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feat: introduces configuration, e.g., dimensions, for doc prediction
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@yoshi-automation @bcoe
yoshi-automation authored and bcoe committed Aug 26, 2019
1 parent 01aa9d6 commit 9c8ce64
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126 changes: 122 additions & 4 deletions protos/google/cloud/automl/v1beta1/data_items.proto
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Original file line number Diff line number Diff line change
Expand Up @@ -17,11 +17,13 @@ syntax = "proto3";

package google.cloud.automl.v1beta1;

import "google/api/annotations.proto";
import "google/cloud/automl/v1beta1/geometry.proto";
import "google/cloud/automl/v1beta1/io.proto";
import "google/cloud/automl/v1beta1/text_segment.proto";
import "google/protobuf/any.proto";
import "google/protobuf/duration.proto";
import "google/protobuf/struct.proto";
import "google/api/annotations.proto";

option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
option java_multiple_files = true;
Expand Down Expand Up @@ -56,19 +58,135 @@ message TextSnippet {
// characters long.
string content = 1;

// Optional. The format of [content][google.cloud.automl.v1beta1.TextSnippet.content]. Currently the only two allowed
// values are "text/html" and "text/plain". If left blank, the format is
// automatically determined from the type of the uploaded [content][google.cloud.automl.v1beta1.TextSnippet.content].
// Optional. The format of
// [content][google.cloud.automl.v1beta1.TextSnippet.content]. Currently the
// only two allowed values are "text/html" and "text/plain". If left blank,
// the format is automatically determined from the type of the uploaded
// [content][google.cloud.automl.v1beta1.TextSnippet.content].
string mime_type = 2;

// Output only. HTTP URI where you can download the content.
string content_uri = 4;
}

// Message that describes dimension of a document.
message DocumentDimensions {
// Unit of the document dimension.
enum DocumentDimensionUnit {
// Should not be used.
DOCUMENT_DIMENSION_UNIT_UNSPECIFIED = 0;

// Document dimension is measured in inches.
INCH = 1;

// Document dimension is measured in centimeters.
CENTIMETER = 2;

// Document dimension is measured in points. 72 points = 1 inch.
POINT = 3;
}

// Unit of the dimension.
DocumentDimensionUnit unit = 1;

// Width value of the document, works together with the unit.
float width = 2;

// Height value of the document, works together with the unit.
float height = 3;
}

// A structured text document e.g. a PDF.
message Document {
// Describes the layout information of a
// [text_segment][google.cloud.automl.v1beta1.Document.Layout.text_segment] in
// the document.
message Layout {
// The type of TextSegment in the context of the original document.
enum TextSegmentType {
// Should not be used.
TEXT_SEGMENT_TYPE_UNSPECIFIED = 0;

// The text segment is a token. e.g. word.
TOKEN = 1;

// The text segment is a paragraph.
PARAGRAPH = 2;

// The text segment is a form field.
FORM_FIELD = 3;

// The text segment is the name part of a form field. It will be treated
// as child of another FORM_FIELD TextSegment if its span is subspan of
// another TextSegment with type FORM_FIELD.
FORM_FIELD_NAME = 4;

// The text segment is the text content part of a form field. It will be
// treated as child of another FORM_FIELD TextSegment if its span is
// subspan of another TextSegment with type FORM_FIELD.
FORM_FIELD_CONTENTS = 5;

// The text segment is a whole table, including headers, and all rows.
TABLE = 6;

// The text segment is a table's headers. It will be treated as child of
// another TABLE TextSegment if its span is subspan of another TextSegment
// with type TABLE.
TABLE_HEADER = 7;

// The text segment is a row in table. It will be treated as child of
// another TABLE TextSegment if its span is subspan of another TextSegment
// with type TABLE.
TABLE_ROW = 8;

// The text segment is a cell in table. It will be treated as child of
// another TABLE_ROW TextSegment if its span is subspan of another
// TextSegment with type TABLE_ROW.
TABLE_CELL = 9;
}

// Text Segment that represents a segment in
// [document_text][google.cloud.automl.v1beta1.Document.document_text].
TextSegment text_segment = 1;

// Page number of the
// [text_segment][google.cloud.automl.v1beta1.Document.Layout.text_segment]
// in the original document, starts from 1.
int32 page_number = 2;

// The position of the
// [text_segment][google.cloud.automl.v1beta1.Document.Layout.text_segment]
// in the page. Contains exactly 4
//
// [normalized_vertices][google.cloud.automl.v1beta1.BoundingPoly.normalized_vertices]
// and they are connected by edges in the order provided, which will
// represent a rectangle parallel to the frame. The
// [NormalizedVertex-s][google.cloud.automl.v1beta1.NormalizedVertex] are
// relative to the page.
// Coordinates are based on top-left as point (0,0).
BoundingPoly bounding_poly = 3;

// The type of the
// [text_segment][google.cloud.automl.v1beta1.Document.Layout.text_segment]
// in document.
TextSegmentType text_segment_type = 4;
}

// An input config specifying the content of the document.
DocumentInputConfig input_config = 1;

// The plain text version of this document.
TextSnippet document_text = 2;

// Describes the layout of the document.
// Sorted by [page_number][].
repeated Layout layout = 3;

// The dimensions of the page in the document.
DocumentDimensions document_dimensions = 4;

// Number of pages in the document.
int32 page_count = 5;
}

// A representation of a row in a relational table.
Expand Down
85 changes: 62 additions & 23 deletions protos/google/cloud/automl/v1beta1/io.proto
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Original file line number Diff line number Diff line change
Expand Up @@ -140,20 +140,25 @@ option ruby_package = "Google::Cloud::AutoML::V1beta1";
// CSV file(s) with each line in format:
// ML_USE,GCS_FILE_PATH
// GCS_FILE_PATH leads to a .JSONL (that is, JSON Lines) file which
// either imports text in-line or as documents.
// either imports text in-line or as documents. Any given
// .JSONL file must be 100MB or smaller.
// The in-line .JSONL file contains, per line, a proto that wraps a
// TextSnippet proto (in json representation) followed by one or more
// AnnotationPayload protos (called annotations), which have
// display_name and text_extraction detail populated. The given text
// is expected to be annotated exhaustively, for example, if you look
// for animals and text contains "dolphin" that is not labeled, then
// "dolphin" is assumed to not be an animal. Any given text snippet
// content must have 30,000 characters or less, and also be UTF-8 NFC
// encoded (ASCII already is). The document .JSONL file contains, per line, a proto that wraps a
// Document proto with input_config set. Only PDF documents are
// supported now, and each document may be up to 2MB large. Currently
// annotations on documents cannot be specified at import. Any given
// .JSONL file must be 100MB or smaller.
// content must be 10KB or smaller, and also be UTF-8 NFC encoded
// (ASCII already is).
// The document .JSONL file contains, per line, a proto that wraps a
// Document proto. The Document proto must have either document_text
// or input_config set. In document_text case, the Document proto may
// also contain the spatial information of the document, including
// layout, document dimension and page number. In input_config case,
// only PDF documents are supported now, and each document may be up
// to 2MB large. Currently, annotations on documents cannot be
// specified at import.
// Three sample CSV rows:
// TRAIN,gs://folder/file1.jsonl
// VALIDATE,gs://folder/file2.jsonl
Expand All @@ -162,27 +167,61 @@ option ruby_package = "Google::Cloud::AutoML::V1beta1";
// with artificial line breaks, but the only actual line break is
// denoted by \n).:
// {
// "text_snippet": {
// "content": "dog car cat"
// } "annotations": [
// {
// "display_name": "animal",
// "text_extraction": {
// "text_segment": {"start_offset": 0, "end_offset": 3}
// "document": {
// "document_text": {"content": "dog cat"}
// "layout": [
// {
// "text_segment": {
// "start_offset": 0,
// "end_offset": 3,
// },
// "page_number": 1,
// "bounding_poly": {
// "normalized_vertices": [
// {"x": 0.1, "y": 0.1},
// {"x": 0.1, "y": 0.3},
// {"x": 0.3, "y": 0.3},
// {"x": 0.3, "y": 0.1},
// ],
// },
// "text_segment_type": TOKEN,
// },
// {
// "text_segment": {
// "start_offset": 4,
// "end_offset": 7,
// },
// "page_number": 1,
// "bounding_poly": {
// "normalized_vertices": [
// {"x": 0.4, "y": 0.1},
// {"x": 0.4, "y": 0.3},
// {"x": 0.8, "y": 0.3},
// {"x": 0.8, "y": 0.1},
// ],
// },
// "text_segment_type": TOKEN,
// }
// },
//
// ],
// "document_dimensions": {
// "width": 8.27,
// "height": 11.69,
// "unit": INCH,
// }
// "page_count": 1,
// },
// "annotations": [
// {
// "display_name": "vehicle",
// "text_extraction": {
// "text_segment": {"start_offset": 4, "end_offset": 7}
// }
// "display_name": "animal",
// "text_extraction": {"text_segment": {"start_offset": 0,
// "end_offset": 3}}
// },
// {
// "display_name": "animal",
// "text_extraction": {
// "text_segment": {"start_offset": 8, "end_offset": 11}
// }
// },
// "text_extraction": {"text_segment": {"start_offset": 4,
// "end_offset": 7}}
// }
// ],
// }\n
// {
Expand Down
32 changes: 23 additions & 9 deletions protos/google/cloud/automl/v1beta1/prediction_service.proto
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Original file line number Diff line number Diff line change
Expand Up @@ -18,12 +18,12 @@ syntax = "proto3";
package google.cloud.automl.v1beta1;

import "google/api/annotations.proto";
import "google/api/client.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";
import "google/api/client.proto";

option go_package = "google.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl";
option java_multiple_files = true;
Expand All @@ -38,7 +38,8 @@ option ruby_package = "Google::Cloud::AutoML::V1beta1";
// 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";
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.
Expand Down Expand Up @@ -66,12 +67,14 @@ service PredictionService {
};
}

// Perform a batch prediction. Unlike the online [Predict][google.cloud.automl.v1beta1.PredictionService.Predict], batch
// 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.
// 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
Expand All @@ -86,7 +89,8 @@ service PredictionService {
}
}

// Request message for [PredictionService.Predict][google.cloud.automl.v1beta1.PredictionService.Predict].
// Request message for
// [PredictionService.Predict][google.cloud.automl.v1beta1.PredictionService.Predict].
message PredictRequest {
// Name of the model requested to serve the prediction.
string name = 1;
Expand Down Expand Up @@ -122,12 +126,20 @@ message PredictRequest {
map<string, string> params = 3;
}

// Response message for [PredictionService.Predict][google.cloud.automl.v1beta1.PredictionService.Predict].
// 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:
Expand All @@ -146,7 +158,8 @@ message PredictResponse {
map<string, string> metadata = 2;
}

// Request message for [PredictionService.BatchPredict][google.cloud.automl.v1beta1.PredictionService.BatchPredict].
// Request message for
// [PredictionService.BatchPredict][google.cloud.automl.v1beta1.PredictionService.BatchPredict].
message BatchPredictRequest {
// Name of the model requested to serve the batch prediction.
string name = 1;
Expand Down Expand Up @@ -226,7 +239,8 @@ message BatchPredictRequest {

// 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].
// by the
// [PredictionService.BatchPredict][google.cloud.automl.v1beta1.PredictionService.BatchPredict].
message BatchPredictResult {
// Additional domain-specific prediction response metadata.
//
Expand Down

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