gcloud beta ml vision detect-text-pdf

NAME: gcloud beta ml vision detect-text-pdf - detect and transcribe text from PDF files stored in Google Cloud Storage
SYNOPSIS: gcloud beta ml vision detect-text-pdf INPUT_FILE OUTPUT_PATH [ --batch-size = BATCH_SIZE ] [ --model-version = MODEL_VERSION ; default="builtin/stable"] [ GCLOUD_WIDE_FLAG … ]
DESCRIPTION: (BETA) Detect and transcribe text from PDF files stored in Google Cloud Storage.
The Vision API accepts PDF files up to 2000 pages. Larger files will return an error.
EXAMPLES: To detect text for input PDF file 'gs://my_bucket/input_file' and store output in 'gs://my_bucket/out_put_prefix':
gcloud beta ml vision detect-text-pdf gs://my_bucket/input_file gs://my_bucket/out_put_prefix
POSITIONAL ARGUMENTS: INPUT_FILE

Google Cloud Storage location to read the input from. It must be in Google Cloud Storage format (gs://bucket/object)

OUTPUT_PATH

Google Cloud Storage location to store the output file. It must be in Google Cloud Storage format (gs://bucket/object)
FLAGS: --batch-size = BATCH_SIZE

Maximum number of response protos to put into each output JSON file on Google Cloud Storage. The valid range is [1, 100]. If not specified, the default value is 20.

--model-version = MODEL_VERSION ; default="builtin/stable"

Model version to use for the feature. MODEL_VERSION must be one of: builtin/latest , builtin/stable .
GCLOUD WIDE FLAGS: These flags are available to all commands: --access-token-file , --account , --billing-project , --configuration , --flags-file , --flatten , --format , --help , --impersonate-service-account , --log-http , --project , --quiet , --trace-token , --user-output-enabled , --verbosity .
Run $ gcloud help for details.
API REFERENCE: This command uses the vision/v1 API. The full documentation for this API can be found at: https://cloud.google.com/vision/
NOTES: This command is currently in beta and might change without notice. These variants are also available:
gcloud ml vision detect-text-pdf

gcloud alpha ml vision detect-text-pdf

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gcloud beta ml vision detect-text-pdf