// Copyright 2020 Google LLC // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. syntax = "proto3"; package google.cloud.automl.v1; import "google/api/annotations.proto"; import "google/api/client.proto"; import "google/api/field_behavior.proto"; import "google/api/resource.proto"; import "google/cloud/automl/v1/annotation_payload.proto"; import "google/cloud/automl/v1/data_items.proto"; import "google/cloud/automl/v1/io.proto"; import "google/cloud/automl/v1/operations.proto"; import "google/longrunning/operations.proto"; option csharp_namespace = "Google.Cloud.AutoML.V1"; option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1;automl"; option java_multiple_files = true; option java_outer_classname = "PredictionServiceProto"; option java_package = "com.google.cloud.automl.v1"; option php_namespace = "Google\\Cloud\\AutoMl\\V1"; option ruby_package = "Google::Cloud::AutoML::V1"; // AutoML Prediction API. // // On any input that is documented to expect a string parameter in // snake_case or kebab-case, either of those cases is accepted. service PredictionService { option (google.api.default_host) = "automl.googleapis.com"; option (google.api.oauth_scopes) = "https://www.googleapis.com/auth/cloud-platform"; // Perform an online prediction. The prediction result is directly // returned in the response. // Available for following ML scenarios, and their expected request payloads: // // AutoML Vision Classification // // * An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB. // // AutoML Vision Object Detection // // * An image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB. // // AutoML Natural Language Classification // // * A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in // .PDF, .TIF or .TIFF format with size upto 2MB. // // AutoML Natural Language Entity Extraction // // * A TextSnippet up to 10,000 characters, UTF-8 NFC encoded or a document // in .PDF, .TIF or .TIFF format with size upto 20MB. // // AutoML Natural Language Sentiment Analysis // // * A TextSnippet up to 60,000 characters, UTF-8 encoded or a document in // .PDF, .TIF or .TIFF format with size upto 2MB. // // AutoML Translation // // * A TextSnippet up to 25,000 characters, UTF-8 encoded. // // AutoML Tables // // * A row with column values matching // the columns of the model, up to 5MB. Not available for FORECASTING // `prediction_type`. rpc Predict(PredictRequest) returns (PredictResponse) { option (google.api.http) = { post: "/v1/{name=projects/*/locations/*/models/*}:predict" body: "*" }; option (google.api.method_signature) = "name,payload,params"; } // Perform a batch prediction. Unlike the online [Predict][google.cloud.automl.v1.PredictionService.Predict], batch // prediction result won't be immediately available in the response. Instead, // a long running operation object is returned. User can poll the operation // result via [GetOperation][google.longrunning.Operations.GetOperation] // method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1.BatchPredictResult] is returned in // the [response][google.longrunning.Operation.response] field. // Available for following ML scenarios: // // * AutoML Vision Classification // * AutoML Vision Object Detection // * AutoML Video Intelligence Classification // * AutoML Video Intelligence Object Tracking * AutoML Natural Language Classification // * AutoML Natural Language Entity Extraction // * AutoML Natural Language Sentiment Analysis // * AutoML Tables rpc BatchPredict(BatchPredictRequest) returns (google.longrunning.Operation) { option (google.api.http) = { post: "/v1/{name=projects/*/locations/*/models/*}:batchPredict" body: "*" }; option (google.api.method_signature) = "name,input_config,output_config,params"; option (google.longrunning.operation_info) = { response_type: "BatchPredictResult" metadata_type: "OperationMetadata" }; } } // Request message for [PredictionService.Predict][google.cloud.automl.v1.PredictionService.Predict]. message PredictRequest { // Required. Name of the model requested to serve the prediction. string name = 1 [ (google.api.field_behavior) = REQUIRED, (google.api.resource_reference) = { type: "automl.googleapis.com/Model" } ]; // Required. Payload to perform a prediction on. The payload must match the // problem type that the model was trained to solve. ExamplePayload payload = 2 [(google.api.field_behavior) = REQUIRED]; // Additional domain-specific parameters, any string must be up to 25000 // characters long. // // AutoML Vision Classification // // `score_threshold` // : (float) A value from 0.0 to 1.0. When the model // makes predictions for an image, it will only produce results that have // at least this confidence score. The default is 0.5. // // AutoML Vision Object Detection // // `score_threshold` // : (float) When Model detects objects on the image, // it will only produce bounding boxes which have at least this // confidence score. Value in 0 to 1 range, default is 0.5. // // `max_bounding_box_count` // : (int64) The maximum number of bounding // boxes returned. The default is 100. The // number of returned bounding boxes might be limited by the server. // // AutoML Tables // // `feature_importance` // : (boolean) Whether // // [feature_importance][google.cloud.automl.v1.TablesModelColumnInfo.feature_importance] // is populated in the returned list of // [TablesAnnotation][google.cloud.automl.v1.TablesAnnotation] // objects. The default is false. map params = 3; } // Response message for [PredictionService.Predict][google.cloud.automl.v1.PredictionService.Predict]. message PredictResponse { // Prediction result. // AutoML Translation and AutoML Natural Language Sentiment Analysis // return precisely one payload. repeated AnnotationPayload payload = 1; // The preprocessed example that AutoML actually makes prediction on. // Empty if AutoML does not preprocess the input example. // // For AutoML Natural Language (Classification, Entity Extraction, and // Sentiment Analysis), if the input is a document, the recognized text is // returned in the // [document_text][google.cloud.automl.v1.Document.document_text] // property. ExamplePayload preprocessed_input = 3; // Additional domain-specific prediction response metadata. // // AutoML Vision Object Detection // // `max_bounding_box_count` // : (int64) The maximum number of bounding boxes to return per image. // // AutoML Natural Language Sentiment Analysis // // `sentiment_score` // : (float, deprecated) A value between -1 and 1, // -1 maps to least positive sentiment, while 1 maps to the most positive // one and the higher the score, the more positive the sentiment in the // document is. Yet these values are relative to the training data, so // e.g. if all data was positive then -1 is also positive (though // the least). // `sentiment_score` is not the same as "score" and "magnitude" // from Sentiment Analysis in the Natural Language API. map metadata = 2; } // Request message for [PredictionService.BatchPredict][google.cloud.automl.v1.PredictionService.BatchPredict]. message BatchPredictRequest { // Required. Name of the model requested to serve the batch prediction. string name = 1 [ (google.api.field_behavior) = REQUIRED, (google.api.resource_reference) = { type: "automl.googleapis.com/Model" } ]; // Required. The input configuration for batch prediction. BatchPredictInputConfig input_config = 3 [(google.api.field_behavior) = REQUIRED]; // Required. The Configuration specifying where output predictions should // be written. BatchPredictOutputConfig output_config = 4 [(google.api.field_behavior) = REQUIRED]; // Additional domain-specific parameters for the predictions, any string must // be up to 25000 characters long. // // AutoML Natural Language Classification // // `score_threshold` // : (float) A value from 0.0 to 1.0. When the model // makes predictions for a text snippet, it will only produce results // that have at least this confidence score. The default is 0.5. // // // AutoML Vision Classification // // `score_threshold` // : (float) A value from 0.0 to 1.0. When the model // makes predictions for an image, it will only produce results that // have at least this confidence score. The default is 0.5. // // AutoML Vision Object Detection // // `score_threshold` // : (float) When Model detects objects on the image, // it will only produce bounding boxes which have at least this // confidence score. Value in 0 to 1 range, default is 0.5. // // `max_bounding_box_count` // : (int64) The maximum number of bounding // boxes returned per image. The default is 100, the // number of bounding boxes returned might be limited by the server. // AutoML Video Intelligence Classification // // `score_threshold` // : (float) A value from 0.0 to 1.0. When the model // makes predictions for a video, it will only produce results that // have at least this confidence score. The default is 0.5. // // `segment_classification` // : (boolean) Set to true to request // segment-level classification. AutoML Video Intelligence returns // labels and their confidence scores for the entire segment of the // video that user specified in the request configuration. // The default is true. // // `shot_classification` // : (boolean) Set to true to request shot-level // classification. AutoML Video Intelligence determines the boundaries // for each camera shot in the entire segment of the video that user // specified in the request configuration. AutoML Video Intelligence // then returns labels and their confidence scores for each detected // shot, along with the start and end time of the shot. // The default is false. // // WARNING: Model evaluation is not done for this classification type, // the quality of it depends on training data, but there are no metrics // provided to describe that quality. // // `1s_interval_classification` // : (boolean) Set to true to request // classification for a video at one-second intervals. AutoML Video // Intelligence returns labels and their confidence scores for each // second of the entire segment of the video that user specified in the // request configuration. The default is false. // // WARNING: Model evaluation is not done for this classification // type, the quality of it depends on training data, but there are no // metrics provided to describe that quality. // // AutoML Video Intelligence Object Tracking // // `score_threshold` // : (float) When Model detects objects on video frames, // it will only produce bounding boxes which have at least this // confidence score. Value in 0 to 1 range, default is 0.5. // // `max_bounding_box_count` // : (int64) The maximum number of bounding // boxes returned per image. The default is 100, the // number of bounding boxes returned might be limited by the server. // // `min_bounding_box_size` // : (float) Only bounding boxes with shortest edge // at least that long as a relative value of video frame size are // returned. Value in 0 to 1 range. Default is 0. // map params = 5; } // Result of the Batch Predict. This message is returned in // [response][google.longrunning.Operation.response] of the operation returned // by the [PredictionService.BatchPredict][google.cloud.automl.v1.PredictionService.BatchPredict]. message BatchPredictResult { // Additional domain-specific prediction response metadata. // // AutoML Vision Object Detection // // `max_bounding_box_count` // : (int64) The maximum number of bounding boxes returned per image. // // AutoML Video Intelligence Object Tracking // // `max_bounding_box_count` // : (int64) The maximum number of bounding boxes returned per frame. map metadata = 1; }