCloudVideointelligenceV1p2beta1_TextSegment": { "properties": { "segment": { "description": "Video segment where a text snippet was detected.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" }, "confidence": { "description": "Confidence for the track of detected text. It is calculated as the highest over all frames where OCR detected text appears.", "type": "number", "format": "float" }, "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_TextFrame" }, "description": "Information related to the frames where OCR detected text appears.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_TextSegment", "description": "Video segment level annotation results for text detection.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_AnnotateVideoResponse": { "properties": { "annotationResults": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoAnnotationResults" }, "description": "Annotation results for all videos specified in `AnnotateVideoRequest`.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_AnnotateVideoResponse", "description": "Video annotation response. Included in the `response` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_NormalizedVertex": { "id": "GoogleCloudVideointelligenceV1p2beta1_NormalizedVertex", "description": "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.", "type": "object", "properties": { "x": { "format": "float", "description": "X coordinate.", "type": "number" }, "y": { "format": "float", "description": "Y coordinate.", "type": "number" } } }, "GoogleCloudVideointelligenceV1p2beta1_DetectedAttribute": { "properties": { "value": { "description": "Text value of the detection result. For example, the value for \"HairColor\" can be \"black\", \"blonde\", etc.", "type": "string" }, "name": { "description": "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": "string" }, "confidence": { "description": "Detected attribute confidence. Range [0, 1].", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_DetectedAttribute", "description": "A generic detected attribute represented by name in string format.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_Entity": { "id": "GoogleCloudVideointelligenceV1p3beta1_Entity", "description": "Detected entity from video analysis.", "type": "object", "properties": { "entityId": { "description": "Opaque entity ID. Some IDs may be available in [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).", "type": "string" }, "description": { "description": "Textual description, e.g., `Fixed-gear bicycle`.", "type": "string" }, "languageCode": { "description": "Language code for `description` in BCP-47 format.", "type": "string" } } }, "GoogleCloudVideointelligenceV1_AnnotateVideoProgress": { "id": "GoogleCloudVideointelligenceV1_AnnotateVideoProgress", "description": "Video annotation progress. Included in the `metadata` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object", "properties": { "annotationProgress": { "items": { "$ref": "GoogleCloudVideointelligenceV1_VideoAnnotationProgress" }, "description": "Progress metadata for all videos specified in `AnnotateVideoRequest`.", "type": "array" } } }, "GoogleCloudVideointelligenceV1p1beta1_FaceFrame": { "properties": { "normalizedBoundingBoxes": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_NormalizedBoundingBox" }, "description": "Normalized Bounding boxes in a frame. There can be more than one boxes if the same face is detected in multiple locations within the current frame.", "type": "array" }, "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_FaceFrame", "type": "object", "description": "Deprecated. No effect.", "deprecated": true }, "GoogleCloudVideointelligenceV1p2beta1_PersonDetectionAnnotation": { "properties": { "tracks": { "description": "The detected tracks of a person.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_Track" } }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_PersonDetectionAnnotation", "description": "Person detection annotation per video.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_Track": { "properties": { "confidence": { "format": "float", "description": "Optional. The confidence score of the tracked object.", "type": "number" }, "segment": { "description": "Video segment of a track.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" }, "timestampedObjects": { "description": "The object with timestamp and attributes per frame in the track.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_TimestampedObject" } }, "attributes": { "description": "Optional. Attributes in the track level.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_DetectedAttribute" } } }, "id": "GoogleCloudVideointelligenceV1p3beta1_Track", "description": "A track of an object instance.", "type": "object" }, "GoogleCloudVideointelligenceV1_FaceAnnotation": { "deprecated": true, "description": "Deprecated. No effect.", "id": "GoogleCloudVideointelligenceV1_FaceAnnotation", "type": "object", "properties": { "thumbnail": { "format": "byte", "description": "Thumbnail of a representative face view (in JPEG format).", "type": "string" }, "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1_FaceFrame" }, "description": "All video frames where a face was detected.", "type": "array" }, "segments": { "description": "All video segments where a face was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_FaceSegment" } } } }, "GoogleCloudVideointelligenceV1p3beta1_FaceDetectionAnnotation": { "id": "GoogleCloudVideointelligenceV1p3beta1_FaceDetectionAnnotation", "description": "Face detection annotation.", "type": "object", "properties": { "tracks": { "description": "The face tracks with attributes.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_Track" } }, "thumbnail": { "description": "The thumbnail of a person's face.", "type": "string", "format": "byte" }, "version": { "description": "Feature version.", "type": "string" } } }, "GoogleCloudVideointelligenceV1beta2_AnnotateVideoResponse": { "id": "GoogleCloudVideointelligenceV1beta2_AnnotateVideoResponse", "description": "Video annotation response. Included in the `response` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object", "properties": { "annotationResults": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_VideoAnnotationResults" }, "description": "Annotation results for all videos specified in `AnnotateVideoRequest`.", "type": "array" } } }, "GoogleCloudVideointelligenceV1p2beta1_SpeechRecognitionAlternative": { "properties": { "transcript": { "description": "Transcript text representing the words that the user spoke.", "type": "string" }, "confidence": { "description": "Output only. The confidence estimate between 0.0 and 1.0. A higher number indicates an estimated greater likelihood that the recognized words are correct. This field is set only for the top alternative. This field is not guaranteed to be accurate and users should not rely on it to be always provided. The default of 0.0 is a sentinel value indicating `confidence` was not set.", "readOnly": true, "type": "number", "format": "float" }, "words": { "description": "Output only. A list of word-specific information for each recognized word. Note: When `enable_speaker_diarization` is set to true, you will see all the words from the beginning of the audio.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_WordInfo" } } }, "id": "GoogleCloudVideointelligenceV1p2beta1_SpeechRecognitionAlternative", "description": "Alternative hypotheses (a.k.a. n-best list).", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_PersonDetectionAnnotation": { "properties": { "tracks": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_Track" }, "description": "The detected tracks of a person.", "type": "array" }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_PersonDetectionAnnotation", "description": "Person detection annotation per video.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_LabelSegment": { "id": "GoogleCloudVideointelligenceV1p1beta1_LabelSegment", "description": "Video segment level annotation results for label detection.", "type": "object", "properties": { "segment": { "description": "Video segment where a label was detected.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" }, "confidence": { "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number", "format": "float" } } }, "GoogleCloudVideointelligenceV1p3beta1_ExplicitContentFrame": { "properties": { "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string", "format": "google-duration" }, "pornographyLikelihood": { "description": "Likelihood of the pornography content..", "type": "string", "enumDescriptions": [ "Unspecified likelihood.", "Very unlikely.", "Unlikely.", "Possible.", "Likely.", "Very likely." ], "enum": [ "LIKELIHOOD_UNSPECIFIED", "VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY" ] } }, "id": "GoogleCloudVideointelligenceV1p3beta1_ExplicitContentFrame", "description": "Video frame level annotation results for explicit content.", "type": "object" }, "GoogleCloudVideointelligenceV1_Entity": { "id": "GoogleCloudVideointelligenceV1_Entity", "description": "Detected entity from video analysis.", "type": "object", "properties": { "languageCode": { "description": "Language code for `description` in BCP-47 format.", "type": "string" }, "entityId": { "description": "Opaque entity ID. Some IDs may be available in [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).", "type": "string" }, "description": { "description": "Textual description, e.g., `Fixed-gear bicycle`.", "type": "string" } } }, "GoogleCloudVideointelligenceV1_LabelFrame": { "properties": { "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string", "format": "google-duration" }, "confidence": { "format": "float", "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number" } }, "id": "GoogleCloudVideointelligenceV1_LabelFrame", "description": "Video frame level annotation results for label detection.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_NormalizedBoundingPoly": { "properties": { "vertices": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_NormalizedVertex" }, "description": "Normalized vertices of the bounding polygon.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_NormalizedBoundingPoly", "description": "Normalized bounding polygon for text (that might not be aligned with axis). Contains list of the corner points in clockwise order starting from top-left corner. For example, for a rectangular bounding box: When the text is horizontal it might look like: 0----1 | | 3----2 When it's clockwise rotated 180 degrees around the top-left corner it becomes: 2----3 | | 1----0 and the vertex order will still be (0, 1, 2, 3). Note that values can be less than 0, or greater than 1 due to trigonometric calculations for location of the box.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_LabelAnnotation": { "properties": { "categoryEntities": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_Entity" }, "description": "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": "array" }, "frames": { "description": "All video frames where a label was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_LabelFrame" } }, "version": { "description": "Feature version.", "type": "string" }, "entity": { "description": "Detected entity.", "$ref": "GoogleCloudVideointelligenceV1beta2_Entity" }, "segments": { "description": "All video segments where a label was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_LabelSegment" } } }, "id": "GoogleCloudVideointelligenceV1beta2_LabelAnnotation", "description": "Label annotation.", "type": "object" }, "GoogleCloudVideointelligenceV1_FaceFrame": { "description": "Deprecated. No effect.", "deprecated": true, "properties": { "normalizedBoundingBoxes": { "items": { "$ref": "GoogleCloudVideointelligenceV1_NormalizedBoundingBox" }, "description": "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.", "type": "array" }, "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string", "format": "google-duration" } }, "id": "GoogleCloudVideointelligenceV1_FaceFrame", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_ExplicitContentAnnotation": { "id": "GoogleCloudVideointelligenceV1p1beta1_ExplicitContentAnnotation", "description": "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.", "type": "object", "properties": { "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_ExplicitContentFrame" }, "description": "All video frames where explicit content was detected.", "type": "array" }, "version": { "description": "Feature version.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p2beta1_FaceSegment": { "properties": { "segment": { "description": "Video segment where a face was detected.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_FaceSegment", "description": "Video segment level annotation results for face detection.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_SpeechTranscriptionConfig": { "properties": { "speechContexts": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_SpeechContext" }, "description": "Optional. A means to provide context to assist the speech recognition.", "type": "array" }, "enableSpeakerDiarization": { "description": "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": "boolean" }, "enableWordConfidence": { "description": "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": "boolean" }, "filterProfanity": { "description": "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": "boolean" }, "enableAutomaticPunctuation": { "description": "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": "boolean" }, "maxAlternatives": { "format": "int32", "description": "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": "integer" }, "audioOutputUriPrefix": { "description": "Optional. Legacy field. This field must be a Cloud Storage URI prefix. (e.g., `gs://bucket/path/`).", "type": "string" }, "languageCode": { "description": "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.", "type": "string" }, "diarizationSpeakerCount": { "description": "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": "integer", "format": "int32" }, "audioTracks": { "description": "Optional. For file formats, such as MXF or MKV, supporting multiple audio tracks, specify up to two tracks. Default: track 0.", "type": "array", "items": { "format": "int32", "type": "integer" } } }, "id": "GoogleCloudVideointelligenceV1beta2_SpeechTranscriptionConfig", "description": "Config for SPEECH_TRANSCRIPTION.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_VideoAnnotationResults": { "properties": { "textAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_TextAnnotation" }, "description": "OCR text detection and tracking. Annotations for list of detected text snippets. Each will have list of frame information associated with it.", "type": "array" }, "error": { "description": "If set, indicates an error. Note that for a single `AnnotateVideoRequest` some videos may succeed and some may fail.", "$ref": "GoogleRpc_Status" }, "segmentPresenceLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LabelAnnotation" }, "description": "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.", "type": "array" }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "faceDetectionAnnotations": { "description": "Face detection annotations.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_FaceDetectionAnnotation" } }, "frameLabelAnnotations": { "description": "Label annotations on frame level. There is exactly one element for each unique label.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LabelAnnotation" } }, "logoRecognitionAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LogoRecognitionAnnotation" }, "description": "Annotations for list of logos detected, tracked and recognized in video.", "type": "array" }, "segmentLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LabelAnnotation" }, "description": "Topical label annotations on video level or user-specified segment level. There is exactly one element for each unique label.", "type": "array" }, "explicitAnnotation": { "description": "Explicit content annotation.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_ExplicitContentAnnotation" }, "speechTranscriptions": { "description": "Speech transcription.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_SpeechTranscription" } }, "shotAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" }, "description": "Shot annotations. Each shot is represented as a video segment.", "type": "array" }, "shotPresenceLabelAnnotations": { "description": "Presence label annotations on shot level. There is exactly one element for each unique label. Compared to the existing topical `shot_label_annotations`, this field presents more fine-grained, shot-level labels detected in video content and is made available only when the client sets `LabelDetectionConfig.model` to \"builtin/latest\" in the request.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LabelAnnotation" } }, "faceAnnotations": { "description": "Deprecated. Please use `face_detection_annotations` instead.", "type": "array", "deprecated": true, "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_FaceAnnotation" } }, "objectAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_ObjectTrackingAnnotation" }, "description": "Annotations for list of objects detected and tracked in video.", "type": "array" }, "shotLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LabelAnnotation" }, "description": "Topical label annotations on shot level. There is exactly one element for each unique label.", "type": "array" }, "celebrityRecognitionAnnotations": { "description": "Celebrity recognition annotations.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_CelebrityRecognitionAnnotation" }, "personDetectionAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_PersonDetectionAnnotation" }, "description": "Person detection annotations.", "type": "array" }, "segment": { "description": "Video segment on which the annotation is run.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_VideoAnnotationResults", "description": "Annotation results for a single video.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_VideoAnnotationProgress": { "properties": { "progressPercent": { "format": "int32", "description": "Approximate percentage processed thus far. Guaranteed to be 100 when fully processed.", "type": "integer" }, "segment": { "description": "Specifies which segment is being tracked if the request contains more than one segment.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" }, "exportStatus": { "description": "Status of exporting annotation response to user specified `output_uri`. Only set if `output_uri` is set in the request.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_ExportToOutputUriStatus" }, "startTime": { "description": "Time when the request was received.", "type": "string", "format": "google-datetime" }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Time of the most recent update.", "type": "string" }, "feature": { "enumDescriptions": [ "Unspecified.", "Label detection. Detect objects, such as dog or flower.", "Shot change detection.", "Explicit content detection.", "Human face detection.", "Speech transcription.", "OCR text detection and tracking.", "Object detection and tracking.", "Logo detection, tracking, and recognition.", "Person detection." ], "enum": [ "FEATURE_UNSPECIFIED", "LABEL_DETECTION", "SHOT_CHANGE_DETECTION", "EXPLICIT_CONTENT_DETECTION", "FACE_DETECTION", "SPEECH_TRANSCRIPTION", "TEXT_DETECTION", "OBJECT_TRACKING", "LOGO_RECOGNITION", "PERSON_DETECTION" ], "description": "Specifies which feature is being tracked if the request contains more than one feature.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_VideoAnnotationProgress", "description": "Annotation progress for a single video.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_ObjectTrackingConfig": { "properties": { "model": { "description": "Model to use for object tracking. Supported values: \"builtin/stable\" (the default if unset) and \"builtin/latest\".", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_ObjectTrackingConfig", "description": "Config for OBJECT_TRACKING.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_AnnotateVideoProgress": { "id": "GoogleCloudVideointelligenceV1beta2_AnnotateVideoProgress", "description": "Video annotation progress. Included in the `metadata` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object", "properties": { "annotationProgress": { "description": "Progress metadata for all videos specified in `AnnotateVideoRequest`.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_VideoAnnotationProgress" } } } }, "GoogleCloudVideointelligenceV1_NormalizedBoundingBox": { "id": "GoogleCloudVideointelligenceV1_NormalizedBoundingBox", "description": "Normalized bounding box. The normalized vertex coordinates are relative to the original image. Range: [0, 1].", "type": "object", "properties": { "right": { "format": "float", "description": "Right X coordinate.", "type": "number" }, "left": { "description": "Left X coordinate.", "type": "number", "format": "float" }, "top": { "format": "float", "description": "Top Y coordinate.", "type": "number" }, "bottom": { "format": "float", "description": "Bottom Y coordinate.", "type": "number" } } }, "GoogleCloudVideointelligenceV1beta2_TextAnnotation": { "id": "GoogleCloudVideointelligenceV1beta2_TextAnnotation", "description": "Annotations related to one detected OCR text snippet. This will contain the corresponding text, confidence value, and frame level information for each detection.", "type": "object", "properties": { "version": { "description": "Feature version.", "type": "string" }, "text": { "description": "The detected text.", "type": "string" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_TextSegment" }, "description": "All video segments where OCR detected text appears.", "type": "array" } } }, "GoogleCloudVideointelligenceV1p3beta1_AnnotateVideoResponse": { "id": "GoogleCloudVideointelligenceV1p3beta1_AnnotateVideoResponse", "description": "Video annotation response. Included in the `response` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object", "properties": { "annotationResults": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoAnnotationResults" }, "description": "Annotation results for all videos specified in `AnnotateVideoRequest`.", "type": "array" } } }, "GoogleCloudVideointelligenceV1beta2_NormalizedVertex": { "properties": { "y": { "description": "Y coordinate.", "type": "number", "format": "float" }, "x": { "description": "X coordinate.", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1beta2_NormalizedVertex", "description": "A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.", "type": "object" }, "GoogleCloudVideointelligenceV1_TimestampedObject": { "properties": { "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this object.", "type": "string", "format": "google-duration" }, "attributes": { "items": { "$ref": "GoogleCloudVideointelligenceV1_DetectedAttribute" }, "description": "Optional. The attributes of the object in the bounding box.", "type": "array" }, "landmarks": { "description": "Optional. The detected landmarks.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_DetectedLandmark" } }, "normalizedBoundingBox": { "description": "Normalized Bounding box in a frame, where the object is located.", "$ref": "GoogleCloudVideointelligenceV1_NormalizedBoundingBox" } }, "id": "GoogleCloudVideointelligenceV1_TimestampedObject", "description": "For tracking related features. An object at time_offset with attributes, and located with normalized_bounding_box.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_TextFrame": { "properties": { "rotatedBoundingBox": { "description": "Bounding polygon of the detected text for this frame.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_NormalizedBoundingPoly" }, "timeOffset": { "format": "google-duration", "description": "Timestamp of this frame.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_TextFrame", "description": "Video frame level annotation results for text annotation (OCR). Contains information regarding timestamp and bounding box locations for the frames containing detected OCR text snippets.", "type": "object" }, "GoogleCloudVideointelligenceV1_TextFrame": { "properties": { "rotatedBoundingBox": { "description": "Bounding polygon of the detected text for this frame.", "$ref": "GoogleCloudVideointelligenceV1_NormalizedBoundingPoly" }, "timeOffset": { "description": "Timestamp of this frame.", "type": "string", "format": "google-duration" } }, "id": "GoogleCloudVideointelligenceV1_TextFrame", "description": "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.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_VideoSegment": { "properties": { "startTimeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the start of the segment (inclusive).", "type": "string", "format": "google-duration" }, "endTimeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the end of the segment (inclusive).", "type": "string", "format": "google-duration" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment", "description": "Video segment.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_ExplicitContentFrame": { "properties": { "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string", "format": "google-duration" }, "pornographyLikelihood": { "enum": [ "LIKELIHOOD_UNSPECIFIED", "VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY" ], "enumDescriptions": [ "Unspecified likelihood.", "Very unlikely.", "Unlikely.", "Possible.", "Likely.", "Very likely." ], "description": "Likelihood of the pornography content..", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_ExplicitContentFrame", "description": "Video frame level annotation results for explicit content.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_AnnotateVideoResponse": { "properties": { "annotationResults": { "description": "Annotation results for all videos specified in `AnnotateVideoRequest`.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoAnnotationResults" } } }, "id": "GoogleCloudVideointelligenceV1p1beta1_AnnotateVideoResponse", "description": "Video annotation response. Included in the `response` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_VideoAnnotationProgress": { "properties": { "feature": { "enum": [ "FEATURE_UNSPECIFIED", "LABEL_DETECTION", "SHOT_CHANGE_DETECTION", "EXPLICIT_CONTENT_DETECTION", "FACE_DETECTION", "SPEECH_TRANSCRIPTION", "TEXT_DETECTION", "OBJECT_TRACKING", "LOGO_RECOGNITION", "CELEBRITY_RECOGNITION", "PERSON_DETECTION" ], "enumDescriptions": [ "Unspecified.", "Label detection. Detect objects, such as dog or flower.", "Shot change detection.", "Explicit content detection.", "Human face detection.", "Speech transcription.", "OCR text detection and tracking.", "Object detection and tracking.", "Logo detection, tracking, and recognition.", "Celebrity recognition.", "Person detection." ], "description": "Specifies which feature is being tracked if the request contains more than one feature.", "type": "string" }, "updateTime": { "description": "Time of the most recent update.", "type": "string", "format": "google-datetime" }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "startTime": { "description": "Time when the request was received.", "type": "string", "format": "google-datetime" }, "progressPercent": { "format": "int32", "description": "Approximate percentage processed thus far. Guaranteed to be 100 when fully processed.", "type": "integer" }, "segment": { "description": "Specifies which segment is being tracked if the request contains more than one segment.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" }, "exportStatus": { "description": "Status of exporting annotation response to user specified `output_uri`. Only set if `output_uri` is set in the request.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_ExportToOutputUriStatus" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_VideoAnnotationProgress", "description": "Annotation progress for a single video.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_ExplicitContentFrame": { "id": "GoogleCloudVideointelligenceV1p1beta1_ExplicitContentFrame", "description": "Video frame level annotation results for explicit content.", "type": "object", "properties": { "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string" }, "pornographyLikelihood": { "description": "Likelihood of the pornography content..", "type": "string", "enumDescriptions": [ "Unspecified likelihood.", "Very unlikely.", "Unlikely.", "Possible.", "Likely.", "Very likely." ], "enum": [ "LIKELIHOOD_UNSPECIFIED", "VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY" ] } } }, "GoogleCloudVideointelligenceV1_LogoRecognitionAnnotation": { "properties": { "entity": { "description": "Entity category information to specify the logo class that all the logo tracks within this LogoRecognitionAnnotation are recognized as.", "$ref": "GoogleCloudVideointelligenceV1_Entity" }, "segments": { "description": "All video segments where the recognized logo appears. There might be multiple instances of the same logo class appearing in one VideoSegment.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" } }, "tracks": { "items": { "$ref": "GoogleCloudVideointelligenceV1_Track" }, "description": "All logo tracks where the recognized logo appears. Each track corresponds to one logo instance appearing in consecutive frames.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1_LogoRecognitionAnnotation", "description": "Annotation corresponding to one detected, tracked and recognized logo class.", "type": "object" }, "GoogleCloudVideointelligenceV1_VideoAnnotationResults": { "id": "GoogleCloudVideointelligenceV1_VideoAnnotationResults", "description": "Annotation results for a single video.", "type": "object", "properties": { "shotLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1_LabelAnnotation" }, "description": "Topical label annotations on shot level. There is exactly one element for each unique label.", "type": "array" }, "objectAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1_ObjectTrackingAnnotation" }, "description": "Annotations for list of objects detected and tracked in video.", "type": "array" }, "shotPresenceLabelAnnotations": { "description": "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.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_LabelAnnotation" } }, "faceAnnotations": { "description": "Deprecated. Please use `face_detection_annotations` instead.", "type": "array", "deprecated": true, "items": { "$ref": "GoogleCloudVideointelligenceV1_FaceAnnotation" } }, "segment": { "description": "Video segment on which the annotation is run.", "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" }, "personDetectionAnnotations": { "description": "Person detection annotations.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_PersonDetectionAnnotation" } }, "faceDetectionAnnotations": { "description": "Face detection annotations.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_FaceDetectionAnnotation" } }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "segmentPresenceLabelAnnotations": { "description": "Presence label annotations on video level or user-specified segment level. There is exactly one element for each unique label. Compared to the existing topical `segment_label_annotations`, this field presents more fine-grained, segment-level labels detected in video content and is made available only when the client sets `LabelDetectionConfig.model` to \"builtin/latest\" in the request.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_LabelAnnotation" } }, "textAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1_TextAnnotation" }, "description": "OCR text detection and tracking. Annotations for list of detected text snippets. Each will have list of frame information associated with it.", "type": "array" }, "error": { "description": "If set, indicates an error. Note that for a single `AnnotateVideoRequest` some videos may succeed and some may fail.", "$ref": "GoogleRpc_Status" }, "shotAnnotations": { "description": "Shot annotations. Each shot is represented as a video segment.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" } }, "segmentLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1_LabelAnnotation" }, "description": "Topical label annotations on video level or user-specified segment level. There is exactly one element for each unique label.", "type": "array" }, "explicitAnnotation": { "description": "Explicit content annotation.", "$ref": "GoogleCloudVideointelligenceV1_ExplicitContentAnnotation" }, "speechTranscriptions": { "description": "Speech transcription.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_SpeechTranscription" } }, "frameLabelAnnotations": { "description": "Label annotations on frame level. There is exactly one element for each unique label.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_LabelAnnotation" } }, "logoRecognitionAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1_LogoRecognitionAnnotation" }, "description": "Annotations for list of logos detected, tracked and recognized in video.", "type": "array" } } }, "GoogleCloudVideointelligenceV1_FaceDetectionAnnotation": { "id": "GoogleCloudVideointelligenceV1_FaceDetectionAnnotation", "description": "Face detection annotation.", "type": "object", "properties": { "tracks": { "description": "The face tracks with attributes.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_Track" } }, "thumbnail": { "format": "byte", "description": "The thumbnail of a person's face.", "type": "string" }, "version": { "description": "Feature version.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p3beta1_ExportToOutputUriStatus": { "properties": { "status": { "description": "Output only. Only set if state is FAILED.", "readOnly": true, "$ref": "GoogleRpc_Status" }, "state": { "type": "string", "description": "Output only. State of the `output_uri` export.", "readOnly": true, "enumDescriptions": [ "Default value.", "Export succeeded.", "Export failed." ], "enum": [ "STATE_UNSPECIFIED", "SUCCEEDED", "FAILED" ] } }, "id": "GoogleCloudVideointelligenceV1p3beta1_ExportToOutputUriStatus", "description": "Status of exporting annotation response to user specified `output_uri`.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_NormalizedBoundingPoly": { "id": "GoogleCloudVideointelligenceV1p3beta1_NormalizedBoundingPoly", "description": "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 trigonometric calculations for location of the box.", "type": "object", "properties": { "vertices": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_NormalizedVertex" }, "description": "Normalized vertices of the bounding polygon.", "type": "array" } } }, "GoogleCloudVideointelligenceV1p2beta1_AnnotateVideoProgress": { "id": "GoogleCloudVideointelligenceV1p2beta1_AnnotateVideoProgress", "description": "Video annotation progress. Included in the `metadata` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object", "properties": { "annotationProgress": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoAnnotationProgress" }, "description": "Progress metadata for all videos specified in `AnnotateVideoRequest`.", "type": "array" } } }, "GoogleCloudVideointelligenceV1p2beta1_FaceAnnotation": { "deprecated": true, "description": "Deprecated. No effect.", "properties": { "segments": { "description": "All video segments where a face was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_FaceSegment" } }, "frames": { "description": "All video frames where a face was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_FaceFrame" } }, "thumbnail": { "description": "Thumbnail of a representative face view (in JPEG format).", "type": "string", "format": "byte" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_FaceAnnotation", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_SpeechTranscription": { "id": "GoogleCloudVideointelligenceV1beta2_SpeechTranscription", "description": "A speech recognition result corresponding to a portion of the audio.", "type": "object", "properties": { "languageCode": { "description": "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.", "readOnly": true, "type": "string" }, "alternatives": { "description": "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": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_SpeechRecognitionAlternative" } } } }, "GoogleCloudVideointelligenceV1p2beta1_DetectedLandmark": { "properties": { "name": { "description": "The name of this landmark, for example, left_hand, right_shoulder.", "type": "string" }, "point": { "description": "The 2D point of the detected landmark using the normalized image coordinate system. The normalized coordinates have the range from 0 to 1.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_NormalizedVertex" }, "confidence": { "description": "The confidence score of the detected landmark. Range [0, 1].", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_DetectedLandmark", "description": "A generic detected landmark represented by name in string format and a 2D location.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_TextAnnotation": { "properties": { "text": { "description": "The detected text.", "type": "string" }, "version": { "description": "Feature version.", "type": "string" }, "segments": { "description": "All video segments where OCR detected text appears.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_TextSegment" } } }, "id": "GoogleCloudVideointelligenceV1p2beta1_TextAnnotation", "description": "Annotations related to one detected OCR text snippet. This will contain the corresponding text, confidence value, and frame level information for each detection.", "type": "object" }, "GoogleCloudVideointelligenceV1_FaceSegment": { "id": "GoogleCloudVideointelligenceV1_FaceSegment", "description": "Video segment level annotation results for face detection.", "type": "object", "properties": { "segment": { "description": "Video segment where a face was detected.", "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" } } }, "GoogleCloudVideointelligenceV1p3beta1_TimestampedObject": { "id": "GoogleCloudVideointelligenceV1p3beta1_TimestampedObject", "description": "For tracking related features. An object at time_offset with attributes, and located with normalized_bounding_box.", "type": "object", "properties": { "normalizedBoundingBox": { "description": "Normalized Bounding box in a frame, where the object is located.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_NormalizedBoundingBox" }, "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this object.", "type": "string", "format": "google-duration" }, "attributes": { "description": "Optional. The attributes of the object in the bounding box.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_DetectedAttribute" } }, "landmarks": { "description": "Optional. The detected landmarks.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_DetectedLandmark" } } } }, "GoogleCloudVideointelligenceV1p3beta1_TextAnnotation": { "properties": { "segments": { "description": "All video segments where OCR detected text appears.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_TextSegment" } }, "text": { "description": "The detected text.", "type": "string" }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_TextAnnotation", "description": "Annotations related to one detected OCR text snippet. This will contain the corresponding text, confidence value, and frame level information for each detection.", "type": "object" }, "GoogleCloudVideointelligenceV1_ExportToOutputUriStatus": { "properties": { "status": { "description": "Output only. Only set if state is FAILED.", "readOnly": true, "$ref": "GoogleRpc_Status" }, "state": { "description": "Output only. State of the `output_uri` export.", "readOnly": true, "enumDescriptions": [ "Default value.", "Export succeeded.", "Export failed." ], "enum": [ "STATE_UNSPECIFIED", "SUCCEEDED", "FAILED" ], "type": "string" } }, "id": "GoogleCloudVideointelligenceV1_ExportToOutputUriStatus", "description": "Status of exporting annotation response to user specified `output_uri`.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_DetectedLandmark": { "properties": { "name": { "description": "The name of this landmark, for example, left_hand, right_shoulder.", "type": "string" }, "point": { "description": "The 2D point of the detected landmark using the normalized image coordinate system. The normalized coordinates have the range from 0 to 1.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_NormalizedVertex" }, "confidence": { "description": "The confidence score of the detected landmark. Range [0, 1].", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_DetectedLandmark", "description": "A generic detected landmark represented by name in string format and a 2D location.", "type": "object" }, "GoogleCloudVideointelligenceV1_DetectedLandmark": { "properties": { "name": { "description": "The name of this landmark, for example, left_hand, right_shoulder.", "type": "string" }, "point": { "description": "The 2D point of the detected landmark using the normalized image coordinate system. The normalized coordinates have the range from 0 to 1.", "$ref": "GoogleCloudVideointelligenceV1_NormalizedVertex" }, "confidence": { "description": "The confidence score of the detected landmark. Range [0, 1].", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1_DetectedLandmark", "description": "A generic detected landmark represented by name in string format and a 2D location.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_FaceFrame": { "description": "Deprecated. No effect.", "deprecated": true, "id": "GoogleCloudVideointelligenceV1p2beta1_FaceFrame", "type": "object", "properties": { "normalizedBoundingBoxes": { "description": "Normalized Bounding boxes in a frame. There can be more than one boxes if the same face is detected in multiple locations within the current frame.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_NormalizedBoundingBox" } }, "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string", "format": "google-duration" } } }, "GoogleCloudVideointelligenceV1p3beta1_ObjectTrackingAnnotation": { "id": "GoogleCloudVideointelligenceV1p3beta1_ObjectTrackingAnnotation", "description": "Annotations corresponding to one tracked object.", "type": "object", "properties": { "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_ObjectTrackingFrame" }, "description": "Information corresponding to all frames where this object track appears. Non-streaming batch mode: it may be one or multiple ObjectTrackingFrame messages in frames. Streaming mode: it can only be one ObjectTrackingFrame message in frames.", "type": "array" }, "version": { "description": "Feature version.", "type": "string" }, "trackId": { "format": "int64", "description": "Streaming mode ONLY. In streaming mode, we do not know the end time of a tracked object before it is completed. Hence, there is no VideoSegment info returned. Instead, we provide a unique identifiable integer track_id so that the customers can correlate the results of the ongoing ObjectTrackAnnotation of the same track_id over time.", "type": "string" }, "entity": { "description": "Entity to specify the object category that this track is labeled as.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_Entity" }, "confidence": { "description": "Object category's labeling confidence of this track.", "type": "number", "format": "float" }, "segment": { "description": "Non-streaming batch mode ONLY. Each object track corresponds to one video segment where it appears.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" } } }, "GoogleCloudVideointelligenceV1p3beta1_NormalizedVertex": { "id": "GoogleCloudVideointelligenceV1p3beta1_NormalizedVertex", "description": "A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.", "type": "object", "properties": { "y": { "description": "Y coordinate.", "type": "number", "format": "float" }, "x": { "description": "X coordinate.", "type": "number", "format": "float" } } }, "GoogleCloudVideointelligenceV1p1beta1_ObjectTrackingAnnotation": { "properties": { "version": { "description": "Feature version.", "type": "string" }, "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_ObjectTrackingFrame" }, "description": "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": "array" }, "segment": { "description": "Non-streaming batch mode ONLY. Each object track corresponds to one video segment where it appears.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" }, "trackId": { "description": "Streaming mode ONLY. In streaming mode, we do not know the end time of a tracked object before it is completed. Hence, there is no VideoSegment info returned. Instead, we provide a unique identifiable integer track_id so that the customers can correlate the results of the ongoing ObjectTrackAnnotation of the same track_id over time.", "type": "string", "format": "int64" }, "entity": { "description": "Entity to specify the object category that this track is labeled as.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_Entity" }, "confidence": { "description": "Object category's labeling confidence of this track.", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_ObjectTrackingAnnotation", "description": "Annotations corresponding to one tracked object.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_SpeechRecognitionAlternative": { "id": "GoogleCloudVideointelligenceV1p3beta1_SpeechRecognitionAlternative", "description": "Alternative hypotheses (a.k.a. n-best list).", "type": "object", "properties": { "words": { "description": "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.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_WordInfo" } }, "transcript": { "description": "Transcript text representing the words that the user spoke.", "type": "string" }, "confidence": { "format": "float", "description": "Output only. The confidence estimate between 0.0 and 1.0. A higher number indicates an estimated greater likelihood that the recognized words are correct. This field is set only for the top alternative. This field is not guaranteed to be accurate and users should not rely on it to be always provided. The default of 0.0 is a sentinel value indicating `confidence` was not set.", "readOnly": true, "type": "number" } } }, "GoogleCloudVideointelligenceV1beta2_FaceSegment": { "properties": { "segment": { "description": "Video segment where a face was detected.", "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" } }, "id": "GoogleCloudVideointelligenceV1beta2_FaceSegment", "description": "Video segment level annotation results for face detection.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_Celebrity": { "properties": { "description": { "description": "Textual description of additional information about the celebrity, if applicable.", "type": "string" }, "name": { "description": "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": "string" }, "displayName": { "description": "The celebrity name.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_Celebrity", "description": "Celebrity definition.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_NormalizedBoundingPoly": { "id": "GoogleCloudVideointelligenceV1p1beta1_NormalizedBoundingPoly", "description": "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 trigonometric calculations for location of the box.", "type": "object", "properties": { "vertices": { "description": "Normalized vertices of the bounding polygon.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_NormalizedVertex" } } } }, "GoogleCloudVideointelligenceV1beta2_WordInfo": { "id": "GoogleCloudVideointelligenceV1beta2_WordInfo", "description": "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`.", "type": "object", "properties": { "startTime": { "description": "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.", "type": "string", "format": "google-duration" }, "confidence": { "description": "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.", "readOnly": true, "type": "number", "format": "float" }, "speakerTag": { "format": "int32", "description": "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.", "readOnly": true, "type": "integer" }, "speakerLabel": { "description": "Output only. A distinct string value is assigned for every speaker within the audio. This field specifies which one of those speakers was detected to have spoken this word.", "readOnly": true, "type": "string" }, "endTime": { "description": "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.", "type": "string", "format": "google-duration" }, "word": { "description": "The word corresponding to this set of information.", "type": "string" } } }, "GoogleCloudVideointelligenceV1_DetectedAttribute": { "properties": { "value": { "description": "Text value of the detection result. For example, the value for \"HairColor\" can be \"black\", \"blonde\", etc.", "type": "string" }, "name": { "description": "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": "string" }, "confidence": { "format": "float", "description": "Detected attribute confidence. Range [0, 1].", "type": "number" } }, "id": "GoogleCloudVideointelligenceV1_DetectedAttribute", "description": "A generic detected attribute represented by name in string format.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_Entity": { "properties": { "languageCode": { "description": "Language code for `description` in BCP-47 format.", "type": "string" }, "entityId": { "description": "Opaque entity ID. Some IDs may be available in [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).", "type": "string" }, "description": { "description": "Textual description, e.g., `Fixed-gear bicycle`.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_Entity", "description": "Detected entity from video analysis.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_SpeechTranscription": { "properties": { "alternatives": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_SpeechRecognitionAlternative" }, "description": "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": "array" }, "languageCode": { "description": "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.", "readOnly": true, "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_SpeechTranscription", "description": "A speech recognition result corresponding to a portion of the audio.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_LabelAnnotation": { "id": "GoogleCloudVideointelligenceV1p3beta1_LabelAnnotation", "description": "Label annotation.", "type": "object", "properties": { "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LabelFrame" }, "description": "All video frames where a label was detected.", "type": "array" }, "categoryEntities": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_Entity" }, "description": "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": "array" }, "version": { "description": "Feature version.", "type": "string" }, "entity": { "description": "Detected entity.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_Entity" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LabelSegment" }, "description": "All video segments where a label was detected.", "type": "array" } } }, "GoogleCloudVideointelligenceV1beta2_TimestampedObject": { "properties": { "normalizedBoundingBox": { "description": "Normalized Bounding box in a frame, where the object is located.", "$ref": "GoogleCloudVideointelligenceV1beta2_NormalizedBoundingBox" }, "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this object.", "type": "string", "format": "google-duration" }, "attributes": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_DetectedAttribute" }, "description": "Optional. The attributes of the object in the bounding box.", "type": "array" }, "landmarks": { "description": "Optional. The detected landmarks.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_DetectedLandmark" } } }, "id": "GoogleCloudVideointelligenceV1beta2_TimestampedObject", "description": "For tracking related features. An object at time_offset with attributes, and located with normalized_bounding_box.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_CelebrityTrack": { "id": "GoogleCloudVideointelligenceV1p3beta1_CelebrityTrack", "description": "The annotation result of a celebrity face track. RecognizedCelebrity field could be empty if the face track does not have any matched celebrities.", "type": "object", "properties": { "celebrities": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_RecognizedCelebrity" }, "description": "Top N match of the celebrities for the face in this track.", "type": "array" }, "faceTrack": { "description": "A track of a person's face.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_Track" } } }, "GoogleCloudVideointelligenceV1p2beta1_VideoSegment": { "id": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment", "description": "Video segment.", "type": "object", "properties": { "startTimeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the start of the segment (inclusive).", "type": "string" }, "endTimeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the end of the segment (inclusive).", "type": "string", "format": "google-duration" } } }, "GoogleCloudVideointelligenceV1p3beta1_FaceAnnotation": { "properties": { "thumbnail": { "format": "byte", "description": "Thumbnail of a representative face view (in JPEG format).", "type": "string" }, "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_FaceFrame" }, "description": "All video frames where a face was detected.", "type": "array" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_FaceSegment" }, "description": "All video segments where a face was detected.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_FaceAnnotation", "type": "object", "description": "Deprecated. No effect.", "deprecated": true }, "GoogleCloudVideointelligenceV1_PersonDetectionAnnotation": { "properties": { "tracks": { "description": "The detected tracks of a person.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_Track" } }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1_PersonDetectionAnnotation", "description": "Person detection annotation per video.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_TextSegment": { "properties": { "confidence": { "format": "float", "description": "Confidence for the track of detected text. It is calculated as the highest over all frames where OCR detected text appears.", "type": "number" }, "frames": { "description": "Information related to the frames where OCR detected text appears.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_TextFrame" } }, "segment": { "description": "Video segment where a text snippet was detected.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_TextSegment", "description": "Video segment level annotation results for text detection.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_FaceDetectionConfig": { "id": "GoogleCloudVideointelligenceV1beta2_FaceDetectionConfig", "description": "Config for FACE_DETECTION.", "type": "object", "properties": { "includeBoundingBoxes": { "description": "Whether bounding boxes are included in the face annotation output.", "type": "boolean" }, "model": { "description": "Model to use for face detection. Supported values: \"builtin/stable\" (the default if unset) and \"builtin/latest\".", "type": "string" }, "includeAttributes": { "description": "Whether to enable face attributes detection, such as glasses, dark_glasses, mouth_open etc. Ignored if 'include_bounding_boxes' is set to false.", "type": "boolean" } } }, "GoogleCloudVideointelligenceV1p3beta1_DetectedAttribute": { "id": "GoogleCloudVideointelligenceV1p3beta1_DetectedAttribute", "description": "A generic detected attribute represented by name in string format.", "type": "object", "properties": { "name": { "description": "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": "string" }, "confidence": { "description": "Detected attribute confidence. Range [0, 1].", "type": "number", "format": "float" }, "value": { "description": "Text value of the detection result. For example, the value for \"HairColor\" can be \"black\", \"blonde\", etc.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p3beta1_AnnotateVideoProgress": { "properties": { "annotationProgress": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoAnnotationProgress" }, "description": "Progress metadata for all videos specified in `AnnotateVideoRequest`.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_AnnotateVideoProgress", "description": "Video annotation progress. Included in the `metadata` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_WordInfo": { "properties": { "endTime": { "description": "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.", "type": "string", "format": "google-duration" }, "word": { "description": "The word corresponding to this set of information.", "type": "string" }, "speakerLabel": { "description": "Output only. A distinct string value is assigned for every speaker within the audio. This field specifies which one of those speakers was detected to have spoken this word.", "readOnly": true, "type": "string" }, "speakerTag": { "format": "int32", "description": "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.", "readOnly": true, "type": "integer" }, "startTime": { "description": "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.", "type": "string", "format": "google-duration" }, "confidence": { "format": "float", "description": "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.", "readOnly": true, "type": "number" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_WordInfo", "description": "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`.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_WordInfo": { "properties": { "speakerTag": { "format": "int32", "description": "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.", "readOnly": true, "type": "integer" }, "startTime": { "format": "google-duration", "description": "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.", "type": "string" }, "confidence": { "description": "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.", "readOnly": true, "type": "number", "format": "float" }, "endTime": { "format": "google-duration", "description": "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.", "type": "string" }, "word": { "description": "The word corresponding to this set of information.", "type": "string" }, "speakerLabel": { "description": "Output only. A distinct string value is assigned for every speaker within the audio. This field specifies which one of those speakers was detected to have spoken this word.", "readOnly": true, "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_WordInfo", "description": "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`.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_ObjectTrackingAnnotation": { "id": "GoogleCloudVideointelligenceV1p2beta1_ObjectTrackingAnnotation", "description": "Annotations corresponding to one tracked object.", "type": "object", "properties": { "trackId": { "format": "int64", "description": "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.", "type": "string" }, "entity": { "description": "Entity to specify the object category that this track is labeled as.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_Entity" }, "confidence": { "format": "float", "description": "Object category's labeling confidence of this track.", "type": "number" }, "segment": { "description": "Non-streaming batch mode ONLY. Each object track corresponds to one video segment where it appears.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" }, "frames": { "description": "Information corresponding to all frames where this object track appears. Non-streaming batch mode: it may be one or multiple ObjectTrackingFrame messages in frames. Streaming mode: it can only be one ObjectTrackingFrame message in frames.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_ObjectTrackingFrame" } }, "version": { "description": "Feature version.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p1beta1_VideoSegment": { "properties": { "startTimeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the start of the segment (inclusive).", "type": "string", "format": "google-duration" }, "endTimeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the end of the segment (inclusive).", "type": "string", "format": "google-duration" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment", "description": "Video segment.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_Entity": { "id": "GoogleCloudVideointelligenceV1beta2_Entity", "description": "Detected entity from video analysis.", "type": "object", "properties": { "entityId": { "description": "Opaque entity ID. Some IDs may be available in [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).", "type": "string" }, "description": { "description": "Textual description, e.g., `Fixed-gear bicycle`.", "type": "string" }, "languageCode": { "description": "Language code for `description` in BCP-47 format.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p1beta1_Entity": { "id": "GoogleCloudVideointelligenceV1p1beta1_Entity", "description": "Detected entity from video analysis.", "type": "object", "properties": { "description": { "description": "Textual description, e.g., `Fixed-gear bicycle`.", "type": "string" }, "entityId": { "description": "Opaque entity ID. Some IDs may be available in [Google Knowledge Graph Search API](https://developers.google.com/knowledge-graph/).", "type": "string" }, "languageCode": { "description": "Language code for `description` in BCP-47 format.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p2beta1_WordInfo": { "properties": { "confidence": { "format": "float", "description": "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.", "readOnly": true, "type": "number" }, "startTime": { "description": "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.", "type": "string", "format": "google-duration" }, "speakerTag": { "description": "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.", "readOnly": true, "type": "integer", "format": "int32" }, "speakerLabel": { "description": "Output only. A distinct string value is assigned for every speaker within the audio. This field specifies which one of those speakers was detected to have spoken this word.", "readOnly": true, "type": "string" }, "word": { "description": "The word corresponding to this set of information.", "type": "string" }, "endTime": { "description": "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.", "type": "string", "format": "google-duration" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_WordInfo", "description": "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`.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_SpeechTranscription": { "properties": { "alternatives": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_SpeechRecognitionAlternative" }, "description": "May contain one or more recognition hypotheses (up to the maximum specified in `max_alternatives`). These alternatives are ordered in terms of accuracy, with the top (first) alternative being the most probable, as ranked by the recognizer.", "type": "array" }, "languageCode": { "description": "Output only. The [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag of the language in this result. This language code was detected to have the most likelihood of being spoken in the audio.", "readOnly": true, "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_SpeechTranscription", "description": "A speech recognition result corresponding to a portion of the audio.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_SpeechTranscription": { "id": "GoogleCloudVideointelligenceV1p1beta1_SpeechTranscription", "description": "A speech recognition result corresponding to a portion of the audio.", "type": "object", "properties": { "languageCode": { "description": "Output only. The [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language tag of the language in this result. This language code was detected to have the most likelihood of being spoken in the audio.", "readOnly": true, "type": "string" }, "alternatives": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_SpeechRecognitionAlternative" }, "description": "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": "array" } } }, "GoogleCloudVideointelligenceV1beta2_VideoSegment": { "properties": { "startTimeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the start of the segment (inclusive).", "type": "string", "format": "google-duration" }, "endTimeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the end of the segment (inclusive).", "type": "string", "format": "google-duration" } }, "id": "GoogleCloudVideointelligenceV1beta2_VideoSegment", "description": "Video segment.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_ExplicitContentAnnotation": { "properties": { "frames": { "description": "All video frames where explicit content was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_ExplicitContentFrame" } }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_ExplicitContentAnnotation", "description": "Explicit content annotation (based on per-frame visual signals only). If no explicit content has been detected in a frame, no annotations are present for that frame.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_PersonDetectionAnnotation": { "properties": { "tracks": { "description": "The detected tracks of a person.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_Track" } }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_PersonDetectionAnnotation", "description": "Person detection annotation per video.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_DetectedAttribute": { "properties": { "name": { "description": "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": "string" }, "confidence": { "description": "Detected attribute confidence. Range [0, 1].", "type": "number", "format": "float" }, "value": { "description": "Text value of the detection result. For example, the value for \"HairColor\" can be \"black\", \"blonde\", etc.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_DetectedAttribute", "description": "A generic detected attribute represented by name in string format.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_ExplicitContentAnnotation": { "id": "GoogleCloudVideointelligenceV1beta2_ExplicitContentAnnotation", "description": "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.", "type": "object", "properties": { "frames": { "description": "All video frames where explicit content was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_ExplicitContentFrame" } }, "version": { "description": "Feature version.", "type": "string" } } }, "GoogleCloudVideointelligenceV1beta2_ExplicitContentDetectionConfig": { "properties": { "model": { "description": "Model to use for explicit content detection. Supported values: \"builtin/stable\" (the default if unset) and \"builtin/latest\".", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_ExplicitContentDetectionConfig", "description": "Config for EXPLICIT_CONTENT_DETECTION.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_NormalizedBoundingBox": { "id": "GoogleCloudVideointelligenceV1p3beta1_NormalizedBoundingBox", "description": "Normalized bounding box. The normalized vertex coordinates are relative to the original image. Range: [0, 1].", "type": "object", "properties": { "left": { "format": "float", "description": "Left X coordinate.", "type": "number" }, "top": { "description": "Top Y coordinate.", "type": "number", "format": "float" }, "bottom": { "format": "float", "description": "Bottom Y coordinate.", "type": "number" }, "right": { "format": "float", "description": "Right X coordinate.", "type": "number" } } }, "GoogleRpc_Status": { "properties": { "code": { "format": "int32", "description": "The status code, which should be an enum value of google.rpc.Code.", "type": "integer" }, "message": { "description": "A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.", "type": "string" }, "details": { "description": "A list of messages that carry the error details. There is a common set of message types for APIs to use.", "type": "array", "items": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." } } } }, "id": "GoogleRpc_Status", "description": "The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors).", "type": "object" }, "GoogleCloudVideointelligenceV1_ExplicitContentAnnotation": { "properties": { "frames": { "description": "All video frames where explicit content was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_ExplicitContentFrame" } }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1_ExplicitContentAnnotation", "description": "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.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_TimestampedObject": { "id": "GoogleCloudVideointelligenceV1p2beta1_TimestampedObject", "description": "For tracking related features. An object at time_offset with attributes, and located with normalized_bounding_box.", "type": "object", "properties": { "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this object.", "type": "string" }, "attributes": { "description": "Optional. The attributes of the object in the bounding box.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_DetectedAttribute" } }, "landmarks": { "description": "Optional. The detected landmarks.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_DetectedLandmark" } }, "normalizedBoundingBox": { "description": "Normalized Bounding box in a frame, where the object is located.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_NormalizedBoundingBox" } } }, "GoogleCloudVideointelligenceV1p3beta1_StreamingAnnotateVideoResponse": { "properties": { "error": { "description": "If set, returns a google.rpc.Status message that specifies the error for the operation.", "$ref": "GoogleRpc_Status" }, "annotationResults": { "description": "Streaming annotation results.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_StreamingVideoAnnotationResults" }, "annotationResultsUri": { "description": "Google Cloud Storage URI that stores annotation results of one streaming session in JSON format. It is the annotation_result_storage_directory from the request followed by '/cloud_project_number-session_id'.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_StreamingAnnotateVideoResponse", "description": "`StreamingAnnotateVideoResponse` is the only message returned to the client by `StreamingAnnotateVideo`. A series of zero or more `StreamingAnnotateVideoResponse` messages are streamed back to the client.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_VideoContext": { "properties": { "segments": { "description": "Video segments to annotate. The segments may overlap and are not required to be contiguous or span the whole video. If unspecified, each video is treated as a single segment.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" } }, "explicitContentDetectionConfig": { "description": "Config for EXPLICIT_CONTENT_DETECTION.", "$ref": "GoogleCloudVideointelligenceV1beta2_ExplicitContentDetectionConfig" }, "faceDetectionConfig": { "description": "Config for FACE_DETECTION.", "$ref": "GoogleCloudVideointelligenceV1beta2_FaceDetectionConfig" }, "speechTranscriptionConfig": { "description": "Config for SPEECH_TRANSCRIPTION.", "$ref": "GoogleCloudVideointelligenceV1beta2_SpeechTranscriptionConfig" }, "personDetectionConfig": { "description": "Config for PERSON_DETECTION.", "$ref": "GoogleCloudVideointelligenceV1beta2_PersonDetectionConfig" }, "labelDetectionConfig": { "description": "Config for LABEL_DETECTION.", "$ref": "GoogleCloudVideointelligenceV1beta2_LabelDetectionConfig" }, "shotChangeDetectionConfig": { "description": "Config for SHOT_CHANGE_DETECTION.", "$ref": "GoogleCloudVideointelligenceV1beta2_ShotChangeDetectionConfig" }, "textDetectionConfig": { "description": "Config for TEXT_DETECTION.", "$ref": "GoogleCloudVideointelligenceV1beta2_TextDetectionConfig" }, "objectTrackingConfig": { "description": "Config for OBJECT_TRACKING.", "$ref": "GoogleCloudVideointelligenceV1beta2_ObjectTrackingConfig" } }, "id": "GoogleCloudVideointelligenceV1beta2_VideoContext", "description": "Video context and/or feature-specific parameters.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_LabelSegment": { "id": "GoogleCloudVideointelligenceV1p3beta1_LabelSegment", "description": "Video segment level annotation results for label detection.", "type": "object", "properties": { "segment": { "description": "Video segment where a label was detected.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" }, "confidence": { "format": "float", "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number" } } }, "GoogleCloudVideointelligenceV1p2beta1_LabelFrame": { "properties": { "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string" }, "confidence": { "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_LabelFrame", "description": "Video frame level annotation results for label detection.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_SpeechRecognitionAlternative": { "properties": { "words": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_WordInfo" }, "description": "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.", "readOnly": true, "type": "array" }, "transcript": { "description": "Transcript text representing the words that the user spoke.", "type": "string" }, "confidence": { "description": "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.", "readOnly": true, "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1beta2_SpeechRecognitionAlternative", "description": "Alternative hypotheses (a.k.a. n-best list).", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_TextSegment": { "id": "GoogleCloudVideointelligenceV1p3beta1_TextSegment", "description": "Video segment level annotation results for text detection.", "type": "object", "properties": { "confidence": { "description": "Confidence for the track of detected text. It is calculated as the highest over all frames where OCR detected text appears.", "type": "number", "format": "float" }, "frames": { "description": "Information related to the frames where OCR detected text appears.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_TextFrame" } }, "segment": { "description": "Video segment where a text snippet was detected.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" } } }, "GoogleCloudVideointelligenceV1p2beta1_LabelSegment": { "properties": { "segment": { "description": "Video segment where a label was detected.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" }, "confidence": { "format": "float", "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_LabelSegment", "description": "Video segment level annotation results for label detection.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_Track": { "properties": { "confidence": { "description": "Optional. The confidence score of the tracked object.", "type": "number", "format": "float" }, "segment": { "description": "Video segment of a track.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" }, "timestampedObjects": { "description": "The object with timestamp and attributes per frame in the track.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_TimestampedObject" } }, "attributes": { "description": "Optional. Attributes in the track level.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_DetectedAttribute" } } }, "id": "GoogleCloudVideointelligenceV1p2beta1_Track", "description": "A track of an object instance.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_FaceAnnotation": { "properties": { "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_FaceFrame" }, "description": "All video frames where a face was detected.", "type": "array" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_FaceSegment" }, "description": "All video segments where a face was detected.", "type": "array" }, "thumbnail": { "format": "byte", "description": "Thumbnail of a representative face view (in JPEG format).", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_FaceAnnotation", "type": "object", "description": "Deprecated. No effect.", "deprecated": true }, "GoogleCloudVideointelligenceV1beta2_SpeechContext": { "id": "GoogleCloudVideointelligenceV1beta2_SpeechContext", "description": "Provides \"hints\" to the speech recognizer to favor specific words and phrases in the results.", "type": "object", "properties": { "phrases": { "items": { "type": "string" }, "description": "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).", "type": "array" } } }, "GoogleCloudVideointelligenceV1p1beta1_TextAnnotation": { "id": "GoogleCloudVideointelligenceV1p1beta1_TextAnnotation", "description": "Annotations related to one detected OCR text snippet. This will contain the corresponding text, confidence value, and frame level information for each detection.", "type": "object", "properties": { "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_TextSegment" }, "description": "All video segments where OCR detected text appears.", "type": "array" }, "version": { "description": "Feature version.", "type": "string" }, "text": { "description": "The detected text.", "type": "string" } } }, "GoogleCloudVideointelligenceV1_NormalizedBoundingPoly": { "id": "GoogleCloudVideointelligenceV1_NormalizedBoundingPoly", "description": "Normalized bounding polygon for text (that might not be aligned with axis). Contains list of the corner points in clockwise order starting from top-left corner. For example, for a rectangular bounding box: When the text is horizontal it might look like: 0----1 | | 3----2 When it's clockwise rotated 180 degrees around the top-left corner it becomes: 2----3 | | 1----0 and the vertex order will still be (0, 1, 2, 3). Note that values can be less than 0, or greater than 1 due to trigonometric calculations for location of the box.", "type": "object", "properties": { "vertices": { "description": "Normalized vertices of the bounding polygon.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_NormalizedVertex" } } } }, "GoogleLongrunning_Operation": { "properties": { "metadata": { "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." }, "description": "Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.", "type": "object" }, "done": { "description": "If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.", "type": "boolean" }, "response": { "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." }, "description": "The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.", "type": "object" }, "name": { "description": "The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.", "type": "string" }, "error": { "description": "The error result of the operation in case of failure or cancellation.", "$ref": "GoogleRpc_Status" } }, "id": "GoogleLongrunning_Operation", "description": "This resource represents a long-running operation that is the result of a network API call.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_LabelSegment": { "properties": { "segment": { "description": "Video segment where a label was detected.", "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" }, "confidence": { "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1beta2_LabelSegment", "description": "Video segment level annotation results for label detection.", "type": "object" }, "GoogleCloudVideointelligenceV1_WordInfo": { "id": "GoogleCloudVideointelligenceV1_WordInfo", "description": "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`.", "type": "object", "properties": { "startTime": { "description": "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.", "type": "string", "format": "google-duration" }, "confidence": { "description": "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.", "readOnly": true, "type": "number", "format": "float" }, "speakerTag": { "format": "int32", "description": "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.", "readOnly": true, "type": "integer" }, "speakerLabel": { "description": "Output only. A distinct string value is assigned for every speaker within the audio. This field specifies which one of those speakers was detected to have spoken this word.", "readOnly": true, "type": "string" }, "endTime": { "description": "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.", "type": "string", "format": "google-duration" }, "word": { "description": "The word corresponding to this set of information.", "type": "string" } } }, "GoogleCloudVideointelligenceV1beta2_FaceDetectionAnnotation": { "properties": { "tracks": { "description": "The face tracks with attributes.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_Track" } }, "thumbnail": { "format": "byte", "description": "The thumbnail of a person's face.", "type": "string" }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_FaceDetectionAnnotation", "description": "Face detection annotation.", "type": "object" }, "GoogleCloudVideointelligenceV1_ObjectTrackingAnnotation": { "id": "GoogleCloudVideointelligenceV1_ObjectTrackingAnnotation", "description": "Annotations corresponding to one tracked object.", "type": "object", "properties": { "trackId": { "format": "int64", "description": "Streaming mode ONLY. In streaming mode, we do not know the end time of a tracked object before it is completed. Hence, there is no VideoSegment info returned. Instead, we provide a unique identifiable integer track_id so that the customers can correlate the results of the ongoing ObjectTrackAnnotation of the same track_id over time.", "type": "string" }, "entity": { "description": "Entity to specify the object category that this track is labeled as.", "$ref": "GoogleCloudVideointelligenceV1_Entity" }, "confidence": { "format": "float", "description": "Object category's labeling confidence of this track.", "type": "number" }, "segment": { "description": "Non-streaming batch mode ONLY. Each object track corresponds to one video segment where it appears.", "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" }, "frames": { "description": "Information corresponding to all frames where this object track appears. Non-streaming batch mode: it may be one or multiple ObjectTrackingFrame messages in frames. Streaming mode: it can only be one ObjectTrackingFrame message in frames.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_ObjectTrackingFrame" } }, "version": { "description": "Feature version.", "type": "string" } } }, "GoogleCloudVideointelligenceV1beta2_AnnotateVideoRequest": { "id": "GoogleCloudVideointelligenceV1beta2_AnnotateVideoRequest", "description": "Video annotation request.", "type": "object", "properties": { "features": { "items": { "enum": [ "FEATURE_UNSPECIFIED", "LABEL_DETECTION", "SHOT_CHANGE_DETECTION", "EXPLICIT_CONTENT_DETECTION", "FACE_DETECTION", "SPEECH_TRANSCRIPTION", "TEXT_DETECTION", "OBJECT_TRACKING", "LOGO_RECOGNITION", "PERSON_DETECTION" ], "enumDescriptions": [ "Unspecified.", "Label detection. Detect objects, such as dog or flower.", "Shot change detection.", "Explicit content detection.", "Human face detection.", "Speech transcription.", "OCR text detection and tracking.", "Object detection and tracking.", "Logo detection, tracking, and recognition.", "Person detection." ], "type": "string" }, "description": "Required. Requested video annotation features.", "type": "array" }, "videoContext": { "description": "Additional video context and/or feature-specific parameters.", "$ref": "GoogleCloudVideointelligenceV1beta2_VideoContext" }, "outputUri": { "description": "Optional. Location where the output (in JSON format) should be stored. Currently, only [Cloud Storage](https://cloud.google.com/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). For more information, see [Request URIs](https://cloud.google.com/storage/docs/request-endpoints).", "type": "string" }, "locationId": { "description": "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": "string" }, "inputContent": { "description": "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": "string", "format": "byte" }, "inputUri": { "description": "Input video location. Currently, only [Cloud Storage](https://cloud.google.com/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). For more information, see [Request URIs](https://cloud.google.com/storage/docs/request-endpoints). 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": "string" } } }, "GoogleCloudVideointelligenceV1beta2_ExplicitContentFrame": { "properties": { "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string", "format": "google-duration" }, "pornographyLikelihood": { "enumDescriptions": [ "Unspecified likelihood.", "Very unlikely.", "Unlikely.", "Possible.", "Likely.", "Very likely." ], "enum": [ "LIKELIHOOD_UNSPECIFIED", "VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY" ], "description": "Likelihood of the pornography content..", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_ExplicitContentFrame", "description": "Video frame level annotation results for explicit content.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_NormalizedBoundingBox": { "id": "GoogleCloudVideointelligenceV1p1beta1_NormalizedBoundingBox", "description": "Normalized bounding box. The normalized vertex coordinates are relative to the original image. Range: [0, 1].", "type": "object", "properties": { "left": { "description": "Left X coordinate.", "type": "number", "format": "float" }, "top": { "description": "Top Y coordinate.", "type": "number", "format": "float" }, "bottom": { "format": "float", "description": "Bottom Y coordinate.", "type": "number" }, "right": { "format": "float", "description": "Right X coordinate.", "type": "number" } } }, "GoogleCloudVideointelligenceV1p1beta1_AnnotateVideoProgress": { "id": "GoogleCloudVideointelligenceV1p1beta1_AnnotateVideoProgress", "description": "Video annotation progress. Included in the `metadata` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object", "properties": { "annotationProgress": { "description": "Progress metadata for all videos specified in `AnnotateVideoRequest`.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoAnnotationProgress" } } } }, "GoogleCloudVideointelligenceV1p2beta1_ObjectTrackingFrame": { "properties": { "normalizedBoundingBox": { "description": "The normalized bounding box location of this object track for the frame.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_NormalizedBoundingBox" }, "timeOffset": { "format": "google-duration", "description": "The timestamp of the frame in microseconds.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_ObjectTrackingFrame", "description": "Video frame level annotations for object detection and tracking. This field stores per frame location, time offset, and confidence.", "type": "object" }, "GoogleCloudVideointelligenceV1_NormalizedVertex": { "id": "GoogleCloudVideointelligenceV1_NormalizedVertex", "description": "A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.", "type": "object", "properties": { "x": { "description": "X coordinate.", "type": "number", "format": "float" }, "y": { "description": "Y coordinate.", "type": "number", "format": "float" } } }, "GoogleCloudVideointelligenceV1p1beta1_DetectedLandmark": { "properties": { "name": { "description": "The name of this landmark, for example, left_hand, right_shoulder.", "type": "string" }, "point": { "description": "The 2D point of the detected landmark using the normalized image coordinate system. The normalized coordinates have the range from 0 to 1.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_NormalizedVertex" }, "confidence": { "description": "The confidence score of the detected landmark. Range [0, 1].", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_DetectedLandmark", "description": "A generic detected landmark represented by name in string format and a 2D location.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_NormalizedBoundingBox": { "id": "GoogleCloudVideointelligenceV1beta2_NormalizedBoundingBox", "description": "Normalized bounding box. The normalized vertex coordinates are relative to the original image. Range: [0, 1].", "type": "object", "properties": { "right": { "format": "float", "description": "Right X coordinate.", "type": "number" }, "left": { "format": "float", "description": "Left X coordinate.", "type": "number" }, "top": { "format": "float", "description": "Top Y coordinate.", "type": "number" }, "bottom": { "description": "Bottom Y coordinate.", "type": "number", "format": "float" } } }, "GoogleCloudVideointelligenceV1beta2_ObjectTrackingAnnotation": { "id": "GoogleCloudVideointelligenceV1beta2_ObjectTrackingAnnotation", "description": "Annotations corresponding to one tracked object.", "type": "object", "properties": { "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_ObjectTrackingFrame" }, "description": "Information corresponding to all frames where this object track appears. Non-streaming batch mode: it may be one or multiple ObjectTrackingFrame messages in frames. Streaming mode: it can only be one ObjectTrackingFrame message in frames.", "type": "array" }, "version": { "description": "Feature version.", "type": "string" }, "trackId": { "description": "Streaming mode ONLY. In streaming mode, we do not know the end time of a tracked object before it is completed. Hence, there is no VideoSegment info returned. Instead, we provide a unique identifiable integer track_id so that the customers can correlate the results of the ongoing ObjectTrackAnnotation of the same track_id over time.", "type": "string", "format": "int64" }, "entity": { "description": "Entity to specify the object category that this track is labeled as.", "$ref": "GoogleCloudVideointelligenceV1beta2_Entity" }, "confidence": { "description": "Object category's labeling confidence of this track.", "type": "number", "format": "float" }, "segment": { "description": "Non-streaming batch mode ONLY. Each object track corresponds to one video segment where it appears.", "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" } } }, "GoogleCloudVideointelligenceV1p1beta1_Track": { "id": "GoogleCloudVideointelligenceV1p1beta1_Track", "description": "A track of an object instance.", "type": "object", "properties": { "confidence": { "format": "float", "description": "Optional. The confidence score of the tracked object.", "type": "number" }, "segment": { "description": "Video segment of a track.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" }, "timestampedObjects": { "description": "The object with timestamp and attributes per frame in the track.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_TimestampedObject" } }, "attributes": { "description": "Optional. Attributes in the track level.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_DetectedAttribute" } } } }, "GoogleCloudVideointelligenceV1_ObjectTrackingFrame": { "id": "GoogleCloudVideointelligenceV1_ObjectTrackingFrame", "description": "Video frame level annotations for object detection and tracking. This field stores per frame location, time offset, and confidence.", "type": "object", "properties": { "normalizedBoundingBox": { "description": "The normalized bounding box location of this object track for the frame.", "$ref": "GoogleCloudVideointelligenceV1_NormalizedBoundingBox" }, "timeOffset": { "format": "google-duration", "description": "The timestamp of the frame in microseconds.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p2beta1_ExplicitContentAnnotation": { "properties": { "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_ExplicitContentFrame" }, "description": "All video frames where explicit content was detected.", "type": "array" }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_ExplicitContentAnnotation", "description": "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.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_FaceFrame": { "properties": { "normalizedBoundingBoxes": { "description": "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.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_NormalizedBoundingBox" } }, "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_FaceFrame", "type": "object", "description": "Deprecated. No effect.", "deprecated": true }, "GoogleCloudVideointelligenceV1p3beta1_LabelFrame": { "id": "GoogleCloudVideointelligenceV1p3beta1_LabelFrame", "description": "Video frame level annotation results for label detection.", "type": "object", "properties": { "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string" }, "confidence": { "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number", "format": "float" } } }, "GoogleCloudVideointelligenceV1beta2_VideoAnnotationProgress": { "id": "GoogleCloudVideointelligenceV1beta2_VideoAnnotationProgress", "description": "Annotation progress for a single video.", "type": "object", "properties": { "startTime": { "format": "google-datetime", "description": "Time when the request was received.", "type": "string" }, "progressPercent": { "description": "Approximate percentage processed thus far. Guaranteed to be 100 when fully processed.", "type": "integer", "format": "int32" }, "segment": { "description": "Specifies which segment is being tracked if the request contains more than one segment.", "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" }, "exportStatus": { "description": "Status of exporting annotation response to user specified `output_uri`. Only set if `output_uri` is set in the request.", "$ref": "GoogleCloudVideointelligenceV1beta2_ExportToOutputUriStatus" }, "feature": { "description": "Specifies which feature is being tracked if the request contains more than one feature.", "type": "string", "enumDescriptions": [ "Unspecified.", "Label detection. Detect objects, such as dog or flower.", "Shot change detection.", "Explicit content detection.", "Human face detection.", "Speech transcription.", "OCR text detection and tracking.", "Object detection and tracking.", "Logo detection, tracking, and recognition.", "Person detection." ], "enum": [ "FEATURE_UNSPECIFIED", "LABEL_DETECTION", "SHOT_CHANGE_DETECTION", "EXPLICIT_CONTENT_DETECTION", "FACE_DETECTION", "SPEECH_TRANSCRIPTION", "TEXT_DETECTION", "OBJECT_TRACKING", "LOGO_RECOGNITION", "PERSON_DETECTION" ] }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Time of the most recent update.", "type": "string" } } }, "GoogleCloudVideointelligenceV1beta2_DetectedLandmark": { "properties": { "name": { "description": "The name of this landmark, for example, left_hand, right_shoulder.", "type": "string" }, "point": { "description": "The 2D point of the detected landmark using the normalized image coordinate system. The normalized coordinates have the range from 0 to 1.", "$ref": "GoogleCloudVideointelligenceV1beta2_NormalizedVertex" }, "confidence": { "format": "float", "description": "The confidence score of the detected landmark. Range [0, 1].", "type": "number" } }, "id": "GoogleCloudVideointelligenceV1beta2_DetectedLandmark", "description": "A generic detected landmark represented by name in string format and a 2D location.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_VideoAnnotationResults": { "properties": { "faceDetectionAnnotations": { "description": "Face detection annotations.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_FaceDetectionAnnotation" } }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "segmentPresenceLabelAnnotations": { "description": "Presence label annotations on video level or user-specified segment level. There is exactly one element for each unique label. Compared to the existing topical `segment_label_annotations`, this field presents more fine-grained, segment-level labels detected in video content and is made available only when the client sets `LabelDetectionConfig.model` to \"builtin/latest\" in the request.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_LabelAnnotation" } }, "textAnnotations": { "description": "OCR text detection and tracking. Annotations for list of detected text snippets. Each will have list of frame information associated with it.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_TextAnnotation" } }, "error": { "description": "If set, indicates an error. Note that for a single `AnnotateVideoRequest` some videos may succeed and some may fail.", "$ref": "GoogleRpc_Status" }, "shotAnnotations": { "description": "Shot annotations. Each shot is represented as a video segment.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" } }, "segmentLabelAnnotations": { "description": "Topical label annotations on video level or user-specified segment level. There is exactly one element for each unique label.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_LabelAnnotation" } }, "explicitAnnotation": { "description": "Explicit content annotation.", "$ref": "GoogleCloudVideointelligenceV1beta2_ExplicitContentAnnotation" }, "speechTranscriptions": { "description": "Speech transcription.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_SpeechTranscription" } }, "frameLabelAnnotations": { "description": "Label annotations on frame level. There is exactly one element for each unique label.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_LabelAnnotation" } }, "logoRecognitionAnnotations": { "description": "Annotations for list of logos detected, tracked and recognized in video.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_LogoRecognitionAnnotation" } }, "shotLabelAnnotations": { "description": "Topical label annotations on shot level. There is exactly one element for each unique label.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_LabelAnnotation" } }, "objectAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_ObjectTrackingAnnotation" }, "description": "Annotations for list of objects detected and tracked in video.", "type": "array" }, "shotPresenceLabelAnnotations": { "description": "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.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_LabelAnnotation" } }, "faceAnnotations": { "description": "Deprecated. Please use `face_detection_annotations` instead.", "type": "array", "deprecated": true, "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_FaceAnnotation" } }, "segment": { "description": "Video segment on which the annotation is run.", "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" }, "personDetectionAnnotations": { "description": "Person detection annotations.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_PersonDetectionAnnotation" } } }, "id": "GoogleCloudVideointelligenceV1beta2_VideoAnnotationResults", "description": "Annotation results for a single video.", "type": "object" }, "GoogleCloudVideointelligenceV1_AnnotateVideoResponse": { "properties": { "annotationResults": { "description": "Annotation results for all videos specified in `AnnotateVideoRequest`.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_VideoAnnotationResults" } } }, "id": "GoogleCloudVideointelligenceV1_AnnotateVideoResponse", "description": "Video annotation response. Included in the `response` field of the `Operation` returned by the `GetOperation` call of the `google::longrunning::Operations` service.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_LogoRecognitionAnnotation": { "id": "GoogleCloudVideointelligenceV1p2beta1_LogoRecognitionAnnotation", "description": "Annotation corresponding to one detected, tracked and recognized logo class.", "type": "object", "properties": { "entity": { "description": "Entity category information to specify the logo class that all the logo tracks within this LogoRecognitionAnnotation are recognized as.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_Entity" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" }, "description": "All video segments where the recognized logo appears. There might be multiple instances of the same logo class appearing in one VideoSegment.", "type": "array" }, "tracks": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_Track" }, "description": "All logo tracks where the recognized logo appears. Each track corresponds to one logo instance appearing in consecutive frames.", "type": "array" } } }, "GoogleCloudVideointelligenceV1p2beta1_FaceDetectionAnnotation": { "id": "GoogleCloudVideointelligenceV1p2beta1_FaceDetectionAnnotation", "description": "Face detection annotation.", "type": "object", "properties": { "tracks": { "description": "The face tracks with attributes.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_Track" } }, "thumbnail": { "description": "The thumbnail of a person's face.", "type": "string", "format": "byte" }, "version": { "description": "Feature version.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p1beta1_DetectedAttribute": { "id": "GoogleCloudVideointelligenceV1p1beta1_DetectedAttribute", "description": "A generic detected attribute represented by name in string format.", "type": "object", "properties": { "name": { "description": "The name of the attribute, for example, glasses, dark_glasses, mouth_open. A full list of supported type names will be provided in the document.", "type": "string" }, "confidence": { "format": "float", "description": "Detected attribute confidence. Range [0, 1].", "type": "number" }, "value": { "description": "Text value of the detection result. For example, the value for \"HairColor\" can be \"black\", \"blonde\", etc.", "type": "string" } } }, "GoogleCloudVideointelligenceV1p3beta1_ObjectTrackingFrame": { "properties": { "normalizedBoundingBox": { "description": "The normalized bounding box location of this object track for the frame.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_NormalizedBoundingBox" }, "timeOffset": { "format": "google-duration", "description": "The timestamp of the frame in microseconds.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_ObjectTrackingFrame", "description": "Video frame level annotations for object detection and tracking. This field stores per frame location, time offset, and confidence.", "type": "object" }, "GoogleCloudVideointelligenceV1_LabelAnnotation": { "id": "GoogleCloudVideointelligenceV1_LabelAnnotation", "description": "Label annotation.", "type": "object", "properties": { "frames": { "description": "All video frames where a label was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_LabelFrame" } }, "categoryEntities": { "items": { "$ref": "GoogleCloudVideointelligenceV1_Entity" }, "description": "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": "array" }, "version": { "description": "Feature version.", "type": "string" }, "entity": { "description": "Detected entity.", "$ref": "GoogleCloudVideointelligenceV1_Entity" }, "segments": { "description": "All video segments where a label was detected.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_LabelSegment" } } } }, "GoogleCloudVideointelligenceV1p1beta1_FaceAnnotation": { "properties": { "thumbnail": { "description": "Thumbnail of a representative face view (in JPEG format).", "type": "string", "format": "byte" }, "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_FaceFrame" }, "description": "All video frames where a face was detected.", "type": "array" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_FaceSegment" }, "description": "All video segments where a face was detected.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_FaceAnnotation", "type": "object", "deprecated": true, "description": "Deprecated. No effect." }, "GoogleCloudVideointelligenceV1p1beta1_ExportToOutputUriStatus": { "properties": { "state": { "type": "string", "enum": [ "STATE_UNSPECIFIED", "SUCCEEDED", "FAILED" ], "enumDescriptions": [ "Default value.", "Export succeeded.", "Export failed." ], "description": "Output only. State of the `output_uri` export.", "readOnly": true }, "status": { "description": "Output only. Only set if state is FAILED.", "readOnly": true, "$ref": "GoogleRpc_Status" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_ExportToOutputUriStatus", "description": "Status of exporting annotation response to user specified `output_uri`.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_RecognizedCelebrity": { "properties": { "celebrity": { "description": "The recognized celebrity.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_Celebrity" }, "confidence": { "format": "float", "description": "Recognition confidence. Range [0, 1].", "type": "number" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_RecognizedCelebrity", "description": "The recognized celebrity with confidence score.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_TimestampedObject": { "id": "GoogleCloudVideointelligenceV1p1beta1_TimestampedObject", "description": "For tracking related features. An object at time_offset with attributes, and located with normalized_bounding_box.", "type": "object", "properties": { "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this object.", "type": "string", "format": "google-duration" }, "attributes": { "description": "Optional. The attributes of the object in the bounding box.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_DetectedAttribute" } }, "landmarks": { "description": "Optional. The detected landmarks.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_DetectedLandmark" } }, "normalizedBoundingBox": { "description": "Normalized Bounding box in a frame, where the object is located.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_NormalizedBoundingBox" } } }, "GoogleCloudVideointelligenceV1beta2_TextFrame": { "properties": { "rotatedBoundingBox": { "description": "Bounding polygon of the detected text for this frame.", "$ref": "GoogleCloudVideointelligenceV1beta2_NormalizedBoundingPoly" }, "timeOffset": { "format": "google-duration", "description": "Timestamp of this frame.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_TextFrame", "description": "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.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_ShotChangeDetectionConfig": { "properties": { "model": { "description": "Model to use for shot change detection. Supported values: \"builtin/stable\" (the default if unset), \"builtin/latest\", and \"builtin/legacy\".", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_ShotChangeDetectionConfig", "description": "Config for SHOT_CHANGE_DETECTION.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_VideoAnnotationResults": { "properties": { "objectAnnotations": { "description": "Annotations for list of objects detected and tracked in video.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_ObjectTrackingAnnotation" } }, "shotPresenceLabelAnnotations": { "description": "Presence label annotations on shot level. There is exactly one element for each unique label. Compared to the existing topical `shot_label_annotations`, this field presents more fine-grained, shot-level labels detected in video content and is made available only when the client sets `LabelDetectionConfig.model` to \"builtin/latest\" in the request.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_LabelAnnotation" } }, "faceAnnotations": { "deprecated": true, "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_FaceAnnotation" }, "description": "Deprecated. Please use `face_detection_annotations` instead.", "type": "array" }, "shotLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_LabelAnnotation" }, "description": "Topical label annotations on shot level. There is exactly one element for each unique label.", "type": "array" }, "personDetectionAnnotations": { "description": "Person detection annotations.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_PersonDetectionAnnotation" } }, "segment": { "description": "Video segment on which the annotation is run.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" }, "segmentPresenceLabelAnnotations": { "description": "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.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_LabelAnnotation" } }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "textAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_TextAnnotation" }, "description": "OCR text detection and tracking. Annotations for list of detected text snippets. Each will have list of frame information associated with it.", "type": "array" }, "error": { "description": "If set, indicates an error. Note that for a single `AnnotateVideoRequest` some videos may succeed and some may fail.", "$ref": "GoogleRpc_Status" }, "faceDetectionAnnotations": { "description": "Face detection annotations.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_FaceDetectionAnnotation" } }, "frameLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_LabelAnnotation" }, "description": "Label annotations on frame level. There is exactly one element for each unique label.", "type": "array" }, "logoRecognitionAnnotations": { "description": "Annotations for list of logos detected, tracked and recognized in video.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_LogoRecognitionAnnotation" } }, "segmentLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_LabelAnnotation" }, "description": "Topical label annotations on video level or user-specified segment level. There is exactly one element for each unique label.", "type": "array" }, "explicitAnnotation": { "description": "Explicit content annotation.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_ExplicitContentAnnotation" }, "speechTranscriptions": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_SpeechTranscription" }, "description": "Speech transcription.", "type": "array" }, "shotAnnotations": { "description": "Shot annotations. Each shot is represented as a video segment.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" } } }, "id": "GoogleCloudVideointelligenceV1p2beta1_VideoAnnotationResults", "description": "Annotation results for a single video.", "type": "object" }, "GoogleCloudVideointelligenceV1_Track": { "properties": { "confidence": { "description": "Optional. The confidence score of the tracked object.", "type": "number", "format": "float" }, "segment": { "description": "Video segment of a track.", "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" }, "timestampedObjects": { "items": { "$ref": "GoogleCloudVideointelligenceV1_TimestampedObject" }, "description": "The object with timestamp and attributes per frame in the track.", "type": "array" }, "attributes": { "description": "Optional. Attributes in the track level.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_DetectedAttribute" } } }, "id": "GoogleCloudVideointelligenceV1_Track", "description": "A track of an object instance.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_VideoAnnotationResults": { "properties": { "frameLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_LabelAnnotation" }, "description": "Label annotations on frame level. There is exactly one element for each unique label.", "type": "array" }, "logoRecognitionAnnotations": { "description": "Annotations for list of logos detected, tracked and recognized in video.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_LogoRecognitionAnnotation" } }, "segmentLabelAnnotations": { "description": "Topical label annotations on video level or user-specified segment level. There is exactly one element for each unique label.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_LabelAnnotation" } }, "explicitAnnotation": { "description": "Explicit content annotation.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_ExplicitContentAnnotation" }, "speechTranscriptions": { "description": "Speech transcription.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_SpeechTranscription" } }, "shotAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" }, "description": "Shot annotations. Each shot is represented as a video segment.", "type": "array" }, "textAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_TextAnnotation" }, "description": "OCR text detection and tracking. Annotations for list of detected text snippets. Each will have list of frame information associated with it.", "type": "array" }, "error": { "description": "If set, indicates an error. Note that for a single `AnnotateVideoRequest` some videos may succeed and some may fail.", "$ref": "GoogleRpc_Status" }, "segmentPresenceLabelAnnotations": { "description": "Presence label annotations on video level or user-specified segment level. There is exactly one element for each unique label. Compared to the existing topical `segment_label_annotations`, this field presents more fine-grained, segment-level labels detected in video content and is made available only when the client sets `LabelDetectionConfig.model` to \"builtin/latest\" in the request.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_LabelAnnotation" } }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "faceDetectionAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_FaceDetectionAnnotation" }, "description": "Face detection annotations.", "type": "array" }, "personDetectionAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_PersonDetectionAnnotation" }, "description": "Person detection annotations.", "type": "array" }, "segment": { "description": "Video segment on which the annotation is run.", "$ref": "GoogleCloudVideointelligenceV1p1beta1_VideoSegment" }, "shotPresenceLabelAnnotations": { "description": "Presence label annotations on shot level. There is exactly one element for each unique label. Compared to the existing topical `shot_label_annotations`, this field presents more fine-grained, shot-level labels detected in video content and is made available only when the client sets `LabelDetectionConfig.model` to \"builtin/latest\" in the request.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_LabelAnnotation" } }, "faceAnnotations": { "description": "Deprecated. Please use `face_detection_annotations` instead.", "type": "array", "deprecated": true, "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_FaceAnnotation" } }, "objectAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_ObjectTrackingAnnotation" }, "description": "Annotations for list of objects detected and tracked in video.", "type": "array" }, "shotLabelAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_LabelAnnotation" }, "description": "Topical label annotations on shot level. There is exactly one element for each unique label.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_VideoAnnotationResults", "description": "Annotation results for a single video.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_LabelAnnotation": { "properties": { "version": { "description": "Feature version.", "type": "string" }, "frames": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_LabelFrame" }, "description": "All video frames where a label was detected.", "type": "array" }, "categoryEntities": { "description": "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": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_Entity" } }, "entity": { "description": "Detected entity.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_Entity" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1p2beta1_LabelSegment" }, "description": "All video segments where a label was detected.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_LabelAnnotation", "description": "Label annotation.", "type": "object" }, "GoogleCloudVideointelligenceV1p2beta1_VideoAnnotationProgress": { "id": "GoogleCloudVideointelligenceV1p2beta1_VideoAnnotationProgress", "description": "Annotation progress for a single video.", "type": "object", "properties": { "progressPercent": { "description": "Approximate percentage processed thus far. Guaranteed to be 100 when fully processed.", "type": "integer", "format": "int32" }, "segment": { "description": "Specifies which segment is being tracked if the request contains more than one segment.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_VideoSegment" }, "exportStatus": { "description": "Status of exporting annotation response to user specified `output_uri`. Only set if `output_uri` is set in the request.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_ExportToOutputUriStatus" }, "startTime": { "format": "google-datetime", "description": "Time when the request was received.", "type": "string" }, "updateTime": { "format": "google-datetime", "description": "Time of the most recent update.", "type": "string" }, "inputUri": { "description": "Video file location in [Cloud Storage](https://cloud.google.com/storage/).", "type": "string" }, "feature": { "description": "Specifies which feature is being tracked if the request contains more than one feature.", "type": "string", "enum": [ "FEATURE_UNSPECIFIED", "LABEL_DETECTION", "SHOT_CHANGE_DETECTION", "EXPLICIT_CONTENT_DETECTION", "FACE_DETECTION", "SPEECH_TRANSCRIPTION", "TEXT_DETECTION", "OBJECT_TRACKING", "LOGO_RECOGNITION", "PERSON_DETECTION" ], "enumDescriptions": [ "Unspecified.", "Label detection. Detect objects, such as dog or flower.", "Shot change detection.", "Explicit content detection.", "Human face detection.", "Speech transcription.", "OCR text detection and tracking.", "Object detection and tracking.", "Logo detection, tracking, and recognition.", "Person detection." ] } } }, "GoogleCloudVideointelligenceV1beta2_LabelDetectionConfig": { "properties": { "frameConfidenceThreshold": { "description": "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": "number", "format": "float" }, "labelDetectionMode": { "enum": [ "LABEL_DETECTION_MODE_UNSPECIFIED", "SHOT_MODE", "FRAME_MODE", "SHOT_AND_FRAME_MODE" ], "enumDescriptions": [ "Unspecified.", "Detect shot-level labels.", "Detect frame-level labels.", "Detect both shot-level and frame-level labels." ], "description": "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": "string" }, "videoConfidenceThreshold": { "format": "float", "description": "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": "number" }, "stationaryCamera": { "description": "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": "boolean" }, "model": { "description": "Model to use for label detection. Supported values: \"builtin/stable\" (the default if unset) and \"builtin/latest\".", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1beta2_LabelDetectionConfig", "description": "Config for LABEL_DETECTION.", "type": "object" }, "GoogleCloudVideointelligenceV1_TextSegment": { "id": "GoogleCloudVideointelligenceV1_TextSegment", "description": "Video segment level annotation results for text detection.", "type": "object", "properties": { "segment": { "description": "Video segment where a text snippet was detected.", "$ref": "GoogleCloudVideointelligenceV1_VideoSegment" }, "confidence": { "format": "float", "description": "Confidence for the track of detected text. It is calculated as the highest over all frames where OCR detected text appears.", "type": "number" }, "frames": { "description": "Information related to the frames where OCR detected text appears.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1_TextFrame" } } } }, "GoogleCloudVideointelligenceV1p2beta1_TextFrame": { "id": "GoogleCloudVideointelligenceV1p2beta1_TextFrame", "description": "Video frame level annotation results for text annotation (OCR). Contains information regarding timestamp and bounding box locations for the frames containing detected OCR text snippets.", "type": "object", "properties": { "rotatedBoundingBox": { "description": "Bounding polygon of the detected text for this frame.", "$ref": "GoogleCloudVideointelligenceV1p2beta1_NormalizedBoundingPoly" }, "timeOffset": { "description": "Timestamp of this frame.", "type": "string", "format": "google-duration" } } }, "GoogleCloudVideointelligenceV1_ExplicitContentFrame": { "id": "GoogleCloudVideointelligenceV1_ExplicitContentFrame", "description": "Video frame level annotation results for explicit content.", "type": "object", "properties": { "timeOffset": { "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string", "format": "google-duration" }, "pornographyLikelihood": { "description": "Likelihood of the pornography content..", "type": "string", "enumDescriptions": [ "Unspecified likelihood.", "Very unlikely.", "Unlikely.", "Possible.", "Likely.", "Very likely." ], "enum": [ "LIKELIHOOD_UNSPECIFIED", "VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY" ] } } }, "GoogleCloudVideointelligenceV1p3beta1_LogoRecognitionAnnotation": { "id": "GoogleCloudVideointelligenceV1p3beta1_LogoRecognitionAnnotation", "description": "Annotation corresponding to one detected, tracked and recognized logo class.", "type": "object", "properties": { "entity": { "description": "Entity category information to specify the logo class that all the logo tracks within this LogoRecognitionAnnotation are recognized as.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_Entity" }, "segments": { "description": "All video segments where the recognized logo appears. There might be multiple instances of the same logo class appearing in one VideoSegment.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" } }, "tracks": { "description": "All logo tracks where the recognized logo appears. Each track corresponds to one logo instance appearing in consecutive frames.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_Track" } } } }, "GoogleCloudVideointelligenceV1p3beta1_CelebrityRecognitionAnnotation": { "properties": { "version": { "description": "Feature version.", "type": "string" }, "celebrityTracks": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_CelebrityTrack" }, "description": "The tracks detected from the input video, including recognized celebrities and other detected faces in the video.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_CelebrityRecognitionAnnotation", "description": "Celebrity recognition annotation per video.", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_PersonDetectionConfig": { "id": "GoogleCloudVideointelligenceV1beta2_PersonDetectionConfig", "description": "Config for PERSON_DETECTION.", "type": "object", "properties": { "includeAttributes": { "description": "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": "boolean" }, "includeBoundingBoxes": { "description": "Whether bounding boxes are included in the person detection annotation output.", "type": "boolean" }, "includePoseLandmarks": { "description": "Whether to enable pose landmarks detection. Ignored if 'include_bounding_boxes' is set to false.", "type": "boolean" } } }, "GoogleCloudVideointelligenceV1beta2_ExportToOutputUriStatus": { "id": "GoogleCloudVideointelligenceV1beta2_ExportToOutputUriStatus", "description": "Status of exporting annotation response to user specified `output_uri`.", "type": "object", "properties": { "state": { "type": "string", "enum": [ "STATE_UNSPECIFIED", "SUCCEEDED", "FAILED" ], "enumDescriptions": [ "Default value.", "Export succeeded.", "Export failed." ], "description": "Output only. State of the `output_uri` export.", "readOnly": true }, "status": { "description": "Output only. Only set if state is FAILED.", "readOnly": true, "$ref": "GoogleRpc_Status" } } }, "GoogleCloudVideointelligenceV1p2beta1_NormalizedBoundingBox": { "properties": { "right": { "description": "Right X coordinate.", "type": "number", "format": "float" }, "left": { "description": "Left X coordinate.", "type": "number", "format": "float" }, "top": { "description": "Top Y coordinate.", "type": "number", "format": "float" }, "bottom": { "description": "Bottom Y coordinate.", "type": "number", "format": "float" } }, "id": "GoogleCloudVideointelligenceV1p2beta1_NormalizedBoundingBox", "description": "Normalized bounding box. The normalized vertex coordinates are relative to the original image. Range: [0, 1].", "type": "object" }, "GoogleCloudVideointelligenceV1beta2_LogoRecognitionAnnotation": { "properties": { "tracks": { "description": "All logo tracks where the recognized logo appears. Each track corresponds to one logo instance appearing in consecutive frames.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_Track" } }, "entity": { "description": "Entity category information to specify the logo class that all the logo tracks within this LogoRecognitionAnnotation are recognized as.", "$ref": "GoogleCloudVideointelligenceV1beta2_Entity" }, "segments": { "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" }, "description": "All video segments where the recognized logo appears. There might be multiple instances of the same logo class appearing in one VideoSegment.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1beta2_LogoRecognitionAnnotation", "description": "Annotation corresponding to one detected, tracked and recognized logo class.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_StreamingVideoAnnotationResults": { "properties": { "frameTimestamp": { "description": "Timestamp of the processed frame in microseconds.", "type": "string", "format": "google-duration" }, "shotAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" }, "description": "Shot annotation results. Each shot is represented as a video segment.", "type": "array" }, "labelAnnotations": { "description": "Label annotation results.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_LabelAnnotation" } }, "explicitAnnotation": { "description": "Explicit content annotation results.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_ExplicitContentAnnotation" }, "objectAnnotations": { "items": { "$ref": "GoogleCloudVideointelligenceV1p3beta1_ObjectTrackingAnnotation" }, "description": "Object tracking results.", "type": "array" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_StreamingVideoAnnotationResults", "description": "Streaming annotation results corresponding to a portion of the video that is currently being processed. Only ONE type of annotation will be specified in the response.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_FaceDetectionAnnotation": { "properties": { "tracks": { "items": { "$ref": "GoogleCloudVideointelligenceV1p1beta1_Track" }, "description": "The face tracks with attributes.", "type": "array" }, "thumbnail": { "format": "byte", "description": "The thumbnail of a person's face.", "type": "string" }, "version": { "description": "Feature version.", "type": "string" } }, "id": "GoogleCloudVideointelligenceV1p1beta1_FaceDetectionAnnotation", "description": "Face detection annotation.", "type": "object" }, "GoogleCloudVideointelligenceV1p3beta1_FaceSegment": { "properties": { "segment": { "description": "Video segment where a face was detected.", "$ref": "GoogleCloudVideointelligenceV1p3beta1_VideoSegment" } }, "id": "GoogleCloudVideointelligenceV1p3beta1_FaceSegment", "description": "Video segment level annotation results for face detection.", "type": "object" }, "GoogleCloudVideointelligenceV1p1beta1_LabelFrame": { "id": "GoogleCloudVideointelligenceV1p1beta1_LabelFrame", "description": "Video frame level annotation results for label detection.", "type": "object", "properties": { "timeOffset": { "format": "google-duration", "description": "Time-offset, relative to the beginning of the video, corresponding to the video frame for this location.", "type": "string" }, "confidence": { "description": "Confidence that the label is accurate. Range: [0, 1].", "type": "number", "format": "float" } } }, "GoogleCloudVideointelligenceV1beta2_TextSegment": { "properties": { "frames": { "description": "Information related to the frames where OCR detected text appears.", "type": "array", "items": { "$ref": "GoogleCloudVideointelligenceV1beta2_TextFrame" } }, "confidence": { "format": "float", "description": "Confidence for the track of detected text. It is calculated as the highest over all frames where OCR detected text appears.", "type": "number" }, "segment": { "description": "Video segment where a text snippet was detected.", "$ref": "GoogleCloudVideointelligenceV1beta2_VideoSegment" } }, "id": "GoogleCloudVideointelligenceV1beta2_TextSegment", "description": "Video segment level annotation results for text detection.", "type": "object" } }, "discoveryVersion": "v1", "fullyEncodeReservedExpansion": true }