Class OutputConfig (0.9.0)

Version 0.9.0

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Output configuration for ExportData.

As destination the [gcs_destination][google.cloud.automl.v1.OutputConfig.gcs_destination] must be set unless specified otherwise for a domain. If gcs_destination is set then in the given directory a new directory is created. Its name will be "export_data--", where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Only ground truth annotations are exported (not approved annotations are not exported).

The outputs correspond to how the data was imported, and may be used as input to import data. The output formats are represented as EBNF with literal commas and same non-terminal symbols definitions are these in import data's InputConfig:

• For Image Classification: CSV file(s) image_classification_1.csv, image_classification_2.csv,...,\ image_classification_N.csv\ with each line in format: ML_USE,GCS_FILE_PATH,LABEL,LABEL,... where GCS_FILE_PATHs point at the original, source locations of the imported images. For MULTICLASS classification type, there can be at most one LABEL per example.

• For Image Object Detection: CSV file(s) image_object_detection_1.csv, image_object_detection_2.csv,...,\ image_object_detection_N.csv with each line in format: ML_USE,GCS_FILE_PATH,[LABEL],(BOUNDING_BOX | ,,,,,,,) where GCS_FILE_PATHs point at the original, source locations of the imported images.

• For Text Classification: In the created directory CSV file(s) text_classification_1.csv, text_classification_2.csv, ...,\ text_classification_N.csv will be created where N depends on the total number of examples exported. Each line in the CSV is of the format: ML_USE,GCS_FILE_PATH,LABEL,LABEL,... where GCS_FILE_PATHs point at the exported .txt files containing the text content of the imported example. For MULTICLASS classification type, there will be at most one LABEL per example.

• For Text Sentiment: In the created directory CSV file(s) text_sentiment_1.csv, text_sentiment_2.csv, ...,\ text_sentiment_N.csv will be created where N depends on the total number of examples exported. Each line in the CSV is of the format: ML_USE,GCS_FILE_PATH,SENTIMENT where GCS_FILE_PATHs point at the exported .txt files containing the text content of the imported example.

• For Text Extraction: CSV file text_extraction.csv, with each line in format: ML_USE,GCS_FILE_PATH GCS_FILE_PATH leads to a .JSONL (i.e. JSON Lines) file which contains, per line, a proto that wraps a TextSnippet proto (in json representation) followed by AnnotationPayload protos (called annotations). If initially documents had been imported, the JSONL will point at the original, source locations of the imported documents.

• For Translation: CSV file translation.csv, with each line in format: ML_USE,GCS_FILE_PATH GCS_FILE_PATH leads to a .TSV file which describes examples that have given ML_USE, using the following row format per line: TEXT_SNIPPET (in source language) \tTEXT_SNIPPET (in target language)

  Required. The Google Cloud Storage location where the output is to be written to. For Image Object Detection, Text Extraction in the given directory a new directory will be created with name: export_data-- where timestamp is in YYYY- MM-DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory.