# Imports
from PIL import Image
from .common import Any, NDArray, check_image, np
# Functions
[docs]
def resize_image(
image: NDArray[Any],
width: int,
height: int,
resample: Image.Resampling | int = Image.Resampling.LANCZOS,
ignore_dtype: bool = False
) -> NDArray[Any]:
""" Resize an image to a new width and height.
Args:
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:
NDArray[Any]: Image with resized dimensions
>>> ## 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'>
"""
# Check input data
check_image(image, ignore_dtype=ignore_dtype)
assert isinstance(width, int), f"width must be integer, got {type(width)}"
assert isinstance(height, int), f"height must be integer, got {type(height)}"
assert isinstance(resample, Image.Resampling | int), f"resample must be Image.Resampling, got {type(resample)}"
# Resize image
new_image: Image.Image = Image.fromarray(image)
new_image = new_image.resize((width, height), resample=resample)
return np.array(new_image)
