private/google/cloud/automl/v1beta1/prediction_service.proto
// 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.v1beta1;
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/v1beta1/annotation_payload.proto";
import "google/cloud/automl/v1beta1/data_items.proto";
import "google/cloud/automl/v1beta1/io.proto";
import "google/cloud/automl/v1beta1/operations.proto";
import "google/longrunning/operations.proto";
option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
option java_multiple_files = true;
option java_outer_classname = "PredictionServiceProto";
option java_package = "com.google.cloud.automl.v1beta1";
option php_namespace = "Google\\Cloud\\AutoMl\\V1beta1";
option ruby_package = "Google::Cloud::AutoML::V1beta1";
// 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 will be directly
// returned in the response.
// Available for following ML problems, and their expected request payloads:
// * Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes
// up to 30MB.
// * Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes
// up to 30MB.
// * Text Classification - TextSnippet, content up to 60,000 characters,
// UTF-8 encoded.
// * Text Extraction - TextSnippet, content up to 30,000 characters,
// UTF-8 NFC encoded.
// * Translation - TextSnippet, content up to 25,000 characters, UTF-8
// encoded.
// * Tables - Row, with column values matching the columns of the model,
// up to 5MB. Not available for FORECASTING
//
// [prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type].
// * Text Sentiment - TextSnippet, content up 500 characters, UTF-8
// encoded.
rpc Predict(PredictRequest) returns (PredictResponse) {
option (google.api.http) = {
post: "/v1beta1/{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.v1beta1.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.v1beta1.BatchPredictResult] is returned in
// the [response][google.longrunning.Operation.response] field.
// Available for following ML problems:
// * Image Classification
// * Image Object Detection
// * Video Classification
// * Video Object Tracking * Text Extraction
// * Tables
rpc BatchPredict(BatchPredictRequest) returns (google.longrunning.Operation) {
option (google.api.http) = {
post: "/v1beta1/{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.v1beta1.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.
//
// * For Image 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.
//
// * For Image 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) No more than this number of bounding
// boxes will be returned in the response. Default is 100, the
// requested value may be limited by server.
// * For Tables:
// feature_imp<span>ortan</span>ce - (boolean) Whether feature importance
// should be populated in the returned TablesAnnotation.
// The default is false.
map<string, string> params = 3;
}
// Response message for [PredictionService.Predict][google.cloud.automl.v1beta1.PredictionService.Predict].
message PredictResponse {
// Prediction result.
// Translation and Text Sentiment will 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 Text Extraction:
// If the input is a .pdf file, the OCR'ed text will be provided in
// [document_text][google.cloud.automl.v1beta1.Document.document_text].
ExamplePayload preprocessed_input = 3;
// Additional domain-specific prediction response metadata.
//
// * For Image Object Detection:
// `max_bounding_box_count` - (int64) At most that many bounding boxes per
// image could have been returned.
//
// * For Text Sentiment:
// `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 will be also positive (though
// the least).
// The sentiment_score shouldn't be confused with "score" or "magnitude"
// from the previous Natural Language Sentiment Analysis API.
map<string, string> metadata = 2;
}
// Request message for [PredictionService.BatchPredict][google.cloud.automl.v1beta1.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];
// Required. Additional domain-specific parameters for the predictions, any string must
// be up to 25000 characters long.
//
// * For Text 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.
//
// * For Image 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.
//
// * For Image 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) No more than this number of bounding
// boxes will be produced per image. Default is 100, the
// requested value may be limited by server.
//
// * For Video 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.
// 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. The default is "false".
// `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.
// 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. The default is
// "false".
//
// * For Tables:
//
// feature_imp<span>ortan</span>ce - (boolean) Whether feature importance
// should be populated in the returned TablesAnnotations. The
// default is false.
//
// * For Video 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) No more than this number of bounding
// boxes will be returned per frame. Default is 100, the requested
// value may be limited by server.
// `min_bounding_box_size` - (float) Only bounding boxes with shortest edge
// at least that long as a relative value of video frame size will be
// returned. Value in 0 to 1 range. Default is 0.
map<string, string> params = 5 [(google.api.field_behavior) = REQUIRED];
}
// 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.v1beta1.PredictionService.BatchPredict].
message BatchPredictResult {
// Additional domain-specific prediction response metadata.
//
// * For Image Object Detection:
// `max_bounding_box_count` - (int64) At most that many bounding boxes per
// image could have been returned.
//
// * For Video Object Tracking:
// `max_bounding_box_count` - (int64) At most that many bounding boxes per
// frame could have been returned.
map<string, string> metadata = 1;
}