stouputils.data_science.data_processing.image.salt_pepper module

salt_pepper_image(image: ndarray[Any, dtype[Any]], density: float, ignore_dtype: bool = False) → ndarray[Any, dtype[Any]]

Add salt and pepper noise to an image.

Parameters:

• image (NDArray[Any]) – Image to add noise to

• density (float) – Density of the noise (between 0 and 1)

• ignore_dtype (bool) – Ignore the dtype check

Returns:

Image with salt and pepper noise

Return type:

NDArray[Any]

>>> ## Basic tests
>>> image = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
>>> noisy = salt_pepper_image(image.astype(np.uint8), 0.1)
>>> noisy.shape == image.shape
True

>>> np.random.seed(42)
>>> img = np.full((4,4), 128, dtype=np.uint8)
>>> noisy = salt_pepper_image(img, 1.0)
>>> sorted(np.unique(noisy).tolist())  # Should only contain 0 and 255
[0, 255]

>>> rgb = np.full((3,3,3), 128, dtype=np.uint8)
>>> noisy_rgb = salt_pepper_image(rgb, 0.1)
>>> noisy_rgb.shape == (3,3,3)
True

>>> ## Test invalid inputs
>>> salt_pepper_image("not an image", 0.1)
Traceback (most recent call last):
        ...
AssertionError: Image must be a numpy array

>>> salt_pepper_image(image.astype(np.uint8), "0.1")
Traceback (most recent call last):
        ...
AssertionError: density must be a number, got <class 'str'>

>>> salt_pepper_image(image.astype(np.uint8), 1.5)
Traceback (most recent call last):
        ...
AssertionError: density must be between 0 and 1, got 1.5