gcloud beta ml vision detect-text-pdf - detect and transcribe text from PDF files stored in Google Cloud Storage
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 ...]
(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.
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
- 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)
- --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.
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.
This command uses the vision/v1 API. The full documentation for this API can be found at: https://cloud.google.com/vision/
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