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662 lines
22 KiB
Protocol Buffer
662 lines
22 KiB
Protocol Buffer
// Copyright 2025 Google LLC
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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syntax = "proto3";
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package google.cloud.visionai.v1;
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import "google/protobuf/struct.proto";
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import "google/protobuf/timestamp.proto";
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option csharp_namespace = "Google.Cloud.VisionAI.V1";
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option go_package = "cloud.google.com/go/visionai/apiv1/visionaipb;visionaipb";
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option java_multiple_files = true;
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option java_outer_classname = "AnnotationsProto";
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option java_package = "com.google.cloud.visionai.v1";
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option php_namespace = "Google\\Cloud\\VisionAI\\V1";
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option ruby_package = "Google::Cloud::VisionAI::V1";
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// Enum describing all possible types of a stream annotation.
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enum StreamAnnotationType {
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// Type UNSPECIFIED.
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STREAM_ANNOTATION_TYPE_UNSPECIFIED = 0;
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// active_zone annotation defines a polygon on top of the content from an
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// image/video based stream, following processing will only focus on the
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// content inside the active zone.
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STREAM_ANNOTATION_TYPE_ACTIVE_ZONE = 1;
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// crossing_line annotation defines a polyline on top of the content from an
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// image/video based Vision AI stream, events happening across the line will
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// be captured. For example, the counts of people who goes acroos the line
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// in Occupancy Analytic Processor.
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STREAM_ANNOTATION_TYPE_CROSSING_LINE = 2;
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}
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// Output format for Personal Protective Equipment Detection Operator.
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message PersonalProtectiveEquipmentDetectionOutput {
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// The entity info for annotations from person detection prediction result.
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message PersonEntity {
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// Entity id.
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int64 person_entity_id = 1;
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}
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// The entity info for annotations from PPE detection prediction result.
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message PPEEntity {
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// Label id.
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int64 ppe_label_id = 1;
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// Human readable string of the label (Examples: helmet, glove, mask).
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string ppe_label_string = 2;
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// Human readable string of the super category label (Examples: head_cover,
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// hands_cover, face_cover).
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string ppe_supercategory_label_string = 3;
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// Entity id.
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int64 ppe_entity_id = 4;
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}
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// Bounding Box in the normalized coordinates.
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message NormalizedBoundingBox {
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// Min in x coordinate.
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float xmin = 1;
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// Min in y coordinate.
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float ymin = 2;
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// Width of the bounding box.
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float width = 3;
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// Height of the bounding box.
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float height = 4;
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}
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// PersonIdentified box contains the location and the entity info of the
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// person.
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message PersonIdentifiedBox {
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// An unique id for this box.
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int64 box_id = 1;
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// Bounding Box in the normalized coordinates.
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NormalizedBoundingBox normalized_bounding_box = 2;
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// Confidence score associated with this box.
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float confidence_score = 3;
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// Person entity info.
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PersonEntity person_entity = 4;
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}
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// PPEIdentified box contains the location and the entity info of the PPE.
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message PPEIdentifiedBox {
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// An unique id for this box.
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int64 box_id = 1;
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// Bounding Box in the normalized coordinates.
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NormalizedBoundingBox normalized_bounding_box = 2;
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// Confidence score associated with this box.
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float confidence_score = 3;
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// PPE entity info.
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PPEEntity ppe_entity = 4;
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}
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// Detected Person contains the detected person and their associated
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// ppes and their protecting information.
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message DetectedPerson {
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// The id of detected person.
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int64 person_id = 1;
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// The info of detected person identified box.
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PersonIdentifiedBox detected_person_identified_box = 2;
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// The info of detected person associated ppe identified boxes.
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repeated PPEIdentifiedBox detected_ppe_identified_boxes = 3;
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// Coverage score for each body part.
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// Coverage score for face.
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optional float face_coverage_score = 4;
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// Coverage score for eyes.
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optional float eyes_coverage_score = 5;
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// Coverage score for head.
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optional float head_coverage_score = 6;
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// Coverage score for hands.
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optional float hands_coverage_score = 7;
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// Coverage score for body.
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optional float body_coverage_score = 8;
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// Coverage score for feet.
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optional float feet_coverage_score = 9;
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}
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// Current timestamp.
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google.protobuf.Timestamp current_time = 1;
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// A list of DetectedPersons.
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repeated DetectedPerson detected_persons = 2;
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}
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// Prediction output format for Generic Object Detection.
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message ObjectDetectionPredictionResult {
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// The entity info for annotations from object detection prediction result.
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message Entity {
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// Label id.
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int64 label_id = 1;
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// Human readable string of the label.
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string label_string = 2;
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}
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// Identified box contains location and the entity of the object.
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message IdentifiedBox {
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// Bounding Box in the normalized coordinates.
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message NormalizedBoundingBox {
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// Min in x coordinate.
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float xmin = 1;
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// Min in y coordinate.
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float ymin = 2;
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// Width of the bounding box.
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float width = 3;
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// Height of the bounding box.
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float height = 4;
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}
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// An unique id for this box.
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int64 box_id = 1;
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// Bounding Box in the normalized coordinates.
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NormalizedBoundingBox normalized_bounding_box = 2;
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// Confidence score associated with this box.
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float confidence_score = 3;
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// Entity of this box.
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Entity entity = 4;
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}
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// Current timestamp.
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google.protobuf.Timestamp current_time = 1;
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// A list of identified boxes.
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repeated IdentifiedBox identified_boxes = 2;
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}
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// Prediction output format for Image Object Detection.
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message ImageObjectDetectionPredictionResult {
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// The resource IDs of the AnnotationSpecs that had been identified, ordered
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// by the confidence score descendingly. It is the id segment instead of full
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// resource name.
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repeated int64 ids = 1;
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// The display names of the AnnotationSpecs that had been identified, order
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// matches the IDs.
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repeated string display_names = 2;
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// The Model's confidences in correctness of the predicted IDs, higher value
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// means higher confidence. Order matches the Ids.
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repeated float confidences = 3;
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// Bounding boxes, i.e. the rectangles over the image, that pinpoint
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// the found AnnotationSpecs. Given in order that matches the IDs. Each
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// bounding box is an array of 4 numbers `xMin`, `xMax`, `yMin`, and
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// `yMax`, which represent the extremal coordinates of the box. They are
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// relative to the image size, and the point 0,0 is in the top left
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// of the image.
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repeated google.protobuf.ListValue bboxes = 4;
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}
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// Prediction output format for Image and Text Classification.
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message ClassificationPredictionResult {
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// The resource IDs of the AnnotationSpecs that had been identified.
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repeated int64 ids = 1;
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// The display names of the AnnotationSpecs that had been identified, order
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// matches the IDs.
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repeated string display_names = 2;
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// The Model's confidences in correctness of the predicted IDs, higher value
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// means higher confidence. Order matches the Ids.
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repeated float confidences = 3;
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}
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// Prediction output format for Image Segmentation.
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message ImageSegmentationPredictionResult {
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// A PNG image where each pixel in the mask represents the category in which
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// the pixel in the original image was predicted to belong to. The size of
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// this image will be the same as the original image. The mapping between the
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// AnntoationSpec and the color can be found in model's metadata. The model
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// will choose the most likely category and if none of the categories reach
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// the confidence threshold, the pixel will be marked as background.
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string category_mask = 1;
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// A one channel image which is encoded as an 8bit lossless PNG. The size of
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// the image will be the same as the original image. For a specific pixel,
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// darker color means less confidence in correctness of the cateogry in the
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// categoryMask for the corresponding pixel. Black means no confidence and
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// white means complete confidence.
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string confidence_mask = 2;
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}
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// Prediction output format for Video Action Recognition.
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message VideoActionRecognitionPredictionResult {
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// Each IdentifiedAction is one particular identification of an action
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// specified with the AnnotationSpec id, display_name and the associated
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// confidence score.
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message IdentifiedAction {
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// The resource ID of the AnnotationSpec that had been identified.
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string id = 1;
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// The display name of the AnnotationSpec that had been identified.
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string display_name = 2;
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// The Model's confidence in correction of this identification, higher
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// value means higher confidence.
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float confidence = 3;
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}
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// The beginning, inclusive, of the video's time segment in which the
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// actions have been identified.
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google.protobuf.Timestamp segment_start_time = 1;
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// The end, inclusive, of the video's time segment in which the actions have
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// been identified. Particularly, if the end is the same as the start, it
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// means the identification happens on a specific video frame.
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google.protobuf.Timestamp segment_end_time = 2;
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// All of the actions identified in the time range.
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repeated IdentifiedAction actions = 3;
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}
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// Prediction output format for Video Object Tracking.
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message VideoObjectTrackingPredictionResult {
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// Boundingbox for detected object. I.e. the rectangle over the video frame
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// pinpointing the found AnnotationSpec. The coordinates are relative to the
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// frame size, and the point 0,0 is in the top left of the frame.
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message BoundingBox {
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// The leftmost coordinate of the bounding box.
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float x_min = 1;
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// The rightmost coordinate of the bounding box.
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float x_max = 2;
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// The topmost coordinate of the bounding box.
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float y_min = 3;
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// The bottommost coordinate of the bounding box.
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float y_max = 4;
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}
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// Each DetectedObject is one particular identification of an object
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// specified with the AnnotationSpec id and display_name, the bounding box,
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// the associated confidence score and the corresponding track_id.
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message DetectedObject {
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// The resource ID of the AnnotationSpec that had been identified.
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string id = 1;
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// The display name of the AnnotationSpec that had been identified.
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string display_name = 2;
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// Boundingbox.
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BoundingBox bounding_box = 3;
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// The Model's confidence in correction of this identification, higher
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// value means higher confidence.
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float confidence = 4;
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// The same object may be identified on muitiple frames which are typical
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// adjacent. The set of frames where a particular object has been detected
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// form a track. This track_id can be used to trace down all frames for an
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// detected object.
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int64 track_id = 5;
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}
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// The beginning, inclusive, of the video's time segment in which the
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// current identifications happens.
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google.protobuf.Timestamp segment_start_time = 1;
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// The end, inclusive, of the video's time segment in which the current
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// identifications happen. Particularly, if the end is the same as the start,
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// it means the identifications happen on a specific video frame.
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google.protobuf.Timestamp segment_end_time = 2;
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// All of the objects detected in the specified time range.
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repeated DetectedObject objects = 3;
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}
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// Prediction output format for Video Classification.
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message VideoClassificationPredictionResult {
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// Each IdentifiedClassification is one particular identification of an
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// classification specified with the AnnotationSpec id and display_name,
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// and the associated confidence score.
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message IdentifiedClassification {
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// The resource ID of the AnnotationSpec that had been identified.
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string id = 1;
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// The display name of the AnnotationSpec that had been identified.
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string display_name = 2;
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// The Model's confidence in correction of this identification, higher
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// value means higher confidence.
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float confidence = 3;
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}
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// The beginning, inclusive, of the video's time segment in which the
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// classifications have been identified.
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google.protobuf.Timestamp segment_start_time = 1;
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// The end, inclusive, of the video's time segment in which the
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// classifications have been identified. Particularly, if the end is the same
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// as the start, it means the identification happens on a specific video
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// frame.
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google.protobuf.Timestamp segment_end_time = 2;
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// All of the classifications identified in the time range.
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repeated IdentifiedClassification classifications = 3;
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}
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// The prediction result proto for occupancy counting.
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message OccupancyCountingPredictionResult {
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// The entity info for annotations from occupancy counting operator.
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message Entity {
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// Label id.
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int64 label_id = 1;
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// Human readable string of the label.
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string label_string = 2;
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}
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// Identified box contains location and the entity of the object.
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message IdentifiedBox {
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// Bounding Box in the normalized coordinates.
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message NormalizedBoundingBox {
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// Min in x coordinate.
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float xmin = 1;
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// Min in y coordinate.
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float ymin = 2;
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// Width of the bounding box.
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float width = 3;
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// Height of the bounding box.
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float height = 4;
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}
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// An unique id for this box.
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int64 box_id = 1;
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// Bounding Box in the normalized coordinates.
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NormalizedBoundingBox normalized_bounding_box = 2;
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// Confidence score associated with this box.
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float score = 3;
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// Entity of this box.
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Entity entity = 4;
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// An unique id to identify a track. It should be consistent across frames.
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// It only exists if tracking is enabled.
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int64 track_id = 5;
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}
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// The statistics info for annotations from occupancy counting operator.
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message Stats {
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// The object info and instant count for annotations from occupancy counting
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// operator.
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message ObjectCount {
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// Entity of this object.
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Entity entity = 1;
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// Count of the object.
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int32 count = 2;
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}
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// The object info and accumulated count for annotations from occupancy
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// counting operator.
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message AccumulatedObjectCount {
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// The start time of the accumulated count.
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google.protobuf.Timestamp start_time = 1;
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// The object count for the accumulated count.
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ObjectCount object_count = 2;
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}
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// Message for Crossing line count.
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message CrossingLineCount {
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// Line annotation from the user.
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StreamAnnotation annotation = 1;
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// The direction that follows the right hand rule.
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repeated ObjectCount positive_direction_counts = 2;
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// The direction that is opposite to the right hand rule.
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repeated ObjectCount negative_direction_counts = 3;
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// The accumulated positive count.
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repeated AccumulatedObjectCount accumulated_positive_direction_counts = 4;
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// The accumulated negative count.
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repeated AccumulatedObjectCount accumulated_negative_direction_counts = 5;
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}
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// Message for the active zone count.
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message ActiveZoneCount {
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// Active zone annotation from the user.
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StreamAnnotation annotation = 1;
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// Counts in the zone.
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repeated ObjectCount counts = 2;
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}
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// Counts of the full frame.
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repeated ObjectCount full_frame_count = 1;
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// Crossing line counts.
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repeated CrossingLineCount crossing_line_counts = 2;
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// Active zone counts.
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repeated ActiveZoneCount active_zone_counts = 3;
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}
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// The track info for annotations from occupancy counting operator.
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message TrackInfo {
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// An unique id to identify a track. It should be consistent across frames.
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string track_id = 1;
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// Start timestamp of this track.
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google.protobuf.Timestamp start_time = 2;
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}
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// The dwell time info for annotations from occupancy counting operator.
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message DwellTimeInfo {
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// An unique id to identify a track. It should be consistent across frames.
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string track_id = 1;
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// The unique id for the zone in which the object is dwelling/waiting.
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string zone_id = 2;
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// The beginning time when a dwelling object has been identified in a zone.
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google.protobuf.Timestamp dwell_start_time = 3;
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// The end time when a dwelling object has exited in a zone.
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google.protobuf.Timestamp dwell_end_time = 4;
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}
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// Current timestamp.
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google.protobuf.Timestamp current_time = 1;
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// A list of identified boxes.
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repeated IdentifiedBox identified_boxes = 2;
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// Detection statistics.
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Stats stats = 3;
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// Track related information. All the tracks that are live at this timestamp.
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// It only exists if tracking is enabled.
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repeated TrackInfo track_info = 4;
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// Dwell time related information. All the tracks that are live in a given
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// zone with a start and end dwell time timestamp
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repeated DwellTimeInfo dwell_time_info = 5;
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// The presentation timestamp of the frame.
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optional int64 pts = 6;
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}
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// message about annotations about Vision AI stream resource.
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message StreamAnnotation {
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oneof annotation_payload {
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// Annotation for type ACTIVE_ZONE
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NormalizedPolygon active_zone = 5;
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// Annotation for type CROSSING_LINE
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NormalizedPolyline crossing_line = 6;
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}
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// ID of the annotation. It must be unique when used in the certain context.
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// For example, all the annotations to one input streams of a Vision AI
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// application.
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string id = 1;
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// User-friendly name for the annotation.
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string display_name = 2;
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// The Vision AI stream resource name.
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string source_stream = 3;
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// The actual type of Annotation.
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StreamAnnotationType type = 4;
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}
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// A wrapper of repeated StreamAnnotation.
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message StreamAnnotations {
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// Multiple annotations.
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repeated StreamAnnotation stream_annotations = 1;
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}
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// Normalized Polygon.
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message NormalizedPolygon {
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// The bounding polygon normalized vertices. Top left corner of the image
|
||
// will be [0, 0].
|
||
repeated NormalizedVertex normalized_vertices = 1;
|
||
}
|
||
|
||
// Normalized Pplyline, which represents a curve consisting of connected
|
||
// straight-line segments.
|
||
message NormalizedPolyline {
|
||
// A sequence of vertices connected by straight lines.
|
||
repeated NormalizedVertex normalized_vertices = 1;
|
||
}
|
||
|
||
// 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.
|
||
message NormalizedVertex {
|
||
// X coordinate.
|
||
float x = 1;
|
||
|
||
// Y coordinate.
|
||
float y = 2;
|
||
}
|
||
|
||
// Message of essential metadata of App Platform.
|
||
// This message is usually attached to a certain processor output annotation for
|
||
// customer to identify the source of the data.
|
||
message AppPlatformMetadata {
|
||
// The application resource name.
|
||
string application = 1;
|
||
|
||
// The instance resource id. Instance is the nested resource of application
|
||
// under collection 'instances'.
|
||
string instance_id = 2;
|
||
|
||
// The node name of the application graph.
|
||
string node = 3;
|
||
|
||
// The referred processor resource name of the application node.
|
||
string processor = 4;
|
||
}
|
||
|
||
// For any cloud function based customer processing logic, customer's cloud
|
||
// function is expected to receive AppPlatformCloudFunctionRequest as request
|
||
// and send back AppPlatformCloudFunctionResponse as response.
|
||
// Message of request from AppPlatform to Cloud Function.
|
||
message AppPlatformCloudFunctionRequest {
|
||
// A general annotation message that uses struct format to represent different
|
||
// concrete annotation protobufs.
|
||
message StructedInputAnnotation {
|
||
// The ingestion time of the current annotation.
|
||
int64 ingestion_time_micros = 1;
|
||
|
||
// The struct format of the actual annotation.
|
||
google.protobuf.Struct annotation = 2;
|
||
}
|
||
|
||
// The metadata of the AppPlatform for customer to identify the source of the
|
||
// payload.
|
||
AppPlatformMetadata app_platform_metadata = 1;
|
||
|
||
// The actual annotations to be processed by the customized Cloud Function.
|
||
repeated StructedInputAnnotation annotations = 2;
|
||
}
|
||
|
||
// Message of the response from customer's Cloud Function to AppPlatform.
|
||
message AppPlatformCloudFunctionResponse {
|
||
// A general annotation message that uses struct format to represent different
|
||
// concrete annotation protobufs.
|
||
message StructedOutputAnnotation {
|
||
// The struct format of the actual annotation.
|
||
google.protobuf.Struct annotation = 1;
|
||
}
|
||
|
||
// The modified annotations that is returned back to AppPlatform.
|
||
// If the annotations fields are empty, then those annotations will be dropped
|
||
// by AppPlatform.
|
||
repeated StructedOutputAnnotation annotations = 2;
|
||
|
||
// If set to true, AppPlatform will use original annotations instead of
|
||
// dropping them, even if it is empty in the annotations filed.
|
||
bool annotation_passthrough = 3;
|
||
|
||
// The event notifications that is returned back to AppPlatform. Typically it
|
||
// will then be configured to be consumed/forwared to a operator that handles
|
||
// events, such as Pub/Sub operator.
|
||
repeated AppPlatformEventBody events = 4;
|
||
}
|
||
|
||
// Message of content of appPlatform event
|
||
message AppPlatformEventBody {
|
||
// Human readable string of the event like "There are more than 6 people in
|
||
// the scene". or "Shelf is empty!".
|
||
string event_message = 1;
|
||
|
||
// For the case of Pub/Sub, it will be stored in the message attributes.
|
||
// pubsub.proto
|
||
google.protobuf.Struct payload = 2;
|
||
|
||
// User defined Event Id, used to classify event, within a delivery interval,
|
||
// events from the same application instance with the same id will be
|
||
// de-duplicated & only first one will be sent out. Empty event_id will be
|
||
// treated as "".
|
||
string event_id = 3;
|
||
}
|