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from typing import Callable
import numpy as np
from typing_extensions import Concatenate, ParamSpec
ImageOp = Callable[[np.ndarray], np.ndarray]
"""
An image processing operation that takes an image and produces a new image.
The given image is guaranteed to *not* be modified.
"""
def clipped(op: ImageOp) -> ImageOp:
"""
Ensures that all values in the returned image are between 0 and 1.
"""
return lambda i: np.clip(op(i), 0, 1)
P = ParamSpec("P")
def to_op(fn: Callable[Concatenate[np.ndarray, P], np.ndarray]) -> Callable[P, ImageOp]:
"""
Applies a form of currying to convert the given function into a constructor for an image operation.
Example: Simple resize method could be defined as follows: `resize(np.ndarray, Size2D) -> np.ndarray`.
It takes an image and its new size and returns the resized image.
If we want to convert it to an image operation, we have to create a function with the following signature: `resize_op(Size2D) -> ImageOp`.
The implementation of this function would be rather simple, it would simply take all arguments of `resize` except for the image like this:
```py
def resize_op(size: Size2D) -> ImageOp:
return lambda img: resize(img, size)
```
`to_op` does exactly this transformation, but for any number of arguments.
Note: This only works if the input image is the first argument of the given function.
"""
def p(*args: P.args, **kwargs: P.kwargs) -> ImageOp:
return lambda i: fn(i, *args, **kwargs)
return p
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