e3e7e7ddb0
Provides defined Message types for formatting data assigned to protobuf.Value fields in AI Platform. PiperOrigin-RevId: 342967619
481 lines
19 KiB
Protocol Buffer
481 lines
19 KiB
Protocol Buffer
// Copyright 2020 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.aiplatform.v1beta1.schema;
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import "google/cloud/aiplatform/v1beta1/schema/annotation_spec_color.proto";
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import "google/cloud/aiplatform/v1beta1/schema/geometry.proto";
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import "google/protobuf/duration.proto";
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import "google/protobuf/struct.proto";
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import "google/protobuf/wrappers.proto";
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import "google/api/annotations.proto";
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option go_package = "google.golang.org/genproto/googleapis/cloud/aiplatform/v1beta1/schema;schema";
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option java_multiple_files = true;
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option java_outer_classname = "IoFormatProto";
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option java_package = "com.google.cloud.aiplatform.v1beta1.schema";
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// Prediction input format for Image Classification.
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message ImageClassificationPredictionInstance {
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// The image bytes or GCS URI to make the prediction on.
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string content = 1;
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// The MIME type of the content of the image. Only the images in below listed
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// MIME types are supported.
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// - image/jpeg
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// - image/gif
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// - image/png
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// - image/webp
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// - image/bmp
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// - image/tiff
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// - image/vnd.microsoft.icon
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string mime_type = 2;
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}
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// Prediction input format for Image Object Detection.
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message ImageObjectDetectionPredictionInstance {
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// The image bytes or GCS URI to make the prediction on.
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string content = 1;
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// The MIME type of the content of the image. Only the images in below listed
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// MIME types are supported.
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// - image/jpeg
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// - image/gif
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// - image/png
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// - image/webp
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// - image/bmp
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// - image/tiff
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// - image/vnd.microsoft.icon
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string mime_type = 2;
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}
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// Prediction input format for Image Segmentation.
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message ImageSegmentationPredictionInstance {
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// The image bytes to make the predictions on.
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string content = 1;
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// The MIME type of the content of the image. Only the images in below listed
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// MIME types are supported.
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// - image/jpeg
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// - image/png
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string mime_type = 2;
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}
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// Prediction input format for Video Classification.
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message VideoClassificationPredictionInstance {
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// The Google Cloud Storage location of the video on which to perform the
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// prediction.
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string content = 1;
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// The MIME type of the content of the video. Only the following are
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// supported: video/mp4 video/avi video/quicktime
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string mime_type = 2;
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// The beginning, inclusive, of the video's time segment on which to perform
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// the prediction. Expressed as a number of seconds as measured from the
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// start of the video, with "s" appended at the end. Fractions are allowed,
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// up to a microsecond precision.
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string time_segment_start = 3;
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// The end, exclusive, of the video's time segment on which to perform
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// the prediction. Expressed as a number of seconds as measured from the
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// start of the video, with "s" appended at the end. Fractions are allowed,
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// up to a microsecond precision, and "Infinity" is allowed, which means the
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// end of the video.
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string time_segment_end = 4;
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}
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// Prediction input format for Video Classification.
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message VideoObjectTrackingPredictionInstance {
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// The Google Cloud Storage location of the video on which to perform the
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// prediction.
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string content = 1;
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// The MIME type of the content of the video. Only the following are
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// supported: video/mp4 video/avi video/quicktime
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string mime_type = 2;
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// The beginning, inclusive, of the video's time segment on which to perform
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// the prediction. Expressed as a number of seconds as measured from the
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// start of the video, with "s" appended at the end. Fractions are allowed,
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// up to a microsecond precision.
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string time_segment_start = 3;
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// The end, exclusive, of the video's time segment on which to perform
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// the prediction. Expressed as a number of seconds as measured from the
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// start of the video, with "s" appended at the end. Fractions are allowed,
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// up to a microsecond precision, and "Infinity" is allowed, which means the
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// end of the video.
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string time_segment_end = 4;
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}
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// Prediction input format for Video Action Recognition.
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message VideoActionRecognitionPredictionInstance {
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// The Google Cloud Storage location of the video on which to perform the
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// prediction.
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string content = 1;
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// The MIME type of the content of the video. Only the following are
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// supported: video/mp4 video/avi video/quicktime
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string mime_type = 2;
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// The beginning, inclusive, of the video's time segment on which to perform
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// the prediction. Expressed as a number of seconds as measured from the
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// start of the video, with "s" appended at the end. Fractions are allowed,
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// up to a microsecond precision.
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string time_segment_start = 3;
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// The end, exclusive, of the video's time segment on which to perform
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// the prediction. Expressed as a number of seconds as measured from the
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// start of the video, with "s" appended at the end. Fractions are allowed,
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// up to a microsecond precision, and "Infinity" is allowed, which means the
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// end of the video.
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string time_segment_end = 4;
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}
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// Prediction input format for Text Classification.
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message TextClassificationPredictionInstance {
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// The text snippet to make the predictions on.
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string content = 1;
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// The MIME type of the text snippet. The supported MIME types are listed
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// below.
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// - text/plain
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string mime_type = 2;
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}
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// Prediction input format for Text Sentiment.
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message TextSentimentPredictionInstance {
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// The text snippet to make the predictions on.
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string content = 1;
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// The MIME type of the text snippet. The supported MIME types are listed
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// below.
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// - text/plain
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string mime_type = 2;
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}
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// Prediction input format for Text Extraction.
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message TextExtractionPredictionInstance {
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// The text snippet to make the predictions on.
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string content = 1;
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// The MIME type of the text snippet. The supported MIME types are listed
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// below.
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// - text/plain
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string mime_type = 2;
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// This field is only used for batch prediction. If a key is provided, the
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// batch prediction result will by mapped to this key. If omitted, then the
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// batch prediction result will contain the entire input instance. AI Platform
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// will not check if keys in the request are duplicates, so it is up to the
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// caller to ensure the keys are unique.
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string key = 3;
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}
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// Prediction model parameters for Image Classification.
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message ImageClassificationPredictionParams {
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// The Model only returns predictions with at least this confidence score.
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// Default value is 0.0
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float confidence_threshold = 1;
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// The Model only returns up to that many top, by confidence score,
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// predictions per instance. If this number is very high, the Model may return
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// fewer predictions. Default value is 10.
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int32 max_predictions = 2;
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}
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// Prediction model parameters for Image Object Detection.
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message ImageObjectDetectionPredictionParams {
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// The Model only returns predictions with at least this confidence score.
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// Default value is 0.0
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float confidence_threshold = 1;
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// The Model only returns up to that many top, by confidence score,
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// predictions per instance. Note that number of returned predictions is also
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// limited by metadata's predictionsLimit. Default value is 10.
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int32 max_predictions = 2;
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}
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// Prediction model parameters for Image Segmentation.
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message ImageSegmentationPredictionParams {
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// When the model predicts category of pixels of the image, it will only
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// provide predictions for pixels that it is at least this much confident
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// about. All other pixels will be classified as background. Default value is
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// 0.5.
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float confidence_threshold = 1;
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}
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// Prediction model parameters for Video Classification.
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message VideoClassificationPredictionParams {
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// The Model only returns predictions with at least this confidence score.
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// Default value is 0.0
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float confidence_threshold = 1;
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// The Model only returns up to that many top, by confidence score,
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// predictions per instance. If this number is very high, the Model may return
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// fewer predictions. Default value is 10,000.
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int32 max_predictions = 2;
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// Set to true to request segment-level classification. AI Platform returns
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// labels and their confidence scores for the entire time segment of the
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// video that user specified in the input instance.
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// Default value is true
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bool segment_classification = 3;
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// Set to true to request shot-level classification. AI Platform determines
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// the boundaries for each camera shot in the entire time segment of the
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// video that user specified in the input instance. AI Platform then
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// returns labels and their confidence scores for each detected shot, along
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// with the start and end time of the shot.
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// WARNING: Model evaluation is not done for this classification type,
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// the quality of it depends on the training data, but there are no metrics
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// provided to describe that quality.
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// Default value is false
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bool shot_classification = 4;
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// Set to true to request classification for a video at one-second intervals.
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// AI Platform returns labels and their confidence scores for each second of
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// the entire time segment of the video that user specified in the input
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// WARNING: Model evaluation is not done for this classification type, the
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// quality of it depends on the training data, but there are no metrics
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// provided to describe that quality. Default value is false
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bool one_sec_interval_classification = 5;
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}
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// Prediction model parameters for Video Object Tracking.
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message VideoObjectTrackingPredictionParams {
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// The Model only returns predictions with at least this confidence score.
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// Default value is 0.0
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float confidence_threshold = 1;
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// The model only returns up to that many top, by confidence score,
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// predictions per frame of the video. If this number is very high, the
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// Model may return fewer predictions per frame. Default value is 50.
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int32 max_predictions = 2;
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// Only bounding boxes with shortest edge at least that long as a relative
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// value of video frame size are returned. Default value is 0.0.
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float min_bounding_box_size = 3;
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}
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// Prediction model parameters for Video Action Recognition.
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message VideoActionRecognitionPredictionParams {
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// The Model only returns predictions with at least this confidence score.
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// Default value is 0.0
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float confidence_threshold = 1;
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// The model only returns up to that many top, by confidence score,
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// predictions per frame of the video. If this number is very high, the
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// Model may return fewer predictions per frame. Default value is 50.
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int32 max_predictions = 2;
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}
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// Represents a line of JSONL in the batch prediction output file.
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message PredictionResult {
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// Some identifier from the input so that the prediction can be mapped back to
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// the input instance.
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oneof input {
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// User's input instance.
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// Struct is used here instead of Any so that JsonFormat does not append an
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// extra "@type" field when we convert the proto to JSON.
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google.protobuf.Struct instance = 1;
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// Optional user-provided key from the input instance.
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string key = 2;
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}
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// The prediction result.
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// Value is used here instead of Any so that JsonFormat does not append an
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// extra "@type" field when we convert the proto to JSON and so we can
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// represent array of objects.
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google.protobuf.Value prediction = 3;
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}
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// Represents a line of JSONL in the text sentiment batch prediction output
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// file. This is a hack to allow printing of integer values.
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message TextSentimentPredictionResult {
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// Prediction output format for Text Sentiment.
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message Prediction {
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// The integer sentiment labels between 0 (inclusive) and sentimentMax label
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// (inclusive), while 0 maps to the least positive sentiment and
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// sentimentMax maps to the most positive one. The higher the score is, the
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// more positive the sentiment in the text snippet is. Note: sentimentMax is
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// an integer value between 1 (inclusive) and 10 (inclusive).
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int32 sentiment = 1;
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}
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// User's input instance.
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TextSentimentPredictionInstance instance = 1;
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// The prediction result.
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Prediction prediction = 2;
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}
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// Prediction output format for Image Classification.
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message ClassificationPredictionResult {
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// The resource IDs of the AnnotationSpecs that had been identified, ordered
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// by the confidence score descendingly.
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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 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.
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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 Video Classification.
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message VideoClassificationPredictionResult {
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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 type of the prediction. The requested types can be configured
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// via parameters. This will be one of
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// - segment-classification
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// - shot-classification
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// - one-sec-interval-classification
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string type = 3;
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// The beginning, inclusive, of the video's time segment in which the
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// AnnotationSpec has been identified. Expressed as a number of seconds as
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// measured from the start of the video, with fractions up to a microsecond
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// precision, and with "s" appended at the end. Note that for
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// 'segment-classification' prediction type, this equals the original
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// 'timeSegmentStart' from the input instance, for other types it is the
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// start of a shot or a 1 second interval respectively.
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google.protobuf.Duration time_segment_start = 4;
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// The end, exclusive, of the video's time segment in which the
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// AnnotationSpec has been identified. Expressed as a number of seconds as
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// measured from the start of the video, with fractions up to a microsecond
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// precision, and with "s" appended at the end. Note that for
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// 'segment-classification' prediction type, this equals the original
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// 'timeSegmentEnd' from the input instance, for other types it is the end
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// of a shot or a 1 second interval respectively.
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google.protobuf.Duration time_segment_end = 5;
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// The Model's confidence in correction of this prediction, higher
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// value means higher confidence.
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google.protobuf.FloatValue confidence = 6;
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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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// The fields `xMin`, `xMax`, `yMin`, and `yMax` refer to a bounding box,
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// i.e. the rectangle over the video frame pinpointing the found
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// AnnotationSpec. The coordinates are relative to the frame size, and the
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// point 0,0 is in the top left of the frame.
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message Frame {
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// A time (frame) of a video in which the object has been detected.
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// Expressed as a number of seconds as measured from the
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// start of the video, with fractions up to a microsecond precision, and
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// with "s" appended at the end.
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google.protobuf.Duration time_offset = 1;
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// The leftmost coordinate of the bounding box.
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google.protobuf.FloatValue x_min = 2;
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// The rightmost coordinate of the bounding box.
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google.protobuf.FloatValue x_max = 3;
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// The topmost coordinate of the bounding box.
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google.protobuf.FloatValue y_min = 4;
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// The bottommost coordinate of the bounding box.
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google.protobuf.FloatValue y_max = 5;
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}
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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 beginning, inclusive, of the video's time segment in which the
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// object instance has been detected. Expressed as a number of seconds as
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// measured from the start of the video, with fractions up to a microsecond
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// precision, and with "s" appended at the end.
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google.protobuf.Duration time_segment_start = 3;
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// The end, inclusive, of the video's time segment in which the
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// object instance has been detected. Expressed as a number of seconds as
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// measured from the start of the video, with fractions up to a microsecond
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// precision, and with "s" appended at the end.
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google.protobuf.Duration time_segment_end = 4;
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// The Model's confidence in correction of this prediction, higher
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// value means higher confidence.
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google.protobuf.FloatValue confidence = 5;
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// All of the frames of the video in which a single object instance has been
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// detected. The bounding boxes in the frames identify the same object.
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repeated Frame frames = 6;
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}
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// Prediction output format for Text Extraction.
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message TextExtractionPredictionResult {
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// The resource IDs of the AnnotationSpecs that had been identified,
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// ordered by the confidence score descendingly.
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repeated int64 ids = 1;
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// The display names of the AnnotationSpecs that had been identified,
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// order matches the IDs.
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repeated string display_names = 2;
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// The start offsets, inclusive, of the text segment in which the
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// AnnotationSpec has been identified. Expressed as a zero-based number
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// of characters as measured from the start of the text snippet.
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repeated int64 text_segment_start_offsets = 3;
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// The end offsets, inclusive, of the text segment in which the
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// AnnotationSpec has been identified. Expressed as a zero-based number
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// of characters as measured from the start of the text snippet.
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repeated int64 text_segment_end_offsets = 4;
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// The Model's confidences in correctness of the predicted IDs, higher
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// value means higher confidence. Order matches the Ids.
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repeated float confidences = 5;
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}
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