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load_image

Load an image file and return its data as a list of NumPy arrays in RGB format.

This function reads an image file from the specified path, validates its existence and format, and returns the image data as a list of NumPy arrays in RGB format. For multi-page image formats like TIFF, each page is returned as a separate array.

Parameters:

Name Type Description Default
image_path str

The path to the image file to be loaded.

 required

Returns:

Type Description
list[ndarray]

list[np.ndarray]: A list of NumPy arrays, where each array represents an image
list[ndarray]

in RGB format. For single-page images, the list contains one element.

Raises:

Type Description
FileNotFoundError

If the specified file does not exist.
ValueError
  • If the file format is not supported.
  • If the file contains invalid image data.
  • If the file is a PDF.
  • If any side of the image (width or height) is less than 32 pixels.
Notes
  • Supported input formats are: ["jpg", "jpeg", "png", "bmp", "tiff", "tif", "pdf"].
  • Multi-page formats like TIFF are supported, and each page is returned as a separate NumPy array.
  • The returned image data is in BGR format, which is commonly used for image processing tasks.
  • PDF files are not supported by this function. Use load_pdf() for handling PDFs.
Example 
from yomitoku.data.functions import load_image

pages = load_image("example.tiff")
print(len(pages))  # Output: Number of pages in the TIFF file
print(pages[0].shape)  # Output: (height, width, channels) for the first page
Source code in src/yomitoku/data/functions.py 
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def load_image(image_path: str) -> list[np.ndarray]:
    """
    Load an image file and return its data as a list of NumPy arrays in RGB format.

    This function reads an image file from the specified path, validates its existence
    and format, and returns the image data as a list of NumPy arrays in RGB format.
    For multi-page image formats like TIFF, each page is returned as a separate array.

    Args:
        image_path (str): The path to the image file to be loaded.

    Returns:
        list[np.ndarray]: A list of NumPy arrays, where each array represents an image
        in RGB format. For single-page images, the list contains one element.

    Raises:
        FileNotFoundError: If the specified file does not exist.
        ValueError:
            - If the file format is not supported.
            - If the file contains invalid image data.
            - If the file is a PDF.
            - If any side of the image (width or height) is less than 32 pixels.

    Notes:
        - Supported input formats are: ["jpg", "jpeg", "png", "bmp", "tiff", "tif", "pdf"].
        - Multi-page formats like TIFF are supported, and each page is returned as a
          separate NumPy array.
        - The returned image data is in BGR format, which is commonly used for image
          processing tasks.
        - PDF files are not supported by this function. Use `load_pdf()` for handling PDFs.

    Example:
        ```python
        from yomitoku.data.functions import load_image

        pages = load_image("example.tiff")
        print(len(pages))  # Output: Number of pages in the TIFF file
        print(pages[0].shape)  # Output: (height, width, channels) for the first page
        ```
    """
    image_path = Path(image_path)
    if not image_path.exists():
        raise make_error(ErrorCode.IMAGE_FILE_NOT_FOUND)

    ext = image_path.suffix[1:].lower()
    if ext not in SUPPORT_INPUT_FORMAT:
        raise make_error(ErrorCode.UNSUPPORTED_IMAGE_FORMAT)

    if ext == "pdf":
        raise make_error(ErrorCode.PDF_NOT_SUPPORTED_BY_LOAD_IMAGE)
    try:
        img = Image.open(image_path)
    except Exception:
        raise make_error(ErrorCode.INVALID_IMAGE_DATA)

    pages = []
    if ext in ["tif", "tiff"]:
        try:
            while True:
                img_arr = np.array(img.copy().convert("RGB"))
                validate_image(img_arr)
                pages.append(img_arr[:, :, ::-1])
                img.seek(img.tell() + 1)
        except EOFError:
            pass
    else:
        img_arr = np.array(img.convert("RGB"))
        validate_image(img_arr)
        pages.append(img_arr[:, :, ::-1])

    return pages