Set the OCR agent

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Task

You want to specify the type of agent that you use when performing optical character recognition (OCR) on files, such as images and PDFs.

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Approach

Set the environment variable named OCR_AGENT to one of the following supported values:

• unstructured.partition.utils.ocr_models.tesseract_ocr.OCRAgentTesseract to use Tesseract OCR. This is the default if not otherwise specified.
• unstructured.partition.utils.ocr_models.paddle_ocr.OCRAgentPaddle to use Paddle OCR.
• unstructured.partition.utils.ocr_models.google_vision_ocr.OCRAgentGoogleVision to use Google Cloud Vision OCR.

Also, be sure to install the corresponding OCR agent and its dependencies, if you have not already done so:

• For Tesseract OCR, see the dependency list.
• For Paddle OCR, see the dependency list.
• For Google Cloud Vision OCR, see the dependency list.

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Example code

This example uses a PNG file with an embedded combination of English and Korean text. This example uses Tesseract OCR.

Language codes will differ depending on the OCR agent you use:

• For Tesseract OCR, see the language codes list.
• For Paddle OCR, see the language codes list and language names list.
• For Google Cloud Vision OCR, see the language codes list.

import json

from unstructured.partition.image import partition_image

# Source: https://github.com/Unstructured-IO/unstructured-ingest/blob/main/example-docs/img/english-and-korean.png
# Path to the local file to process, relative to this .py file.
filename = "local-ingest-png/english-and-korean.png"

elements = partition_image(
  filename=filename,
  strategy="ocr_only",
  languages=["eng", "kor"] # Language codes differ by the OCR agent used.
)

# Convert the list of returned elements into a list of dictionaries for printing or saving.
element_dicts = [element.to_dict() for element in elements]

# Print the list.
print(json.dumps(element_dicts, indent=2))

# Or, save the list locally:
#
# file = "local-ingest-output/english-and-korean.json"
#
# with open(file, "w") as file:
#     json.dump(element_dicts, file, indent=2)