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imageloading

imageloading

Module for image loading

Classes

ImgShapeError

Bases: Exception

Error when the image has the wrong shape

Functions

convert_to_3channel_img 

convert_to_3channel_img(input_img)

Converts an image (as np.ndarray) to a one with 3 channels

Parameters:

  • input_img (ndarray) –

    image object as np.ndarray

Returns:

  • ndarray –

    image as np.ndarray with 3 channels

Source code in niceml/utilities/imageloading.py 
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def convert_to_3channel_img(input_img: np.ndarray) -> np.ndarray:  # QUEST: still used?
    """
    Converts an image (as np.ndarray) to a one with 3 channels

    Args:
        input_img: image object as np.ndarray

    Returns:
        image as np.ndarray with 3 channels
    """
    if len(input_img.shape) not in [2, 3]:
        raise ImgShapeError(
            f"Image cannot be broadcast to a " f"3 channel image: {input_img.shape}"
        )

    if len(input_img.shape) == 2:
        return np.concatenate([input_img[:, :, np.newaxis]] * 3, axis=2)

    if input_img.shape[2] == 3:
        return input_img

    if input_img.shape[2] == 1:
        return np.concatenate([input_img] * 3, axis=2)

    raise ImgShapeError(
        f"Image cannot be broadcast to a " f"3 channel image: {input_img.shape}"
    )

load_img_uint8 

load_img_uint8(
    image_path,
    file_system=None,
    target_image_size=None,
    interpolation=cv2.INTER_LINEAR,
)

Loads an image from arbitrary source ('file_system') and returns an uint8 np.ndarray

Parameters:

  • image_path (Union[str, LocationConfig]) –

    Path of image file to load

  • file_system (Optional[AbstractFileSystem], default: None ) –

    Allow the function to be used with different file systems; default = local

  • target_image_size (Optional[ImageSize], default: None ) –

    Target size of loaded image

  • interpolation (int, default: INTER_LINEAR ) –

    Interpolation of resizing

Returns:

  • ndarray –

    Loaded image object with target size in uint8 format

Source code in niceml/utilities/imageloading.py 
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def load_img_uint8(
    image_path: Union[str, LocationConfig],
    file_system: Optional[AbstractFileSystem] = None,
    target_image_size: Optional[ImageSize] = None,
    interpolation: int = cv2.INTER_LINEAR,
) -> np.ndarray:
    """
    Loads an image from arbitrary source ('file_system') and returns an uint8 np.ndarray

    Args:
        image_path: Path of image file to load
        file_system: Allow the function to be used with different file systems; default = local
        target_image_size: Target size of loaded image
        interpolation: Interpolation of resizing

    Returns:
        Loaded image object with target size in uint8 format
    """
    file_system: AbstractFileSystem = file_system or LocalFileSystem()
    try:
        if isinstance(image_path, LocationConfig):
            image_path = image_path.uri
        with file_system.open(image_path) as fs_file:
            image = Image.open(fs_file).copy()
        np_array = np.array(image)
        if np_array.dtype == bool:
            np_array = np_array.astype(np.uint8)
            np_array *= 255
    except OSError:
        with TemporaryDirectory() as tmp_dir:
            tmp_file = join(tmp_dir, basename(image_path))
            file_system.get_file(image_path, tmp_file)
            np_array = cv2.imread(tmp_file)  # pylint: disable=no-member
    if target_image_size is not None and not target_image_size.np_array_has_same_size(
        np_array
    ):
        np_array = cv2.resize(
            np_array, target_image_size.to_numpy_shape(), interpolation=interpolation
        )
    return np_array