Detect text in a document: Bounds

Returns the bounds for the boxes around the text detected in a document.

Explore further

For detailed documentation that includes this code sample, see the following:

• Dense document text detection tutorial

Code sample

Python

Before trying this sample, follow the Python setup instructions in the Vision quickstart using client libraries. For more information, see the Vision Python API reference documentation.

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def get_document_bounds(image_file, feature):
    """Returns document bounds given an image."""
    client = vision.ImageAnnotatorClient()

    bounds = []

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

    image = vision.Image(content=content)

    response = client.document_text_detection(image=image)
    document = response.full_text_annotation

    # Collect specified feature bounds by enumerating all document features
    for page in document.pages:
        for block in page.blocks:
            for paragraph in block.paragraphs:
                for word in paragraph.words:
                    for symbol in word.symbols:
                        if feature == FeatureType.SYMBOL:
                            bounds.append(symbol.bounding_box)

                    if feature == FeatureType.WORD:
                        bounds.append(word.bounding_box)

                if feature == FeatureType.PARA:
                    bounds.append(paragraph.bounding_box)

            if feature == FeatureType.BLOCK:
                bounds.append(block.bounding_box)

    # The list `bounds` contains the coordinates of the bounding boxes.
    return bounds

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