stouputils.data_science.data_processing.image.resize module

resize_image(image: ndarray[Any, dtype[Any]], width: int, height: int, resample: Resampling | int = Resampling.LANCZOS, ignore_dtype: bool = False) → ndarray[Any, dtype[Any]]

Resize an image to a new width and height.

Parameters:

• image (NDArray[Any]) – Image to resize

• width (int) – New width

• height (int) – New height

• resample (Image.Resampling | int) – Resampling method

• ignore_dtype (bool) – Ignore the dtype check

Returns:

Image with resized dimensions

Return type:

NDArray[Any]

>>> ## Basic tests
>>> image = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
>>> resized = resize_image(image.astype(np.uint8), 6, 6)
>>> resized.shape
(6, 6)

>>> img = np.ones((5, 5), dtype=np.uint8) * 255
>>> resized = resize_image(img, 10, 10)
>>> resized.shape
(10, 10)

>>> rgb = np.full((3, 3, 3), 128, dtype=np.uint8)
>>> resized_rgb = resize_image(rgb, 6, 6)
>>> resized_rgb.shape
(6, 6, 3)

>>> ## Test invalid inputs
>>> resize_image("not an image", 10, 10)
Traceback (most recent call last):
        ...
AssertionError: Image must be a numpy array

>>> resize_image(image.astype(np.uint8), "10", 10)
Traceback (most recent call last):
        ...
AssertionError: width must be integer, got <class 'str'>

>>> resize_image(image.astype(np.uint8), 10, "10")
Traceback (most recent call last):
        ...
AssertionError: height must be integer, got <class 'str'>