# Imports
from .common import Any, NDArray, check_image, cv2, np
# Functions
[docs]
def shear_image(image: NDArray[Any], x: float, y: float, ignore_dtype: bool = False) -> NDArray[Any]:
""" Shear an image
Args:
image (NDArray[Any]): Image to shear
x (float): Shearing along the x axis (between -180 and 180)
y (float): Shearing along the y axis (between -180 and 180)
ignore_dtype (bool): Ignore the dtype check
Returns:
NDArray[Any]: Sheared image
>>> ## Basic tests
>>> image = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
>>> shear_image(image.astype(np.uint8), 15, 0).tolist()
[[1, 2, 3], [3, 5, 6], [3, 7, 8]]
>>> shear_image(image.astype(np.float32), 0, 15).tolist()
[[1.0, 1.4375, 1.40625], [4.0, 4.15625, 4.40625], [7.0, 7.15625, 7.40625]]
>>> ## Test invalid inputs
>>> shear_image(image.astype(np.uint8), 200, 0)
Traceback (most recent call last):
...
AssertionError: x must be between -180 and 180, got 200
>>> shear_image(image.astype(np.uint8), 0, -200)
Traceback (most recent call last):
...
AssertionError: y must be between -180 and 180, got -200
>>> shear_image("not an image", 0, 0)
Traceback (most recent call last):
...
AssertionError: Image must be a numpy array
"""
# Check input data
check_image(image, ignore_dtype=ignore_dtype)
assert isinstance(x, float | int), f"x must be a number, got {type(x)}"
assert isinstance(y, float | int), f"y must be a number, got {type(y)}"
assert -180 <= x <= 180, f"x must be between -180 and 180, got {x}"
assert -180 <= y <= 180, f"y must be between -180 and 180, got {y}"
# Get image dimensions
height, width = image.shape[:2]
# Convert relative shear angles to absolute values
x_shear: float = np.tan(np.radians(x))
y_shear: float = np.tan(np.radians(y))
# Create shear matrix
shear_matrix: NDArray[Any] = np.array([
[1, x_shear, 0],
[y_shear, 1, 0]
], dtype=np.float32)
# Apply affine transformation
return cv2.warpAffine(image, shear_matrix, (width, height))
