def detect_handwritten_ocr()

in vision/snippets/detect/beta_snippets.py [0:0]

• 32 lines of code
• 10 McCabe index (conditional complexity)

def detect_handwritten_ocr(path):
    """Detects handwritten characters in a local image.

    Args:
    path: The path to the local file.
    """
    from google.cloud import vision_v1p3beta1 as vision

    client = vision.ImageAnnotatorClient()

    with open(path, "rb") as image_file:
        content = image_file.read()

    image = vision.Image(content=content)

    # Language hint codes for handwritten OCR:
    # en-t-i0-handwrit, mul-Latn-t-i0-handwrit
    # Note: Use only one language hint code per request for handwritten OCR.
    image_context = vision.ImageContext(language_hints=["en-t-i0-handwrit"])

    response = client.document_text_detection(image=image, image_context=image_context)

    print(f"Full Text: {response.full_text_annotation.text}")
    for page in response.full_text_annotation.pages:
        for block in page.blocks:
            print(f"\nBlock confidence: {block.confidence}\n")

            for paragraph in block.paragraphs:
                print("Paragraph confidence: {}".format(paragraph.confidence))

                for word in paragraph.words:
                    word_text = "".join([symbol.text for symbol in word.symbols])
                    print(
                        "Word text: {} (confidence: {})".format(
                            word_text, word.confidence
                        )
                    )

                    for symbol in word.symbols:
                        print(
                            "\tSymbol: {} (confidence: {})".format(
                                symbol.text, symbol.confidence
                            )
                        )

    if response.error.message:
        raise Exception(
            "{}\nFor more info on error messages, check: "
            "https://cloud.google.com/apis/design/errors".format(response.error.message)
        )